Update README.md

README.md

@@ -995,6 +995,38 @@ model-index:
       name: Spearman Max
 ---
 
+  /!\ This model achieves SOTA results in the MTEB STS multilingual Leaderboard (in "other"). Here is the comparison
+
+  	            State-of-the-art results (Multi)	STSb-XLM-RoBERTa-base	Paraphrase Multilingual MPNet base v2
+Average	                    73.17	                        71.68	                       **73.89**
+STS17 (ar-ar)	          **81.87**	                        80.43	                         81.24
+STS17 (en-ar)	          **81.22**	                        76.3	                         77.03
+STS17 (en-de)	            87.3	                        91.06	                       **91.09**
+STS17 (en-tr)	            77.18	                      **80.74**	                         79.87
+STS17 (es-en)	          **88.24**	                        83.09	                         85.53
+STS17 (es-es)	          **88.25**	                        84.16	                         87.27
+STS17 (fr-en)	            88.06	                      **91.33**	                         90.68
+STS17 (it-en)	            89.68	                      **92.87**	                         92.47
+STS17 (ko-ko)	            83.69	                      **97.67**	                         97.66
+STS17 (nl-en)	            88.25	                      **92.13**	                         91.15
+STS22 (ar)	                58.67	                        58.67	                       **62.66**
+STS22 (de)	              **60.12**	                        52.17	                         57.74
+STS22 (de-en)	          **60.92**	                        58.5	                         57.5
+STS22 (de-fr)	          **67.79**	                        51.28	                         57.99
+STS22 (de-pl)	          **58.69**	                        44.56	                         44.22
+STS22 (es)	              **68.57**	                        63.68	                         66.21
+STS22 (es-en)	          **78.8**	                        70.65	                         75.18
+STS22 (es-it)	          **75.04**	                        60.88	                         66.25
+STS22 (fr)	              **83.75**	                        76.46	                         78.76
+STS22 (fr-pl)	            84.52	                        84.52	                       **84.52**
+STS22 (it)	              **79.28**	                        66.73	                         68.47
+STS22 (pl)	                42.08	                        41.18	                       **43.36**
+STS22 (pl-en)	          **77.5**	                        64.35	                         75.11
+STS22 (ru)	              **61.71**	                        58.59	                         58.67
+STS22 (tr)	              **68.72**	                        57.52	                         63.84
+STS22 (zh-en)	          **71.88**	                        60.69	                         65.37
+STSb	                    89.86	                        95.05	                       **95.15**
+
 # SentenceTransformer based on sentence-transformers/paraphrase-multilingual-mpnet-base-v2
 
 This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2). 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.
@@ -1103,7 +1135,7 @@ You can finetune this model on your own dataset.
 | pearson_max         | 0.9551     |
 | spearman_max        | 0.9593     |
 
-#### Semantic Similarity
+#### Evalutation results vs SOTA results
 * Dataset: `sts-test`
 * Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
 
@@ -1120,499 +1152,6 @@ You can finetune this model on your own dataset.
 | pearson_max         | 0.948      |
 | spearman_max        | 0.9515     |
 
