bespin-global
/

klue-sroberta-base-continue-learning-by-mnr

Sentence Similarity

sentence-transformers

feature-extraction

Inference Endpoints

text-embeddings-inference

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Copycats commited on Apr 4, 2022

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@@ -76,13 +76,15 @@ print(sentence_embeddings)
 <!--- Describe how your model was evaluated -->
-For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name={MODEL_NAME})
 **EmbeddingSimilarityEvaluator: Evaluating the model on sts-test dataset:**
-- Cosine-Similarity :	Pearson: 0.8901	Spearman: 0.8893
-- Manhattan-Distance:	Pearson: 0.8867	Spearman: 0.8818
-- Euclidean-Distance:	Pearson: 0.8875	Spearman: 0.8827
-- Dot-Product-Similarity:	Pearson: 0.8786	Spearman: 0.8735
 - Average : 0.8892573547643868

 <!--- Describe how your model was evaluated -->
 **EmbeddingSimilarityEvaluator: Evaluating the model on sts-test dataset:**
+- Cosine-Similarity :
+	- Pearson: 0.8901	Spearman: 0.8893
+- Manhattan-Distance:
+	- Pearson: 0.8867	Spearman: 0.8818
+- Euclidean-Distance:
+	- Pearson: 0.8875	Spearman: 0.8827
+- Dot-Product-Similarity:
+	- Pearson: 0.8786	Spearman: 0.8735
 - Average : 0.8892573547643868