diff --git "a/README.md" "b/README.md" new file mode 100644--- /dev/null +++ "b/README.md" @@ -0,0 +1,5961 @@ +--- +language: +- multilingual +- af +- am +- ar +- as +- az +- be +- bg +- bn +- br +- bs +- ca +- cs +- cy +- da +- de +- el +- en +- eo +- es +- et +- eu +- fa +- fi +- fr +- fy +- ga +- gd +- gl +- gu +- ha +- he +- hi +- hr +- hu +- hy +- id +- is +- it +- ja +- jv +- ka +- kk +- km +- kn +- ko +- ku +- ky +- la +- lo +- lt +- lv +- mg +- mk +- ml +- mn +- mr +- ms +- my +- ne +- nl +- 'no' +- om +- or +- pa +- pl +- ps +- pt +- ro +- ru +- sa +- sd +- si +- sk +- sl +- so +- sq +- sr +- su +- sv +- sw +- ta +- te +- th +- tl +- tr +- ug +- uk +- ur +- uz +- vi +- xh +- yi +- zh +license: mit +tags: +- mteb +- Sentence Transformers +- sentence-similarity +- sentence-transformers +- mlx +model-index: +- name: multilingual-e5-small + results: + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (en) + type: mteb/amazon_counterfactual + config: en + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 73.79104477611939 + - type: ap + value: 36.9996434842022 + - type: f1 + value: 67.95453679103099 + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (de) + type: mteb/amazon_counterfactual + config: de + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 71.64882226980728 + - type: ap + value: 82.11942130026586 + - type: f1 + value: 69.87963421606715 + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (en-ext) + type: mteb/amazon_counterfactual + config: en-ext + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 75.8095952023988 + - type: ap + value: 24.46869495579561 + - type: f1 + value: 63.00108480037597 + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (ja) + type: mteb/amazon_counterfactual + config: ja + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 64.186295503212 + - type: ap + value: 15.496804690197042 + - type: f1 + value: 52.07153895475031 + - task: + type: Classification + dataset: + name: MTEB AmazonPolarityClassification + type: mteb/amazon_polarity + config: default + split: test + revision: e2d317d38cd51312af73b3d32a06d1a08b442046 + metrics: + - type: accuracy + value: 88.699325 + - type: ap + value: 85.27039559917269 + - type: f1 + value: 88.65556295032513 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (en) + type: mteb/amazon_reviews_multi + config: en + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 44.69799999999999 + - type: f1 + value: 43.73187348654165 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (de) + type: mteb/amazon_reviews_multi + config: de + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 40.245999999999995 + - type: f1 + value: 39.3863530637684 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (es) + type: mteb/amazon_reviews_multi + config: es + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 40.394 + - type: f1 + value: 39.301223469483446 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (fr) + type: mteb/amazon_reviews_multi + config: fr + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 38.864 + - type: f1 + value: 37.97974261868003 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (ja) + type: mteb/amazon_reviews_multi + config: ja + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 37.682 + - type: f1 + value: 37.07399369768313 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (zh) + type: mteb/amazon_reviews_multi + config: zh + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 37.504 + - type: f1 + value: 36.62317273874278 + - task: + type: Retrieval + dataset: + name: MTEB ArguAna + type: arguana + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 19.061 + - type: map_at_10 + value: 31.703 + - type: map_at_100 + value: 32.967 + - type: map_at_1000 + value: 33.001000000000005 + - type: map_at_3 + value: 27.466 + - type: map_at_5 + value: 29.564 + - type: mrr_at_1 + value: 19.559 + - type: mrr_at_10 + value: 31.874999999999996 + - type: mrr_at_100 + value: 33.146 + - type: mrr_at_1000 + value: 33.18 + - type: mrr_at_3 + value: 27.667 + - type: mrr_at_5 + value: 29.74 + - type: ndcg_at_1 + value: 19.061 + - type: ndcg_at_10 + value: 39.062999999999995 + - type: ndcg_at_100 + value: 45.184000000000005 + - type: ndcg_at_1000 + value: 46.115 + - type: ndcg_at_3 + value: 30.203000000000003 + - type: ndcg_at_5 + value: 33.953 + - type: precision_at_1 + value: 19.061 + - type: precision_at_10 + value: 