Fine Tuning Jina Embedding V3 for classification task
Is there any blog post available for Fine Tuning Jina Embedding V3 for classification task. (only lora as well as full model)?
I could not find any, kindly guide.
Hey, I don't think we have a blogpost I can point you to that details fine-tuning jina-embeddings-v3, but it's relatively straightforward to do with ST. Just make sure to set the default_task to train a LoRA adapter, like 'classification'.
model = SentenceTransformer("jinaai/jina-embeddings-v3", trust_remote_code=True, model_kwargs={'default_task': 'classification'})
model = SentenceTransformer("jinaai/jina-embeddings-v3", trust_remote_code=True)
Or
model[0].default_task = 'classification'
You can also choose to fine-tune the main parameters (non-lora parameters) by setting https://huggingface.co/jinaai/jina-embeddings-v3/blob/main/config.json#L27 to True, and then not passing a default_task.
Hope this helps!
@mumeranwaar
You can also take a look at this blogpost: https://jina.ai/news/jina-classifier-for-high-performance-zero-shot-and-few-shot-classification/
Our zero-shot / few-shot classifier API might be just what you're looking for with your classification problem, though it does not detail how to finetune our v3 model.