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المنصة

Natural Language Inference On Rte

المقاييس

Accuracy

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

Paper Title
Vega v2 6B (KD-based prompt transfer)96%Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE
PaLM 540B (fine-tuned)95.7%PaLM: Scaling Language Modeling with Pathways
Turing NLR v5 XXL 5.4B (fine-tuned)94.1%Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE
ST-MoE-32B 269B (fine-tuned)93.5%ST-MoE: Designing Stable and Transferable Sparse Expert Models
DeBERTa-1.5B93.2%DeBERTa: Decoding-enhanced BERT with Disentangled Attention
MUPPET Roberta Large92.8%Muppet: Massive Multi-task Representations with Pre-Finetuning
DeBERTaV3large92.7%DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing
T5-XXL 11B92.5%SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
T5-XXL 11B (fine-tuned)92.5%Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
UL2 20B (fine-tuned)92.1%UL2: Unifying Language Learning Paradigms
ST-MoE-L 4.1B (fine-tuned)92.1%ST-MoE: Designing Stable and Transferable Sparse Expert Models
SMARTRoBERTa92.0%SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
FLAN 137B (prompt-tuned)91.7%Finetuned Language Models Are Zero-Shot Learners
T5-XL 3B91.1%Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
RoBERTa-large 355M + Entailment as Few-shot Learner90.5%Entailment as Few-Shot Learner
ALBERT89.2%ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Adv-RoBERTa ensemble88.7%StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding
RoBERTa88.2%RoBERTa: A Robustly Optimized BERT Pretraining Approach
RoBERTa (ensemble)88.2%RoBERTa: A Robustly Optimized BERT Pretraining Approach
T5-Large 738M87.4%LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions
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