Hallucination robustness on TruthfulQA
48.76TruthfulQA AccuracyQwen3-1.7B
Evaluation Results
| Method | Links | |
|---|---|---|
| Qwen3-1.7BType=Base Model2026.05 | 48.76 | |
| FoLoRAFine-tuning dataset=MetaMathQA, Calibration data=NQ Open, Calibration model size=4B2026.05 | 48.46 | |
| LoRA-NullFine-tuning dataset=MetaMathQA, Calibration data=model-generated pretraining-proxy2026.05 | 48.4 | |
| FoLoRAFine-tuning dataset=MetaMathQA, Calibration data=NQ Open, Calibration model size=1.7B2026.05 | 48.36 | |
| CorDAFine-tuning dataset=MetaMathQA, Calibration data=model-generated pretraining-proxy, Calibration model size=4B2026.05 | 48.35 | |
| FoLoRAFine-tuning dataset=MetaMathQA, Calibration data=NQ Open2026.05 | 48.32 | |
| CorDAFine-tuning dataset=MetaMathQA, Calibration data=model-generated pretraining-proxy2026.05 | 48.3 | |
| FoLoRAFine-tuning dataset=MetaMathQA, Calibration data=NQ Open, Calibration model size=0.6B2026.05 | 48.22 | |
| LoRA-NullFine-tuning dataset=MetaMathQA, Calibration data=model-generated pretraining-proxy, Calibration model size=4B2026.05 | 48.16 | |
| MiLoRAFine-tuning dataset=MetaMathQA2026.05 | 48.06 | |
| OPLoRAFine-tuning dataset=MetaMathQA2026.05 | 48.06 | |
| LoRAFine-tuning dataset=MetaMathQA2026.05 | 47.93 |