HyperAIHyperAI
StartseiteNeuigkeitenNeueste ForschungsarbeitenTutorialsDatensätzeWikiSOTALLM-ModelleGPU-RanglisteVeranstaltungen
Suche
Über
HyperAIHyperAI

Natural Language Inference On Scitail

Metriken

Dev Accuracy

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname
Dev Accuracy
Paper TitleRepository
MT-DNN-SMART_1%ofTrainingData88.6SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
Finetuned Transformer LM-Improving Language Understanding by Generative Pre-Training
RE2-Simple and Effective Text Matching with Richer Alignment Features
MT-DNN-SMARTLARGEv0-SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
SplitEE-S-SplitEE: Early Exit in Deep Neural Networks with Split Computing
CA-MTL-Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data
Hierarchical BiLSTM Max Pooling-Sentence Embeddings in NLI with Iterative Refinement Encoders
MT-DNN-Multi-Task Deep Neural Networks for Natural Language Understanding
MT-DNN-SMART_0.1%ofTrainingData82.3SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
MT-DNN-SMART_100%ofTrainingData96.1SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
CAFE-Compare, Compress and Propagate: Enhancing Neural Architectures with Alignment Factorization for Natural Language Inference-
MT-DNN-SMART_10%ofTrainingData91.3SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
Finetuned Transformer LM---
0 of 13 row(s) selected.
Natural Language Inference On Scitail | SOTA | HyperAI