6.279999999999999 + - type: precision_at_100 + value: 0.9129999999999999 + - type: precision_at_1000 + value: 0.099 + - type: precision_at_3 + value: 12.706999999999999 + - type: precision_at_5 + value: 9.431000000000001 + - type: recall_at_1 + value: 19.061 + - type: recall_at_10 + value: 62.802 + - type: recall_at_100 + value: 91.323 + - type: recall_at_1000 + value: 98.72 + - type: recall_at_3 + value: 38.122 + - type: recall_at_5 + value: 47.155 + - task: + type: Clustering + dataset: + name: MTEB ArxivClusteringP2P + type: mteb/arxiv-clustering-p2p + config: default + split: test + revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d + metrics: + - type: v_measure + value: 39.22266660528253 + - task: + type: Clustering + dataset: + name: MTEB ArxivClusteringS2S + type: mteb/arxiv-clustering-s2s + config: default + split: test + revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 + metrics: + - type: v_measure + value: 30.79980849482483 + - task: + type: Reranking + dataset: + name: MTEB AskUbuntuDupQuestions + type: mteb/askubuntudupquestions-reranking + config: default + split: test + revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 + metrics: + - type: map + value: 57.8790068352054 + - type: mrr + value: 71.78791276436706 + - task: + type: STS + dataset: + name: MTEB BIOSSES + type: mteb/biosses-sts + config: default + split: test + revision: d3fb88f8f02e40887cd149695127462bbcf29b4a + metrics: + - type: cos_sim_pearson + value: 82.36328364043163 + - type: cos_sim_spearman + value: 82.26211536195868 + - type: euclidean_pearson + value: 80.3183865039173 + - type: euclidean_spearman + value: 79.88495276296132 + - type: manhattan_pearson + value: 80.14484480692127 + - type: manhattan_spearman + value: 80.39279565980743 + - task: + type: BitextMining + dataset: + name: MTEB BUCC (de-en) + type: mteb/bucc-bitext-mining + config: de-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 98.0375782881002 + - type: f1 + value: 97.86012526096033 + - type: precision + value: 97.77139874739039 + - type: recall + value: 98.0375782881002 + - task: + type: BitextMining + dataset: + name: MTEB BUCC (fr-en) + type: mteb/bucc-bitext-mining + config: fr-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 93.35241030156286 + - type: f1 + value: 92.66050333846944 + - type: precision + value: 92.3306919069631 + - type: recall + value: 93.35241030156286 + - task: + type: BitextMining + dataset: + name: MTEB BUCC (ru-en) + type: mteb/bucc-bitext-mining + config: ru-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 94.0699688257707 + - type: f1 + value: 93.50236693222492 + - type: precision + value: 93.22791825424315 + - type: recall + value: 94.0699688257707 + - task: + type: BitextMining + dataset: + name: MTEB BUCC (zh-en) + type: mteb/bucc-bitext-mining + config: zh-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 89.25750394944708 + - type: f1 + value: 88.79234684921889 + - type: precision + value: 88.57293312269616 + - type: recall + value: 89.25750394944708 + - task: + type: Classification + dataset: + name: MTEB Banking77Classification + type: mteb/banking77 + config: default + split: test + revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 + metrics: + - type: accuracy + value: 79.41558441558442 + - type: f1 + value: 79.25886487487219 + - task: + type: Clustering + dataset: + name: MTEB BiorxivClusteringP2P + type: mteb/biorxiv-clustering-p2p + config: default + split: test + revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 + metrics: + - type: v_measure + value: 35.747820820329736 + - task: + type: Clustering + dataset: + name: MTEB BiorxivClusteringS2S + type: mteb/biorxiv-clustering-s2s + config: default + split: test + revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 + metrics: + - type: v_measure + value: 27.045143830596146 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 24.252999999999997 + - type: map_at_10 + value: 31.655916666666666 + - type: map_at_100 + value: 32.680749999999996 + - type: map_at_1000 + value: 32.79483333333334 + - type: map_at_3 + value: 29.43691666666666 + - type: map_at_5 + value: 30.717416666666665 + - type: mrr_at_1 + value: 28.602750000000004 + - type: mrr_at_10 + value: 35.56875 + - type: mrr_at_100 + value: 36.3595 + - type: mrr_at_1000 + value: 36.427749999999996 + - type: mrr_at_3 + value: 33.586166666666664 + - type: mrr_at_5 + value: 