In the news
Three Tests to Run Before You Switch from LoRA to FullFT
Fireworks AI · Published · 3 min read
In 30 seconds
- What happened
- Fireworks AI tested whether LoRA gaps versus full fine-tuning stem from data coverage, learning rate tuning, or adapter rank limits.
- Why it matters
- Engineers choosing between LoRA and full fine-tuning should run these three tests before assuming full fine-tuning is necessary.
- Watch out
- Test results are task-specific on Qwen3.5-9B; findings may not generalize to other models, domains, or your specific use case.
Listen to this summary
- lora
The patterns behind this
- Reinforcement Learning from Human Feedback
- Web Bot Auth (Signed Agents)
- RL from Verifiable Rewards (RLVR)
Each one covers how the technique works, when it earns its cost, and where it breaks.
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