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.9725     |
-| **spearman_cosine** | **0.9766** |
-| pearson_manhattan   | 0.9382     |
-| spearman_manhattan  | 0.9487     |
-| pearson_euclidean   | 0.9392     |
-| spearman_euclidean  | 0.95       |
-| pearson_dot         | 0.8531     |
-| spearman_dot        | 0.8611     |
-| pearson_max         | 0.9725     |
-| spearman_max        | 0.9766     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.8027     |
-| **spearman_cosine** | **0.8124** |
-| pearson_manhattan   | 0.7839     |
-| spearman_manhattan  | 0.79       |
-| pearson_euclidean   | 0.7836     |
-| spearman_euclidean  | 0.792      |
-| pearson_dot         | 0.7699     |
-| spearman_dot        | 0.782      |
-| pearson_max         | 0.8027     |
-| spearman_max        | 0.8124     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.7796     |
-| **spearman_cosine** | **0.7703** |
-| pearson_manhattan   | 0.7904     |
-| spearman_manhattan  | 0.783      |
-| pearson_euclidean   | 0.7912     |
-| spearman_euclidean  | 0.7842     |
-| pearson_dot         | 0.7077     |
-| spearman_dot        | 0.6914     |
-| pearson_max         | 0.7912     |
-| spearman_max        | 0.7842     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.9113     |
-| **spearman_cosine** | **0.9109** |
-| pearson_manhattan   | 0.897      |
-| spearman_manhattan  | 0.8934     |
-| pearson_euclidean   | 0.8986     |
-| spearman_euclidean  | 0.8955     |
-| pearson_dot         | 0.8844     |
-| spearman_dot        | 0.8923     |
-| pearson_max         | 0.9113     |
-| spearman_max        | 0.9109     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.9362     |
-| **spearman_cosine** | **0.9379** |
-| pearson_manhattan   | 0.923      |
-| spearman_manhattan  | 0.9245     |
-| pearson_euclidean   | 0.9231     |
-| spearman_euclidean  | 0.9251     |
-| pearson_dot         | 0.907      |
-| spearman_dot        | 0.9186     |
-| pearson_max         | 0.9362     |
-| spearman_max        | 0.9379     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.8049     |
-| **spearman_cosine** | **0.7987** |
-| pearson_manhattan   | 0.8018     |
-| spearman_manhattan  | 0.7828     |
-| pearson_euclidean   | 0.8007     |
-| spearman_euclidean  | 0.7825     |
-| pearson_dot         | 0.7895     |
-| spearman_dot        | 0.7819     |
-| pearson_max         | 0.8049     |
-| spearman_max        | 0.7987     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.852      |
-| **spearman_cosine** | **0.8553** |
-| pearson_manhattan   | 0.8464     |
-| spearman_manhattan  | 0.841      |
-| pearson_euclidean   | 0.8468     |
-| spearman_euclidean  | 0.8459     |
-| pearson_dot         | 0.8093     |
-| spearman_dot        | 0.8154     |
-| pearson_max         | 0.852      |
-| spearman_max        | 0.8553     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.8752     |
-| **spearman_cosine** | **0.8727** |
-| pearson_manhattan   | 0.8745     |
-| spearman_manhattan  | 0.8661     |
-| pearson_euclidean   | 0.8748     |
-| spearman_euclidean  | 0.8668     |
-| pearson_dot         | 0.8603     |
-| spearman_dot        | 0.852      |
-| pearson_max         | 0.8752     |
-| spearman_max        | 0.8727     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.9082     |
-| **spearman_cosine** | **0.9068** |
-| pearson_manhattan   | 0.8908     |
-| spearman_manhattan  | 0.8852     |
-| pearson_euclidean   | 0.8908     |
-| spearman_euclidean  | 0.8851     |
-| pearson_dot         | 0.8889     |
-| spearman_dot        | 0.8966     |
-| pearson_max         | 0.9082     |
-| spearman_max        | 0.9068     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.925      |
-| **spearman_cosine** | **0.9247** |
-| pearson_manhattan   | 0.9084     |
-| spearman_manhattan  | 0.9029     |
-| pearson_euclidean   | 0.9116     |
-| spearman_euclidean  | 0.9084     |
-| pearson_dot         | 0.9001     |
-| spearman_dot        | 0.907      |
-| pearson_max         | 0.925      |
