tomaarsen
/

mpnet-base-gooaq

Sentence Similarity

sentence-transformers

feature-extraction

dataset_size:1M<n<10M

loss:MultipleNegativesRankingLoss

Inference Endpoints

Model card Files Files and versions Community

tomaarsen HF staff commited on Jun 20

Commit

67a5e14

•

1 Parent(s): 4ebdc6e

Update README.md

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -88,7 +88,7 @@ co2_eq_emissions:
   hours_used: 4.514
   hardware_used: 1 x NVIDIA GeForce RTX 3090
 model-index:
-- name: MPNet base trained on GooAQ triplets
   results:
   - task:
       type: information-retrieval
@@ -189,7 +189,7 @@ model-index:
       name: Dot Map@100
 ---
-# MPNet base trained on GooAQ triplets
 This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) on the [sentence-transformers/gooaq](https://huggingface.co/datasets/sentence-transformers/gooaq) 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.

   hours_used: 4.514
   hardware_used: 1 x NVIDIA GeForce RTX 3090
 model-index:
+- name: MPNet base trained on GooAQ Question-Answer tuples
   results:
   - task:
       type: information-retrieval
       name: Dot Map@100
 ---
+# MPNet base trained on GooAQ Question-Answer tuples
 This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) on the [sentence-transformers/gooaq](https://huggingface.co/datasets/sentence-transformers/gooaq) 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.