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SOTA
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Question Answering On Piqa
Question Answering On Piqa
평가 지표
Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Accuracy
Paper Title
Repository
Unicorn 11B (fine-tuned)
90.1
UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark
LLaMA3 8B+MoSLoRA
89.7
Mixture-of-Subspaces in Low-Rank Adaptation
CompassMTL 567M with Tailor
88.3
Task Compass: Scaling Multi-task Pre-training with Task Prefix
LLaMA-3 8B + MixLoRA
87.6
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
DeBERTa-Large 304M
87.4
Two is Better than Many? Binary Classification as an Effective Approach to Multi-Choice Question Answering
CompassMTL 567M
87.3
Task Compass: Scaling Multi-task Pre-training with Task Prefix
LLaMA-2 13B + MixLoRA
86.8
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
Shakti-LLM (2.5B)
86.2
SHAKTI: A 2.5 Billion Parameter Small Language Model Optimized for Edge AI and Low-Resource Environments
-
DeBERTa-Large 304M (classification-based)
85.9
Two is Better than Many? Binary Classification as an Effective Approach to Multi-Choice Question Answering
ExDeBERTa 567M
85.5
Task Compass: Scaling Multi-task Pre-training with Task Prefix
UnifiedQA 3B
85.3
UnifiedQA: Crossing Format Boundaries With a Single QA System
PaLM 2-L (1-shot)
85.0
PaLM 2 Technical Report
Mixtral 8x7B (0-shot)
83.6
Mixtral of Experts
PaLM 2-M (1-shot)
83.2
PaLM 2 Technical Report
LLaMA-2 7B + MixLoRA
83.2
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
Mistral 7B (0-shot)
83.0
Mistral 7B
LLaMA 65B (0-shot)
82.8
LLaMA: Open and Efficient Foundation Language Models
LLaMA 2 70B (0-shot)
82.8
Llama 2: Open Foundation and Fine-Tuned Chat Models
Camelidae-8×34B
82.7
Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks
LLaMA 33B (0-shot)
82.3
LLaMA: Open and Efficient Foundation Language Models
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