Cross Lingual Natural Language Inference On 3

Accuracy

评测结果

各个模型在此基准测试上的表现结果

模型名称	Accuracy	Paper Title
XLM-R R4F	84.2%	Better Fine-Tuning by Reducing Representational Collapse
BERT	70.5%	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
X-BiLSTM	67.7%	Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
X-CBOW	61.0%	Supervised Learning of Universal Sentence Representations from Natural Language Inference Data

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