34.73641666666666 + - type: ndcg_at_1 + value: 28.602750000000004 + - type: ndcg_at_10 + value: 36.06933333333334 + - type: ndcg_at_100 + value: 40.70141666666667 + - type: ndcg_at_1000 + value: 43.24341666666667 + - type: ndcg_at_3 + value: 32.307916666666664 + - type: ndcg_at_5 + value: 34.129999999999995 + - type: precision_at_1 + value: 28.602750000000004 + - type: precision_at_10 + value: 6.097666666666667 + - type: precision_at_100 + value: 0.9809166666666668 + - type: precision_at_1000 + value: 0.13766666666666663 + - type: precision_at_3 + value: 14.628166666666667 + - type: precision_at_5 + value: 10.266916666666667 + - type: recall_at_1 + value: 24.252999999999997 + - type: recall_at_10 + value: 45.31916666666667 + - type: recall_at_100 + value: 66.03575000000001 + - type: recall_at_1000 + value: 83.94708333333334 + - type: recall_at_3 + value: 34.71941666666666 + - type: recall_at_5 + value: 39.46358333333333 + - task: + type: Retrieval + dataset: + name: MTEB ClimateFEVER + type: climate-fever + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 9.024000000000001 + - type: map_at_10 + value: 15.644 + - type: map_at_100 + value: 17.154 + - type: map_at_1000 + value: 17.345 + - type: map_at_3 + value: 13.028 + - type: map_at_5 + value: 14.251 + - type: mrr_at_1 + value: 19.674 + - type: mrr_at_10 + value: 29.826999999999998 + - type: mrr_at_100 + value: 30.935000000000002 + - type: mrr_at_1000 + value: 30.987 + - type: mrr_at_3 + value: 26.645000000000003 + - type: mrr_at_5 + value: 28.29 + - type: ndcg_at_1 + value: 19.674 + - type: ndcg_at_10 + value: 22.545 + - type: ndcg_at_100 + value: 29.207 + - type: ndcg_at_1000 + value: 32.912 + - type: ndcg_at_3 + value: 17.952 + - type: ndcg_at_5 + value: 19.363 + - type: precision_at_1 + value: 19.674 + - type: precision_at_10 + value: 7.212000000000001 + - type: precision_at_100 + value: 1.435 + - type: precision_at_1000 + value: 0.212 + - type: precision_at_3 + value: 13.507 + - type: precision_at_5 + value: 10.397 + - type: recall_at_1 + value: 9.024000000000001 + - type: recall_at_10 + value: 28.077999999999996 + - type: recall_at_100 + value: 51.403 + - type: recall_at_1000 + value: 72.406 + - type: recall_at_3 + value: 16.768 + - type: recall_at_5 + value: 20.737 + - task: + type: Retrieval + dataset: + name: MTEB DBPedia + type: dbpedia-entity + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 8.012 + - type: map_at_10 + value: 17.138 + - type: map_at_100 + value: 24.146 + - type: map_at_1000 + value: 25.622 + - type: map_at_3 + value: 12.552 + - type: map_at_5 + value: 14.435 + - type: mrr_at_1 + value: 62.25000000000001 + - type: mrr_at_10 + value: 71.186 + - type: mrr_at_100 + value: 71.504 + - type: mrr_at_1000 + value: 71.514 + - type: mrr_at_3 + value: 69.333 + - type: mrr_at_5 + value: 70.408 + - type: ndcg_at_1 + value: 49.75 + - type: ndcg_at_10 + value: 37.76 + - type: ndcg_at_100 + value: 42.071 + - type: ndcg_at_1000 + value: 49.309 + - type: ndcg_at_3 + value: 41.644 + - type: ndcg_at_5 + value: 39.812999999999995 + - type: precision_at_1 + value: 62.25000000000001 + - type: precision_at_10 + value: 30.15 + - type: precision_at_100 + value: 9.753 + - type: precision_at_1000 + value: 1.9189999999999998 + - type: precision_at_3 + value: 45.667 + - type: precision_at_5 + value: 39.15 + - type: recall_at_1 + value: 8.012 + - type: recall_at_10 + value: 22.599 + - type: recall_at_100 + value: 48.068 + - type: recall_at_1000 + value: 71.328 + - type: recall_at_3 + value: 14.043 + - type: recall_at_5 + value: 17.124 + - task: + type: Classification + dataset: + name: MTEB EmotionClassification + type: mteb/emotion + config: default + split: test + revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 + metrics: + - type: accuracy + value: 42.455 + - type: f1 + value: 37.59462649781862 + - task: + type: Retrieval + dataset: + name: MTEB FEVER + type: fever + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 58.092 + - type: map_at_10 + value: 69.586 + - type: map_at_100 + value: 69.968 + - type: map_at_1000 + value: 69.982 + - type: map_at_3 + value: 67.48100000000001 + - type: map_at_5 + value: 68.915 + - type: mrr_at_1 + value: 62.166 + - type: mrr_at_10 + value: 73.588 + - type: mrr_at_100 + value: 73.86399999999999 + - type: mrr_at_1000 + value: 73.868 + - type: mrr_at_3 + value: 71.6 + - type: mrr_at_5 + value: 72.99 + - type: ndcg_at_1 + value: 62.166 + - type: ndcg_at_10 + value: 75.27199999999999 + - type: ndcg_at_100 + value: 76.816 + - type: ndcg_at_1000 + value: 77.09700000000001 + - type: ndcg_at_3 + value: 71.36 + - type: ndcg_at_5 + value: 73.785 + - type: precision_at_1 + value: 62.166 + - type: precision_at_10 + value: 9.716 + - type: precision_at_100 + value: 1.065 + - type: precision_at_1000 + value: 0.11 + - type: precision_at_3 + value: 28.278 + - type: precision_at_5 + value: 18.343999999999998 + - type: recall_at_1 + value: 58.092 + - type: recall_at_10 + value: 88.73400000000001 + - type: recall_at_100 + value: 95.195 + - type: recall_at_1000 + value: 97.04599999999999 + - type: recall_at_3 + value: 78.45 + - type: recall_at_5 + value: 84.316 + - task: + type: Retrieval + dataset: + name: MTEB FiQA2018 + type: fiqa + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 16.649 + - type: map_at_10 + value: 26.457000000000004 + - type: map_at_100 + value: 28.169 + - type: map_at_1000 + value: 28.352 + - type: map_at_3 + value: 23.305 + - type: map_at_5 + value: 25.169000000000004 + - type: mrr_at_1 + value: 32.407000000000004 + - type: mrr_at_10 + value: 40.922 + - type: mrr_at_100 + value: 41.931000000000004 + - type: mrr_at_1000 + value: 41.983 + - type: mrr_at_3 + value: 38.786 + - type: mrr_at_5 + value: 40.205999999999996 + - type: ndcg_at_1 + value: 32.407000000000004 + - type: ndcg_at_10 + value: 33.314 + - type: ndcg_at_100 + value: 40.312 + - type: ndcg_at_1000 + value: 43.685 + - type: ndcg_at_3 + value: 30.391000000000002 + - type: ndcg_at_5 + value: 31.525 + - type: precision_at_1 + value: 32.407000000000004 + - type: precision_at_10 + value: 8.966000000000001 + - type: precision_at_100 + value: 1.6019999999999999 + - type: precision_at_1000 + value: 0.22200000000000003 + - type: precision_at_3 + value: 20.165 + - type: precision_at_5 + value: 14.722 + - type: recall_at_1 + value: 16.649 + - type: recall_at_10 + value: 39.117000000000004 + - type: recall_at_100 + value: 65.726 + - type: recall_at_1000 + value: 85.784 + - type: recall_at_3 + value: 27.914 + - type: recall_at_5 + value: 33.289 + - task: + type: Retrieval + dataset: + name: MTEB HotpotQA + type: hotpotqa + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 36.253 + - type: map_at_10 + value: 56.16799999999999 + - type: map_at_100 + value: 57.06099999999999 + - type: map_at_1000 + value: 57.126 + - type: map_at_3 + value: 52.644999999999996 + - type: map_at_5 + value: 54.909 + - type: mrr_at_1 + value: 72.505 + - type: mrr_at_10 + value: 79.66 + - type: mrr_at_100 + value: 79.869 + - type: mrr_at_1000 + value: 79.88 + - type: mrr_at_3 + value: 78.411 + - type: mrr_at_5 + value: 79.19800000000001 + - type: ndcg_at_1 + value: 72.505 + - type: ndcg_at_10 + value: 65.094 + - type: ndcg_at_100 + value: 68.219 + - type: ndcg_at_1000 + value: 69.515 + - type: ndcg_at_3 + value: 59.99 + - type: ndcg_at_5 + value: 62.909000000000006 + - type: precision_at_1 + value: 72.505 + - type: precision_at_10 + value: 13.749 + - type: precision_at_100 + value: 1.619 + - type: precision_at_1000 + value: 0.179 + - type: precision_at_3 + value: 38.357 + - type: precision_at_5 + value: 25.313000000000002 + - type: recall_at_1 + value: 36.253 + - type: recall_at_10 + value: 68.744 + - type: recall_at_100 + value: 80.925 + - type: recall_at_1000 + value: 89.534 + - type: recall_at_3 + value: 57.535000000000004 + - type: recall_at_5 + value: 63.282000000000004 + - task: + type: Classification + dataset: + name: MTEB ImdbClassification + type: mteb/imdb + config: default + split: test + revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 + metrics: + - type: accuracy + value: 80.82239999999999 + - type: ap + value: 75.65895781725314 + - type: f1 + value: 80.75880969095746 + - task: + type: Retrieval + dataset: + name: MTEB MSMARCO + type: msmarco + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 21.624 + - type: map_at_10 + value: 34.075 + - type: map_at_100 + value: 35.229 + - type: map_at_1000 + value: 35.276999999999994 + - type: map_at_3 + value: 30.245 + - type: map_at_5 + value: 32.42 + - type: mrr_at_1 + value: 22.264 + - type: mrr_at_10 + value: 34.638000000000005 + - type: mrr_at_100 + value: 35.744 + - type: mrr_at_1000 + value: 35.787 + - type: mrr_at_3 + value: 30.891000000000002 + - type: mrr_at_5 + value: 33.042 + - type: ndcg_at_1 + value: 22.264 + - type: ndcg_at_10 + value: 40.991 + - type: ndcg_at_100 + value: 46.563 + - type: ndcg_at_1000 + value: 47.743 + - type: ndcg_at_3 + value: 33.198 + - type: ndcg_at_5 + value: 37.069 + - type: precision_at_1 + value: 22.264 + - type: precision_at_10 + value: 6.5089999999999995 + - type: precision_at_100 + value: 0.9299999999999999 + - type: precision_at_1000 + value: 0.10300000000000001 + - type: precision_at_3 + value: 14.216999999999999 + - type: precision_at_5 + value: 10.487 + - type: recall_at_1 + value: 21.624 + - type: recall_at_10 + value: 62.303 + - type: recall_at_100 + value: 88.124 + - type: recall_at_1000 + value: 97.08 + - type: recall_at_3 + value: 41.099999999999994 + - type: recall_at_5 + value: 50.381 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (en) + type: mteb/mtop_domain + config: en + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 91.06703146374831 + - type: f1 + value: 90.86867815863172 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (de) + type: mteb/mtop_domain + config: de + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 87.46970977740209 + - type: f1 + value: 86.36832872036588 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (es) + type: mteb/mtop_domain + config: es + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 89.26951300867245 + - type: f1 + value: 88.93561193959502 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (fr) + type: mteb/mtop_domain + config: fr + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 84.22799874725963 + - type: f1 + value: 84.30490069236556 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (hi) + type: mteb/mtop_domain + config: hi + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - 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task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (el) + type: mteb/amazon_massive_scenario + config: el + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 67.0712844653665 + - type: f1 + value: 66.75545422473901 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (en) + type: mteb/amazon_massive_scenario + config: en + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 74.4754539340955 + - type: f1 + value: 74.38427146553252 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (es) + type: mteb/amazon_massive_scenario + config: es + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 69.82515131136518 + - type: f1 + value: 69.63516462173847 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (fa) + type: mteb/amazon_massive_scenario + config: fa + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 68.70880968392737 + - type: f1 + value: 67.45420662567926 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (fi) + type: mteb/amazon_massive_scenario + config: fi + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 65.95494283792871 + - type: f1 + value: 65.06191009049222 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (fr) + type: mteb/amazon_massive_scenario + config: fr + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 68.75924680564896 + - type: f1 + value: 68.30833379585945 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (he) + type: mteb/amazon_massive_scenario + config: he + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 63.806321452589096 + - type: f1 + value: 63.273048243765054 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (hi) + type: mteb/amazon_massive_scenario + config: hi + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 67.68997982515133 + - type: f1 + value: 66.54703855381324 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (hu) + type: mteb/amazon_massive_scenario + config: hu + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 66.46940147948891 + - type: f1 + value: 65.91017343463396 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (hy) + type: mteb/amazon_massive_scenario + config: hy + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 59.49899125756556 + - type: f1 + value: 57.90333469917769 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (id) + type: mteb/amazon_massive_scenario + config: id + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - 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task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (jv) + type: mteb/amazon_massive_scenario + config: jv + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 56.63416274377943 + - type: f1 + value: 