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while-ai/paper-endpoint-sft-1.5b

sourceHugging Faceapache-2.0updated 2d agoView on Hugging Face
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paper-endpoint-sft-1.5b

Recipe: [recipes/papers/endpoint-sft](https://github.com/whilehq/whileai-sdk/tree/main/recipes/papers/endpoint-sft) · Collection: [Papers, replicated](https://huggingface.co/collections/while-ai/papers-replicated-6ab271de22542eb550d4251c)

SFT on 600 R1 math traces, full trace against first-and-last 21 steps only. The cut drops 19.2% of trace tokens by the paper's 20% rule. Holdout is 64 MATH-500 problems, a different corpus, 4 samples each.

Result

Armpass@195% CIpass@kStepsGPU min
Base, no training0.46[0.36, 0.56]0.6900
Baseline (full trace)0.29[0.21, 0.37]0.537547.7
Recipe (endpoints only)0.28[0.20, 0.36]0.507521.7

Recipe vs baseline: -0.012 [-0.074, +0.047] over 64 paired problems. Verdict: unresolved. The number the paper's table does not have: both SFT arms land below the untrained base. One epoch of 600 traces teaches a 1.5B instruct model to write like R1 without teaching it to answer like R1. The proxy check reads over-optimized: trace shape moved +0.137 while pass@1 did not follow.

Arms in this repo

The root holds the arm the recipe README's headline number reports. Every other arm is a subfolder named after it. checkpoints/ never ships.

folderarm
.recipe arm: endpoints only (n = 21), 2026-09-17 run
baselinebaseline arm: full trace, 2026-09-17 run

Load

python
from peft import PeftModel
from transformers import AutoModelForCausalLM

base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct")
model = PeftModel.from_pretrained(base, "while-ai/paper-endpoint-sft-1.5b")  # the headline arm
model = PeftModel.from_pretrained(base, "while-ai/paper-endpoint-sft-1.5b", subfolder="baseline")  # another arm

Reproduce

bash
git clone https://github.com/whilehq/whileai-sdk && cd whileai-sdk/recipes/papers/endpoint-sft
python recipe.py

The 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.