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Explore CrossEncoders #74

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thefirebanks opened this issue Apr 11, 2021 · 2 comments

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exploration good first issue

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thefirebanks commented Apr 11, 2021

As specified in this issue: UKPLab/sentence-transformers#350 (comment)

The authors of SBERT recommend using CrossEncoders for sentence classification.

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thefirebanks added exploration good first issue labels

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thefirebanks commented Apr 11, 2021

Explore CrossEncoders

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SBERT for classification #51

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thefirebanks commented Apr 28, 2021

Relevant links:

CrossEncoder folders: https://github.com/UKPLab/sentence-transformers/tree/master/sentence_transformers/cross_encoder
CrossEncoder usage: https://github.com/UKPLab/sentence-transformers/blob/master/examples/applications/cross-encoder/cross-encoder_usage.py
Main threads explaining how/why use CrossEncoders for our example:
- https://www.sbert.net/examples/applications/cross-encoder/README.html
- Fine Tuning Models UKPLab/sentence-transformers#350
Pretrained CrossEncoders: https://www.sbert.net/docs/pretrained_cross-encoders.html
CrossEncoders and fine-tuning?: Using cross-encoders: fine-tuning required? UKPLab/sentence-transformers#615
Retrieve and rerank pipeline: https://www.sbert.net/examples/applications/retrieve_rerank/README.html
Advantages of SBERT over BERT:
- Questions about the inference process UKPLab/sentence-transformers#354
- Why are just the embeddings used for inference and not the finetuned model itself? UKPLab/sentence-transformers#540
Augmented SBERT:
- Paper: https://arxiv.org/pdf/2010.08240.pdf
- Clarifications on steps: Augmented SBERT training UKPLab/sentence-transformers#553
Optional: Batch hard triplet loss: https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/other/training_batch_hard_trec.py

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