55.11332211687954 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ka) + type: mteb/amazon_massive_scenario + config: ka + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 52.23604572965702 + - type: f1 + value: 50.86529813991055 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (km) + type: mteb/amazon_massive_scenario + config: km + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 46.62407531943511 + - type: f1 + value: 43.63485467164535 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (kn) + type: mteb/amazon_massive_scenario + config: kn + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 59.15601882985878 + - type: f1 + value: 57.522837510959924 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ko) + type: mteb/amazon_massive_scenario + config: ko + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 69.84532616005382 + - type: f1 + value: 69.60021127179697 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (lv) + type: mteb/amazon_massive_scenario + config: lv + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 56.65770006724949 + - type: f1 + value: 55.84219135523227 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ml) + type: mteb/amazon_massive_scenario + config: ml + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 66.53665097511768 + - type: f1 + value: 65.09087787792639 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (mn) + type: mteb/amazon_massive_scenario + config: mn + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 59.31405514458642 + - type: f1 + value: 58.06135303831491 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ms) + type: mteb/amazon_massive_scenario + config: ms + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 64.88231338264964 + - type: f1 + value: 62.751099407787926 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (my) + type: mteb/amazon_massive_scenario + config: my + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 58.86012104909213 + - type: f1 + value: 56.29118323058282 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (nb) + type: mteb/amazon_massive_scenario + config: nb + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 67.37390719569602 + - type: f1 + value: 66.27922244885102 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (nl) + type: mteb/amazon_massive_scenario + config: nl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 70.8675184936113 + - type: f1 + value: 70.22146529932019 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (pl) + type: mteb/amazon_massive_scenario + config: pl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 68.2212508406187 + - type: f1 + value: 67.77454802056282 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (pt) + type: mteb/amazon_massive_scenario + config: pt + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 68.18090114324143 + - type: f1 + value: 68.03737625431621 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ro) + type: mteb/amazon_massive_scenario + config: ro + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 64.65030262273034 + - type: f1 + value: 63.792945486912856 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ru) + type: mteb/amazon_massive_scenario + config: ru + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 69.48217888365838 + - type: f1 + value: 69.96028997292197 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (sl) + type: mteb/amazon_massive_scenario + config: sl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 60.17821116341627 + - type: f1 + value: 59.3935969827171 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (sq) + type: mteb/amazon_massive_scenario + config: sq + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 62.86146603900471 + - type: f1 + value: 60.133692735032376 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (sv) + type: mteb/amazon_massive_scenario + config: sv + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 70.89441829186282 + - type: f1 + value: 70.03064076194089 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (sw) + type: mteb/amazon_massive_scenario + config: sw + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 58.15063887020847 + - type: f1 + value: 56.23326278499678 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ta) + type: mteb/amazon_massive_scenario + config: ta + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 59.43846671149966 + - type: f1 + value: 