Parameter	Value
Base Model	Qwen/Qwen3-8B
LoRA Rank	64
LoRA Alpha	128
Learning Rate	1.72e-04
Epochs	4
Validation Loss	0.1947
Training Samples	35,976
Dataset	GLM-4.7-flash SFT traces (successful traces only)
Context Length	16,384 tokens
Quantization	4-bit (QLoRA)

Evaluation Results

Benchmark	Score
SimpleQA (200)	11.0% accuracy
GAIA (165)	9.1% accuracy
HLE (200)	6.0% accuracy
DeepResearch (100)	0.2206 score

Usage

python

from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer

model = AutoPeftModelForCausalLM.from_pretrained(
    "akenginorhun/qwen3-8b-orchestrator-lora-successful-only",
    device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained(
    "akenginorhun/qwen3-8b-orchestrator-lora-successful-only"
)

W&B Sweep

Sweep ID: 4j1os87c
Project: hazy-research/limit-successful
Method: Bayesian optimization (12 runs)