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المنصة
الرئيسية
SOTA
الاستدلال بالحدس
Common Sense Reasoning On Winogrande
Common Sense Reasoning On Winogrande
المقاييس
Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
Accuracy
Paper Title
ST-MoE-32B 269B (fine-tuned)
96.1
ST-MoE: Designing Stable and Transferable Sparse Expert Models
Unicorn 11B (fine-tuned)
91.3
UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark
CompassMTL 567M with Tailor
90.5
Task Compass: Scaling Multi-task Pre-training with Task Prefix
CompassMTL 567M
89.6
Task Compass: Scaling Multi-task Pre-training with Task Prefix
UnifiedQA 11B (fine-tuned)
89.4
UnifiedQA: Crossing Format Boundaries With a Single QA System
Claude 3 Opus (5-shot)
88.5
The Claude 3 Model Family: Opus, Sonnet, Haiku
GPT-4 (5-shot)
87.5
GPT-4 Technical Report
ExDeBERTa 567M
87
Task Compass: Scaling Multi-task Pre-training with Task Prefix
LLaMA-2 13B + MixLoRA
86.3
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
LLaMA3 8B+MoSLoRA
85.8
Mixture-of-Subspaces in Low-Rank Adaptation
PaLM 2-L (1-shot)
83.0
PaLM 2 Technical Report
LLaMA-3 8B + MixLoRA
82.1
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
ST-MoE-L 4.1B (fine-tuned)
81.7
ST-MoE: Designing Stable and Transferable Sparse Expert Models
GPT-3.5 (5-shot)
81.6
GPT-4 Technical Report
PaLM 540B (0-shot)
81.1
PaLM: Scaling Language Modeling with Pathways
Camelidae-8×34B
80.9
Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks
PaLM 2-M (1-shot)
79.2
PaLM 2 Technical Report
RoBERTa-Winogrande 355M (fine-tuned)
79.1
WinoGrande: An Adversarial Winograd Schema Challenge at Scale
PaLM 2-S (1-shot)
77.9
PaLM 2 Technical Report
Mixtral 8x7B (0-shot)
77.2
Mixtral of Experts
0 of 77 row(s) selected.
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