57.70440450281974 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (te) + type: mteb/amazon_massive_scenario + config: te + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 60.8507061197041 + - type: f1 + value: 59.22916396061171 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (th) + type: mteb/amazon_massive_scenario + config: th + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 70.65568258238063 + - type: f1 + value: 69.90736239440633 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (tl) + type: mteb/amazon_massive_scenario + config: tl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 60.8843308675185 + - type: f1 + value: 59.30332663713599 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (tr) + type: mteb/amazon_massive_scenario + config: tr + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 68.05312710154674 + - type: f1 + value: 67.44024062594775 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ur) + type: mteb/amazon_massive_scenario + config: ur + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 62.111634162743776 + - type: f1 + value: 60.89083013084519 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (vi) + type: mteb/amazon_massive_scenario + config: vi + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 67.44115669132482 + - type: f1 + value: 67.92227541674552 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (zh-CN) + type: mteb/amazon_massive_scenario + config: zh-CN + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 74.4687289845326 + - type: f1 + value: 74.16376793486025 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (zh-TW) + type: mteb/amazon_massive_scenario + config: zh-TW + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 68.31876260928043 + - type: f1 + value: 68.5246745215607 + - task: + type: Clustering + dataset: + name: MTEB MedrxivClusteringP2P + type: mteb/medrxiv-clustering-p2p + config: default + split: test + revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 + metrics: + - type: v_measure + value: 30.90431696479766 + - task: + type: Clustering + dataset: + name: MTEB MedrxivClusteringS2S + type: mteb/medrxiv-clustering-s2s + config: default + split: test + revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 + metrics: + - type: v_measure + value: 27.259158476693774 + - task: + type: Reranking + dataset: + name: MTEB MindSmallReranking + type: mteb/mind_small + config: default + split: test + revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 + metrics: + - type: map + value: 30.28445330838555 + - type: mrr + value: 31.15758529581164 + - task: + type: Retrieval + dataset: + name: MTEB NFCorpus + type: nfcorpus + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 5.353 + - type: map_at_10 + value: 11.565 + - type: map_at_100 + value: 14.097000000000001 + - type: map_at_1000 + value: 15.354999999999999 + - type: map_at_3 + value: 8.749 + - type: map_at_5 + value: 9.974 + - type: mrr_at_1 + value: 42.105 + - type: mrr_at_10 + value: 50.589 + - type: mrr_at_100 + value: 51.187000000000005 + - type: mrr_at_1000 + value: 51.233 + - type: mrr_at_3 + value: 48.246 + - type: mrr_at_5 + value: 49.546 + - type: ndcg_at_1 + value: 40.402 + - type: ndcg_at_10 + value: 31.009999999999998 + - type: ndcg_at_100 + value: 28.026 + - type: ndcg_at_1000 + value: 36.905 + - type: ndcg_at_3 + value: 35.983 + - type: ndcg_at_5 + value: 33.764 + - type: precision_at_1 + value: 42.105 + - type: precision_at_10 + value: 22.786 + - type: precision_at_100 + value: 6.916 + - type: precision_at_1000 + value: 1.981 + - type: precision_at_3 + value: 33.333 + - type: precision_at_5 + value: 28.731 + - type: recall_at_1 + value: 5.353 + - type: recall_at_10 + value: 15.039 + - type: recall_at_100 + value: 27.348 + - type: recall_at_1000 + value: 59.453 + - type: recall_at_3 + value: 9.792 + - type: recall_at_5 + value: 11.882 + - task: + type: Retrieval + dataset: + name: MTEB NQ + type: nq + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 33.852 + - type: map_at_10 + value: 48.924 + - type: map_at_100 + value: 49.854 + - type: map_at_1000 + value: 49.886 + - type: map_at_3 + value: 44.9 + - type: map_at_5 + value: 47.387 + - type: mrr_at_1 + value: 38.035999999999994 + - type: mrr_at_10 + value: 51.644 + - type: mrr_at_100 + value: 52.339 + - type: mrr_at_1000 + value: 52.35999999999999 + - type: mrr_at_3 + value: 48.421 + - type: