# JSNLI Fine-tuning

A Japanese natural language inference model based on BERT architecture, trained on the JSNLI dataset, used to determine logical relationships (entailment/neutral/contradiction) between sentence pairs

A Japanese sentence embedding model fine-tuned using supervised SimCSE method, suitable for sentence similarity calculation and feature extraction tasks.

This is a Japanese sentence embedding model based on sentence-transformers, capable of mapping sentences and paragraphs into a 768-dimensional vector space, suitable for tasks like clustering and semantic search.

A text classification model fine-tuned on the JSNLI dataset based on the Japanese RoBERTa model, excelling in natural language inference tasks