-| spearman_max        | 0.9247     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.9133     |
-| **spearman_cosine** | **0.9115** |
-| pearson_manhattan   | 0.8977     |
-| spearman_manhattan  | 0.8933     |
-| pearson_euclidean   | 0.8979     |
-| spearman_euclidean  | 0.8937     |
-| pearson_dot         | 0.8912     |
-| spearman_dot        | 0.8988     |
-| pearson_max         | 0.9133     |
-| spearman_max        | 0.9115     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.8985     |
-| **spearman_cosine** | **0.8452** |
-| pearson_manhattan   | 0.8715     |
-| spearman_manhattan  | 0.8452     |
-| pearson_euclidean   | 0.8809     |
-| spearman_euclidean  | 0.8452     |
-| pearson_dot         | 0.8538     |
-| spearman_dot        | 0.8452     |
-| pearson_max         | 0.8985     |
-| spearman_max        | 0.8452     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.6495     |
-| **spearman_cosine** | **0.6385** |
-| pearson_manhattan   | 0.6429     |
-| spearman_manhattan  | 0.6474     |
-| pearson_euclidean   | 0.6443     |
-| spearman_euclidean  | 0.6445     |
-| pearson_dot         | 0.6128     |
-| spearman_dot        | 0.6108     |
-| pearson_max         | 0.6495     |
-| spearman_max        | 0.6474     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.7441     |
-| **spearman_cosine** | **0.7518** |
-| pearson_manhattan   | 0.7339     |
-| spearman_manhattan  | 0.7367     |
-| pearson_euclidean   | 0.7337     |
-| spearman_euclidean  | 0.7342     |
-| pearson_dot         | 0.6886     |
-| spearman_dot        | 0.6986     |
-| pearson_max         | 0.7441     |
-| spearman_max        | 0.7518     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.6279     |
-| **spearman_cosine** | **0.6319** |
-| pearson_manhattan   | 0.5435     |
-| spearman_manhattan  | 0.6002     |
-| pearson_euclidean   | 0.54       |
-| spearman_euclidean  | 0.5955     |
-| pearson_dot         | 0.5658     |
-| spearman_dot        | 0.6069     |
-| pearson_max         | 0.6279     |
-| spearman_max        | 0.6319     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.7779     |
-| **spearman_cosine** | **0.7876** |
-| pearson_manhattan   | 0.7426     |
-| spearman_manhattan  | 0.7789     |
-| pearson_euclidean   | 0.7437     |
-| spearman_euclidean  | 0.7806     |
-| pearson_dot         | 0.7214     |
-| spearman_dot        | 0.7489     |
-| pearson_max         | 0.7779     |
-| spearman_max        | 0.7876     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.5268     |
-| **spearman_cosine** | **0.5774** |
-| pearson_manhattan   | 0.4171     |
-| spearman_manhattan  | 0.56       |
-| pearson_euclidean   | 0.4219     |
-| spearman_euclidean  | 0.5665     |
-| pearson_dot         | 0.4981     |
-| spearman_dot        | 0.5367     |
-| pearson_max         | 0.5268     |
-| spearman_max        | 0.5774     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.6306     |
-| **spearman_cosine** | **0.6384** |
-| pearson_manhattan   | 0.6034     |
-| spearman_manhattan  | 0.6168     |
-| pearson_euclidean   | 0.6081     |
-| spearman_euclidean  | 0.622      |
-| pearson_dot         | 0.5767     |
-| spearman_dot        | 0.5831     |
-| pearson_max         | 0.6306     |
-| spearman_max        | 0.6384     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.5568     |
-| **spearman_cosine** | **0.5867** |
-| pearson_manhattan   | 0.4924     |
-| spearman_manhattan  | 0.5738     |
-| pearson_euclidean   | 0.4906     |
-| spearman_euclidean  | 0.5762     |
-| pearson_dot         | 0.4307     |
-| spearman_dot        | 0.5471     |
-| pearson_max         | 0.5568     |
-| spearman_max        | 0.5867     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value     |
-|:--------------------|:----------|
-| pearson_cosine      | 0.5776    |
-| **spearman_cosine** | **0.575** |
-| pearson_manhattan   | 0.5718    |
-| spearman_manhattan  | 0.5501    |
-| pearson_euclidean   | 0.5695    |
-| spearman_euclidean  | 0.5532    |
