2 篇博文 含有标签「fine-tuning」

The final week of May 2026 (May 27–30) proved to be the grand culmination of our experimental modeling phase. After weeks of hyperparameter tuning, GPU out-of-memory crashes, and dataset revisions, our 4th Fine-Tuning cycle (fine_tuning_4) crossed the finish line.

This post reveals the technical breakthrough that resolved the chronic "over-counseling" trap, quantitative validation of our golden weight Checkpoint-4400, and the end-to-end system architecture designed for real-world deployment.

April 1, 2026, was the day our engineering team launched the automated preprocessing pipeline for the massive counseling corpora that would form the foundation of Maeumjigi. Training a high-performance open-source Large Language Model (LLM) like Meta Llama 3.1 requires rigorous data hygiene: converting unstructured multi-party dialogues into clean, token-bounded, and special-token-aligned instruction datasets.