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Writing an LLM from scratch, part 32m -- Interventions: conclusion

The author completed training a GPT-2-like model in 44 hours on a local machine, achieving performance close to GPT-2 small. Through systematic testing of various interventions, they identified learning rate adjustments and dropout removal as most effective for improving model loss. The author plans to next implement an LLM from scratch using JAX without reference to their book.

LLM from scratch (32l) – Interventions: updated instruction fine-tuning results
2.5
The article presents updated results from instruction fine-tuning experiments on a 32-layer language model built from scratch. It discusses interventions and performance improvements achieved through the fine-tuning process.
LLM from scratch, part 33 – what I learned from the appendices
2.0
The author reflects on insights gained from working through appendices in their LLM from scratch series, noting that these supplementary materials provided valuable practical knowledge and deeper understanding of implementation details beyond the main content.

Writing an LLM from scratch, part 32m -- Interventions: conclusion

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LLM from scratch (32l) – Interventions: updated instruction fine-tuning results

LLM from scratch, part 33 – what I learned from the appendices