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gemma4-31b-rovochat-lora-r32-lr1e4
tzchen07/gemma4-31b-rovochat-lora-r32-lr1e4
gemma4-31b-rovochat-lora-r32-lr1e4 is a machine learning model from tzchen07. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as gemma.
LoRA SFT (rank=32, alpha=64, LR=1e-4, seq=16384, 1 epoch) merged into google/gemma-4-31B-it. One point in a rank x LR sweep on the Rovo Chat Orchestrator tool-calling task.
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At a glance
- License
- gemma
- Model type
- gemma4
- Access
- Public
- Created
- Jul 1, 2026
- Updated
- Jul 1, 2026
- SHA
- 3bf863e2
Base models
Model card
From the Hugging Face model README
Gemma-4-31B Rovo Chat Orchestrator — LoRA r=32 (LR 1e-4), merged
LoRA SFT (rank=32, alpha=64, LR=1e-4, seq=16384, 1 epoch) merged into google/gemma-4-31B-it. One point in a rank x LR sweep on the Rovo Chat Orchestrator tool-calling task.
Eval (725 held-out examples, Claude Opus 4.8 judge)
| metric | this model | base gemma-4-31B-it |
|---|---|---|
| Text AA (shallow) | 86.2% | 96.1% |
| Tool AA (shallow) | 26.3% | 53.2% |
| Overall AA | 70.5% | 84.8% |
| Text AA Deep (binary, 1-5 rubric) | pending% | 86.7% |
| Deep quality mean (1-5) | pending | 4.27 |
| False-tool-trigger rate | 10.3% | 1.9% |
| Runaway rate | 7.0% | 0.3% |
Sweep finding
Across the rank x LR grid, learning rate dominates both accuracy and stability: every LR=5e-5 config beats every LR=1e-4 config on overall AA and runaway rate. Instability is approximately (adapter capacity x LR) = how far the weights travel from the RLHF-aligned base. The sweet spot is r=16, LR=5e-5 (sibling repo tzchen07/gemma4-31b-rovochat-lora-r16-lr5e5).
No fine-tune beats the base -it model overall — narrow-domain tuning erodes the base's tool-vs-text calibration faster than it gains tool accuracy. Base wins on text AA, overall, and stability; the best tune improves only tool AA (+3 pts). Companion full-FT analysis (LR is the killing factor): tzchen07/gemma4-31b-rovochat-sft-v3.
- Type
- gemma4
- License
- gemma
- Created
- Jul 1, 2026
- Updated
- Jul 1, 2026