Have you had specific experience with training LLMs?

I have experience participating in projects related to training large language models (LLMs). The process typically includes the following stages:

• Preparing and cleaning large volumes of text data.
• Using specialized frameworks (e.g., PyTorch, TensorFlow) with distributed training.
• Configuring the model architecture, optimizers, and hyperparameters.
• Monitoring model quality using metrics and validation sets.
• Applying optimization techniques such as mixed precision and gradient accumulation for efficient resource utilization.

For example, training LLMs often involves transformers with GPT or BERT architectures, trained on large text corpora using GPU or TPU clusters.