-| pearson_dot         | 0.5315    |
-| spearman_dot        | 0.5191    |
-| pearson_max         | 0.5776    |
-| spearman_max        | 0.575     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.3572     |
-| **spearman_cosine** | **0.4336** |
-| pearson_manhattan   | 0.2081     |
-| spearman_manhattan  | 0.4355     |
-| pearson_euclidean   | 0.2086     |
-| spearman_euclidean  | 0.4402     |
-| pearson_dot         | 0.2234     |
-| spearman_dot        | 0.3707     |
-| pearson_max         | 0.3572     |
-| spearman_max        | 0.4402     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.6863     |
-| **spearman_cosine** | **0.6621** |
-| pearson_manhattan   | 0.6429     |
-| spearman_manhattan  | 0.6484     |
-| pearson_euclidean   | 0.6424     |
-| spearman_euclidean  | 0.6486     |
-| pearson_dot         | 0.6352     |
-| spearman_dot        | 0.6159     |
-| pearson_max         | 0.6863     |
-| spearman_max        | 0.6621     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.757      |
-| **spearman_cosine** | **0.7511** |
-| pearson_manhattan   | 0.7191     |
-| spearman_manhattan  | 0.714      |
-| pearson_euclidean   | 0.7204     |
-| spearman_euclidean  | 0.7258     |
-| pearson_dot         | 0.7144     |
-| spearman_dot        | 0.7284     |
-| pearson_max         | 0.757      |
-| spearman_max        | 0.7511     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.6503     |
-| **spearman_cosine** | **0.6625** |
-| pearson_manhattan   | 0.6474     |
-| spearman_manhattan  | 0.659      |
-| pearson_euclidean   | 0.6517     |
-| spearman_euclidean  | 0.6667     |
-| pearson_dot         | 0.5647     |
-| spearman_dot        | 0.5702     |
-| pearson_max         | 0.6517     |
-| spearman_max        | 0.6667     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.6774     |
-| **spearman_cosine** | **0.6537** |
-| pearson_manhattan   | 0.6825     |
-| spearman_manhattan  | 0.6325     |
-| pearson_euclidean   | 0.6906     |
-| spearman_euclidean  | 0.6407     |
-| pearson_dot         | 0.5835     |
-| spearman_dot        | 0.5962     |
-| pearson_max         | 0.6906     |
-| spearman_max        | 0.6537     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.6709     |
-| **spearman_cosine** | **0.6847** |
-| pearson_manhattan   | 0.6613     |
-| spearman_manhattan  | 0.6907     |
-| pearson_euclidean   | 0.6607     |
-| spearman_euclidean  | 0.6881     |
-| pearson_dot         | 0.6098     |
-| spearman_dot        | 0.6195     |
-| pearson_max         | 0.6709     |
-| spearman_max        | 0.6907     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.5977     |
-| **spearman_cosine** | **0.5799** |
-| pearson_manhattan   | 0.5974     |
-| spearman_manhattan  | 0.5953     |
-| pearson_euclidean   | 0.5949     |
-| spearman_euclidean  | 0.5936     |
-| pearson_dot         | 0.5043     |
-| spearman_dot        | 0.4968     |
-| pearson_max         | 0.5977     |
-| spearman_max        | 0.5953     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.4562     |
-| **spearman_cosine** | **0.4422** |
-| pearson_manhattan   | 0.4155     |
-| spearman_manhattan  | 0.3837     |
-| pearson_euclidean   | 0.4111     |
-| spearman_euclidean  | 0.3822     |
-| pearson_dot         | 0.4863     |
-| spearman_dot        | 0.5303     |
-| pearson_max         | 0.4863     |
-| spearman_max        | 0.5303     |
-
-#### Semantic Similarity
-* Dataset: `sts-test`
-* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
-
-| Metric              | Value      |
-|:--------------------|:-----------|
-| pearson_cosine      | 0.593      |
-| **spearman_cosine** | **0.6266** |
-| pearson_manhattan   | 0.5608     |
-| spearman_manhattan  | 0.6229     |
-| pearson_euclidean   | 0.558      |
-| spearman_euclidean  | 0.6202     |
-| pearson_dot         | 0.4578     |
-| spearman_dot        | 0.5628     |
-| pearson_max         | 0.593      |
-| spearman_max        | 0.6266     |
-
 <!--
 ## Bias, Risks and Limitations