Unity ML-Agents | Pretrain an LLM from Scratch with Sentence Transformers | Part 12
0Welcome back to our Tau LLM series! ๐
In this episode, we're taking significant strides towards production readiness and optimizing our training process. Our highlights include:
**Transition to Production Mode**: We'll be moving our project from the Unity editor to production mode, ensuring all necessary scripts and data files are correctly copied over during the build process.
**Training Pair Implementation**: Watch as we set up training pairs of AgentTrainers and TauAgents, and introduce a TrainingManager to oversee the process using SemaphoreSlim tasks for efficient management.
**Network Optimization**: We've increased our network size to 1024 with 16 layers, aiming for a balanced and efficient model. We'll discuss the benefits and challenges of this setup.
**Expanded Training Set**: We'll run our model with a training set of 100 records to observe any improvements and ensure diverse data handling.
**Reward Calculation Adjustments**: Learn about our approach to refining reward calculation by starting with simpler tasks and gradually increasing difficulty, ensuring balanced training across all columns.
Join us as we build, debug, and optimize our LLM project step by step. Whether you're a beginner or an experienced developer, this episode offers valuable insights into developing, testing, and enhancing an LLM using custom tools and techniques.
Stay tuned and let's get started! ๐