KaiserML
/

RhetoriBERT

Sentence Similarity

sentence-transformers

feature-extraction

Generated from Trainer

dataset_size:35934

loss:MatryoshkaLoss

loss:MultipleNegativesRankingLoss

text-embeddings-inference

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Corran commited on Jan 25

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@@ -144,7 +144,7 @@ model-index:
 # sentence-transformers/static-retrieval-mrl-en-v1
-This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [nomic-ai/nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5) on the [sci_gen_colbert_triplets](https://huggingface.co/datasets/Corran/SciGenColbertTriplets) dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
 ## Model Details

 # sentence-transformers/static-retrieval-mrl-en-v1
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [nomic-ai/nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5) on the [sci_gen_colbert_triplets](https://huggingface.co/datasets/Corran/SciGenColbertTriplets) dataset. It maps sentences from academic texts to a 768-dimensional dense vector space based on their rhetorical function (summarizing results, expressing limitations etc.) and can be used for functional textual similarity, limitations analysis, rhetorical function classification, clustering and more.
 ## Model Details