Qwen3.5-2B - luspo/rank (adamw)
vs base Qwen3.5-2B: InD acc 83.8→78.3, total output tokens 3240→223 (-93%)
gpqa_diamond (OOD) acc 7.6→31.6 (+24.1 pp, +318%)
Trained via GRPO with luspo loss, rank reward shape (alpha=0.15), adamw optimizer, lr=1.0e-06, G=8, max_steps=200, max_completion_length=8000, evaluated over 3 seeds.
Accuracy vs base Qwen3.5-2B
| Dataset | Base | Tuned (mean ± std) | Δ (pp, rel %) |
|---|---|---|---|
| gsm8k | 81.2 | 54.3 ± 4.0 | -26.8 pp, -33% |
| arc_challenge | 85.2 | 79.2 ± 0.8 | -6.0 pp, -7% |
| arc_easy | 97.7 | 94.2 ± 1.0 | -3.5 pp, -4% |
| commonsenseqa | 69.8 | 73.7 ± 3.3 | +3.8 pp, +5% |
| openbookqa | 82.3 | 77.7 ± 0.8 | -4.7 pp, -6% |
| qasc | 76.5 | 76.0 ± 0.5 | -0.5 pp, -1% |
| sciq | 93.8 | 92.8 ± 1.2 | -1.0 pp, -1% |
| mmlu_pro(OOD) | 33.8 | 31.8 ± 1.9 | -2.0 pp, -6% |
| mmlu_redux(OOD) | 52.5 | 54.0 ± 4.4 | +1.5 pp, +3% |
| gpqa_diamond(OOD) | 7.6 | 31.6 ± 3.6 | +24.1 pp, +318% |
| InD Average | 83.8 | 78.3 ± 0.3 | -5.5 pp, -7% |
| OOD | 31.4 | 39.2 ± 0.7 | +7.8 pp, +25% |
| ALL | 68.1 | 66.6 ± 0.1 | -1.5 pp, -2% |
Δ shows the absolute change in accuracy points (pp) and the relative percent change (tuned − base) / base × 100 (rel %, shown as n/a when base accuracy is 0).
Output tokens (total) vs base Qwen3.5-2B
| Dataset | Base | Tuned (mean ± std) | Reduction % |
|---|---|---|---|
| gsm8k | 4450 | 410 ± 6 | -91% |
| arc_challenge | 3157 | 196 ± 1 | -94% |
| arc_easy | 1871 | 192 ± 2 | -90% |
| commonsenseqa | 3949 | 183 ± 1 | -95% |
| openbookqa | 3378 | 183 ± 1 | -95% |
| qasc | 3932 | 207 ± 1 | -95% |
| sciq | 1944 | 194 ± 3 | -90% |
| mmlu_pro(OOD) | 6582 | 277 ± 2 | -96% |
| mmlu_redux(OOD) | 5589 | 269 ± 25 | -95% |
| gpqa_diamond(OOD) | 8001 | 289 ± 1 | -96% |
| InD Average | 3240 | 223 ± 1 | -93% |
| OOD | 6720 | 278 ± 9 | -96% |
| ALL | 4281 | 240 ± 3 | -94% |
Output tokens = total generated tokens (full completion), 3-seed mean.
Reduction = percentage decrease in mean output tokens vs base Qwen3.5-2B (negative reduction, i.e. +, means the tuned model generates more tokens).
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