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while-ai
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Model Details
Model Provider
while-ai
Model Tree
Qwen/Qwen2.5-1.5B-Instruct
Input Modalities
Output Modalities
Supported Functionality
| Arm | pass@1 | 95% CI | pass@k | Steps | GPU min |
|---|---|---|---|---|---|
| Base, no training | 0.36 | [0.29, 0.43] | 0.57 | 0 | 0 |
| Baseline (filter on shaped score) | 0.39 | [0.33, 0.45] | 0.68 | 40 | 30.0 |
| Recipe (filter on binary outcome) | 0.46 | [0.39, 0.53] | 0.70 | 40 | 21.8 |
Recipe vs baseline: +0.067 [+0.021, +0.113] over 120 paired tasks. The interval excludes zero and the delta clears the eval's re-run band (0.025 from ten base re-runs). The shaped score went down while pass@1 went up, the opposite of over-optimization. Verdict: unresolved until a second training seed per arm.
The root holds the arm the recipe README's headline number reports. Every other arm is a subfolder named after it. checkpoints/ never ships.
| folder | arm |
|---|---|
. | recipe arm: filter on binary outcome, 2026-09-17 run |
baseline | baseline arm: filter on shaped score, 2026-09-17 run |
python
from peft import PeftModelfrom transformers import AutoModelForCausalLM base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct")model = PeftModel.from_pretrained(base, "while-ai/paper-filter-metric-1.5b") # the headline armmodel = PeftModel.from_pretrained(base, "while-ai/paper-filter-metric-1.5b", subfolder="baseline") # another armbash
git clone https://github.com/whilehq/whileai-sdk && cd whileai-sdk/recipes/papers/filter-metricpython recipe.pyThe recipe README pins the seed, the library versions and the GPU, and its Checks table says what the eval verified. Read the Learned section before quoting a number from this card.
from peft import PeftModelfrom transformers import AutoModelForCausalLM base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct")model = PeftModel.from_pretrained(base, "while-ai/paper-filter-metric-1.5b") # the headline armmodel = PeftModel.from_pretrained(base, "while-ai/paper-filter-metric-1.5b", subfolder="baseline") # another arm