What are the steps to fine-tune a Sentence Transformer using a triplet loss or contrastive loss objective?
To fine-tune a Sentence Transformer using triplet or contrastive loss, follow these steps: prepare data in the required
Triplet Loss - Advanced Intro - Qdrant
What are the advantages of Triplet Loss over Contrastive loss and how to efficiently implement it?
Training Overview — Sentence Transformers documentation
AI-Growth-Lab/PatentSBERTa · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Training and Finetuning Embedding Models with Sentence Transformers v3
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
ModernBERT: The Next Generation of Encoder Models — A Guide to Using and Fine-Tuning for NLP Tasks
The release of BERT revolutionized natural language processing (NLP), setting a new standard for encoder-only transformer models. However…
Fine-tune ModernBERT for text classification using synthetic data
A Blog post by David Berenstein on Hugging Face
Fine-tune classifier with ModernBERT in 2025
Modern updated guide on how to fine-tune BERT models for classification tasks in 2025.