huggingface / huggingface/sentence-transformers
Fine-tuning to get updated sentence embeddings
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- Dominant language
- Python
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Description
I have a corpus of text that I would like to fine-tune a model on. The goal is to get better embeddings based on the specific text corpus I have. I don't have any kind of labels for the corpus, they're just sentences. Is there any easy loss function or way to do this?
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files, tests, or entry points are identified. Start by clarifying the intended training objective for the unlabeled sentence corpus and the expected embedding improvement; a concrete implementation target and validation criteria are needed before work can be considered complete.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100