AI is changing the world. Don't stay behind. Clear summaries, community insight, delivered without the noise. Subscribe to never miss a beat.

Privacy

Contact

Back to all news

lora fine-tuning developer-tools leaderboard

LoRA Speedrun – a public wall-clock leaderboard for fine-tuning techniques

GitHub - Saivineeth147/lora-speedrun: Speedrunning LoRA fine-tuning: frozen task, frozen hardware, public wall-clock leaderboard. modded-nanogpt for fine-tuning.

github.com

July 20, 2026

6 min read

🔥🔥🔥🔥🔥

54/100

Summary

GitHub repository Saivineeth147/lora-speedrun enables speedrunning LoRA fine-tuning for the Qwen2.5-1.5B model on a single L40S GPU, aiming for ≥ 57% accuracy on GSM8K. The project features a frozen task and hardware setup, with a public leaderboard that requires independent verification of timing runs conducted on Modal's sandbox using free compute credits.

Key Takeaways

The current record for LoRA fine-tuning Qwen2.5-1.5B on GSM8K is 6 minutes and 5 seconds, achieved by @Saivineeth147 using sequence packing and completion-only loss masking with 2 epochs.
The leaderboard for LoRA fine-tuning allows anyone to compete and verify records using a Modal L40S sandbox, with official timing runs covering full attempts.
The project aims to create a standardized environment for comparing different fine-tuning techniques by using frozen tasks and identical hardware across two distinct tracks.
LoRA/QLoRA techniques are prevalent in real-world fine-tuning, and this repository provides a competitive arena for these methods to be tested against each other in a public format.

Read original article