🚀Hands-on Tutorial: Fine-tune a Cross-Encoder for Semantic Similarity
🔥 Why Fine-Tune a Cross-Encoder? 1. More Accurate Semantic Judgments: 2. Adapting to Domain-Specific Data Without fine-tuning, the model might miss these domain...
🔥 Why Fine-Tune a Cross-Encoder? 1. More Accurate Semantic Judgments: 2. Adapting to Domain-Specific Data Without fine-tuning, the model might miss these domain...
1. Introduction A common task in natural language processing (NLP) is text classification. Use cases of text classification include sentiment analysis, intent d...