Knowledge on MMB
61.98AccuracyTAIA
Evaluation Results
| Method | Links | |
|---|---|---|
| TAIAModel=Qwen1.5-32B, Infer Mode=TAIA2024.05 | 61.98 | |
| BaseModel=Qwen1.5-32B, Infer Mode=Base2024.05 | 61.04 | |
| LoRAModel=Qwen1.5-32B, Infer Mode=LoRA2024.05 | 59.54 | |
| TAIAModel=Qwen1.5-14B, Infer Mode=TAIA2024.05 | 52.55 | |
| BaseModel=Qwen1.5-14B, Infer Mode=Base2024.05 | 51.06 | |
| LoRAModel=Qwen1.5-14B, Infer Mode=LoRA2024.05 | 48.15 | |
| TAIAModel=Qwen1.5-7B, Infer Mode=TAIA2024.05 | 46.9 | |
| BaseModel=Qwen1.5-7B, Infer Mode=Base2024.05 | 45.09 | |
| LoRAModel=Qwen1.5-7B, Infer Mode=LoRA2024.05 | 44.85 | |
| LoRACLTraining Dataset=Alpaca-GPT4, Infer Mode=LORACL2024.05 | 35.27 | |
| L2Training Dataset=Alpaca-GPT4, Infer Mode=L22024.05 | 35.04 | |
| Self-DistillTraining Dataset=Alpaca-GPT4, Infer Mode=Self-Distill2024.05 | 35.04 | |
| EWCTraining Dataset=Alpaca-GPT4, Infer Mode=EWC2024.05 | 34.88 | |
| VanillaTraining Dataset=Alpaca-GPT4, Infer Mode=Vanilla2024.05 | 34.8 | |
| TAIATraining Dataset=Alpaca-GPT4, Infer Mode=TAIA2024.05 | 34.64 | |
| TAIATraining Dataset=CoT-Collection, Infer Mode=TAIA2024.05 | 34.64 | |
| VanillaTraining Dataset=Base Model, Infer Mode=Vanilla2024.05 | 33.78 | |
| L2Training Dataset=CoT-Collection, Infer Mode=L22024.05 | 27.73 | |
| EWCTraining Dataset=CoT-Collection, Infer Mode=EWC2024.05 | 27.73 | |
| VanillaTraining Dataset=CoT-Collection, Infer Mode=Vanilla2024.05 | 27.65 | |
| LoRACLTraining Dataset=CoT-Collection, Infer Mode=LORACL2024.05 | 27.65 |