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Optimizing Batch Size for Efficient Training of Large Language Models

The author encountered a bottleneck in training a large language model (RWKV v6) on a limited GPU (RTX 4050), struggling to reduce perplexity (PPL) below 50. Despite adjusting learning rates and other hyperparameters, the model plateaued. The challenge lies in finding optimal batch sizes and gradient accumulation strategies to improve model performance.

Computing & Technology, Computer Science, Machine Learning