The temperature parameter in DeepSeek R1 is primarily used to control the randomness of the model's output. It influences how the model selects words or tokens during generation, with higher temperatures leading to more diverse but potentially less coherent outputs, and lower temperatures resulting in more predictable and coherent outputs. For DeepSeek R1, a temperature range of 0.5 to 0.7 is recommended, with 0.6 being ideal, to prevent repetitive or incoherent outputs[1][3][8].
The gating mechanism in DeepSeek R1's Mixture of Experts (MoE) architecture is a separate component that dynamically selects which experts (or subsets of parameters) to activate based on the input. This mechanism ensures that only a fraction of the total parameters are used during inference, enhancing efficiency and adaptability. Specifically, DeepSeek R1 activates about 37 billion parameters out of its total 671 billion parameters[4][9].
While the temperature parameter and the gating mechanism serve distinct purposes, they both contribute to the model's overall performance and efficiency. The temperature parameter affects the output generation process by controlling the level of randomness, whereas the gating mechanism optimizes resource usage by selectively activating relevant experts. However, there is no direct interaction between these two mechanisms; they operate independently within the model's architecture.
In practice, adjusting the temperature can influence how the model generates text, but it does not directly affect which experts are activated by the gating mechanism. The gating mechanism is primarily concerned with selecting the appropriate subset of parameters based on the input, regardless of the temperature setting. This separation allows for flexible control over both the model's output coherence and its computational efficiency.
Citations:
[1] https://build.nvidia.com/deepseek-ai/deepseek-r1/modelcard
[2] https://www.vellum.ai/blog/the-training-of-deepseek-r1-and-ways-to-use-it
[3] https://www.reddit.com/r/LocalLLaMA/comments/1i81ev6/deepseek_added_recommandations_for_r1_local_use/
[4] https://writesonic.com/blog/what-is-deepseek-r1
[5] https://www.reddit.com/r/LocalLLaMA/comments/1ip73bq/deepseek_drops_recommended_r1_deployment_settings/
[6] https://arxiv.org/html/2412.19437v1
[7] https://api-docs.deepseek.com/quick_start/parameter_settings
[8] https://docs.together.ai/docs/deepseek-r1
[9] https://merlio.app/blog/deepseek-r1-complete-guide