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홈플랫폼문서뉴스연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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Question Answering On Multirc

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EM

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이 벤치마크에서 각 모델의 성능 결과

Paper TitleRepository
Hybrid H3 125M (3-shot, logit scoring)48.9Hungry Hungry Hippos: Towards Language Modeling with State Space Models
FLAN 137B (1-shot)-Finetuned Language Models Are Zero-Shot Learners
DeBERTa-1.5B63.7DeBERTa: Decoding-enhanced BERT with Disentangled Attention
BLOOM 176B (1-shot)-BloombergGPT: A Large Language Model for Finance
T5-XXL 11B (fine-tuned)-Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
GPT-NeoX 20B (1-shot)-BloombergGPT: A Large Language Model for Finance
T5-11B63.3Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
OPT 66B (1-shot)-BloombergGPT: A Large Language Model for Finance
KELM (finetuning BERT-large based single model)27.2KELM: Knowledge Enhanced Pre-Trained Language Representations with Message Passing on Hierarchical Relational Graphs
Hybrid H3 355M (0-shot, logit scoring)59.5Hungry Hungry Hippos: Towards Language Modeling with State Space Models
PaLM 2-S (one-shot)-PaLM 2 Technical Report
ST-MoE-L 4.1B (fine-tuned)-ST-MoE: Designing Stable and Transferable Sparse Expert Models
BERT-large(single model)24.1BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
GPT-3 175B (Few-Shot)-Language Models are Few-Shot Learners
Hybrid H3 355M (3-shot, logit scoring)59.7Hungry Hungry Hippos: Towards Language Modeling with State Space Models
PaLM 540B (finetuned) 69.2PaLM: Scaling Language Modeling with Pathways
Neo-6B (QA)-Ask Me Anything: A simple strategy for prompting language models
Hybrid H3 125M (0-shot, logit scoring)51.4Hungry Hungry Hippos: Towards Language Modeling with State Space Models
Turing NLR v5 XXL 5.4B (fine-tuned)63Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE-
Neo-6B (few-shot)-Ask Me Anything: A simple strategy for prompting language models
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