Tracking my experiments is becoming increasingly challenging. In my Reinforcement Learning using Layered Morphology (RLLM) research, I attempt to embed Large Language Models (LLMs) with ethical alignment - developmentally. To achieve this, I conduct various training experiments. The most extensive one involved 24 steps or training sets (RLLMv1), but I have since identified a simpler set with 10 steps, which I've already executed four times (RLLMv3, RLLMv7, RLLMv8 & RLLMv9). The challenge has been tracking all of the changes including the datasets and trained models. Fortunately, I discovered Whimsical, a tool perfectly suited to address this issue. (In case you are having issues tracking your projects - you can try the approach I shared here.)
Building a Research Visual Map Using Whimsical
Building a Research Visual Map Using…
Building a Research Visual Map Using Whimsical
Tracking my experiments is becoming increasingly challenging. In my Reinforcement Learning using Layered Morphology (RLLM) research, I attempt to embed Large Language Models (LLMs) with ethical alignment - developmentally. To achieve this, I conduct various training experiments. The most extensive one involved 24 steps or training sets (RLLMv1), but I have since identified a simpler set with 10 steps, which I've already executed four times (RLLMv3, RLLMv7, RLLMv8 & RLLMv9). The challenge has been tracking all of the changes including the datasets and trained models. Fortunately, I discovered Whimsical, a tool perfectly suited to address this issue. (In case you are having issues tracking your projects - you can try the approach I shared here.)