mrr_at_5 + value: 50.468999999999994 + - type: ndcg_at_1 + value: 38.007000000000005 + - 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type: recall_at_5 + value: 90.501 + - task: + type: Clustering + dataset: + name: MTEB RedditClustering + type: mteb/reddit-clustering + config: default + split: test + revision: 24640382cdbf8abc73003fb0fa6d111a705499eb + metrics: + - type: v_measure + value: 39.13064340585255 + - task: + type: Clustering + dataset: + name: MTEB RedditClusteringP2P + type: mteb/reddit-clustering-p2p + config: default + split: test + revision: 282350215ef01743dc01b456c7f5241fa8937f16 + metrics: + - type: v_measure + value: 58.97884249325877 + - task: + type: Retrieval + dataset: + name: MTEB SCIDOCS + type: scidocs + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 3.4680000000000004 + - type: map_at_10 + value: 7.865 + - type: map_at_100 + value: 9.332 + - type: map_at_1000 + value: 9.587 + - type: map_at_3 + value: 5.800000000000001 + - type: map_at_5 + value: 6.8790000000000004 + - type: mrr_at_1 + value: 17.0 + - type: mrr_at_10 + value: 25.629 + - type: mrr_at_100 + value: 26.806 + - 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type: euclidean_pearson + value: 53.011731611314104 + - type: euclidean_spearman + value: 58.533194841668426 + - type: manhattan_pearson + value: 53.623067729338494 + - type: manhattan_spearman + value: 58.018756154446926 + - task: + type: STS + dataset: + name: MTEB STS22 (de-pl) + type: mteb/sts22-crosslingual-sts + config: de-pl + split: test + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + metrics: + - type: cos_sim_pearson + value: 13.611046866216112 + - type: cos_sim_spearman + value: 28.238192909158492 + - type: euclidean_pearson + value: 22.16189199885129 + - type: euclidean_spearman + value: 35.012895679076564 + - type: manhattan_pearson + value: 21.969771178698387 + - type: manhattan_spearman + value: 32.456985088607475 + - task: + type: STS + dataset: + name: MTEB STS22 (fr-pl) + type: mteb/sts22-crosslingual-sts + config: fr-pl + split: test + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + metrics: + - type: cos_sim_pearson + value: 74.58077407011655 + - type: cos_sim_spearman + value: 84.51542547285167 + - type: euclidean_pearson + value: 74.64613843596234 + - type: euclidean_spearman + value: 84.51542547285167 + - type: manhattan_pearson + value: 75.15335973101396 + - type: manhattan_spearman + value: 84.51542547285167 + - task: + type: STS + dataset: + name: MTEB STSBenchmark + type: mteb/stsbenchmark-sts + config: default + split: test + revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 + metrics: + - type: cos_sim_pearson + value: 82.0739825531578 + - type: cos_sim_spearman + value: 84.01057479311115 + - type: euclidean_pearson + value: 83.85453227433344 + - type: euclidean_spearman + value: 84.01630226898655 + - type: manhattan_pearson + value: 83.75323603028978 + - type: manhattan_spearman + value: 83.89677983727685 + - task: + type: Reranking + dataset: + name: MTEB SciDocsRR + type: mteb/scidocs-reranking + config: default + split: test + revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab + metrics: + - type: map + value: 78.12945623123957 + - type: mrr + value: 93.87738713719106 + - task: + type: Retrieval + dataset: + name: MTEB SciFact + type: scifact + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 52.983000000000004 + - type: map_at_10 + value: 62.946000000000005 + - type: map_at_100 + value: 63.514 + - type: map_at_1000 + value: 63.554 + - type: map_at_3 + value: 60.183 + - type: map_at_5 + value: 61.672000000000004 + - type: mrr_at_1 + value: 55.667 + - type: mrr_at_10 + value: 64.522 + - type: mrr_at_100 + value: 64.957 + - type: mrr_at_1000 + value: 64.995 + - type: mrr_at_3 + value: 62.388999999999996 + - type: mrr_at_5 + value: 63.639 + - type: ndcg_at_1 + value: 55.667 + - type: ndcg_at_10 + value: 67.704 + - type: ndcg_at_100 + value: 70.299 + - type: ndcg_at_1000 + value: 71.241 + - type: ndcg_at_3 + value: 62.866 + - type: ndcg_at_5 + value: 65.16999999999999 + - type: precision_at_1 + value: 55.667 + - type: precision_at_10 + value: 9.033 + - type: precision_at_100 + value: 1.053 + - type: precision_at_1000 + value: 0.11299999999999999 + - type: precision_at_3 + value: 24.444 + - type: precision_at_5 + value: 16.133 + - type: recall_at_1 + value: 52.983000000000004 + - type: recall_at_10 + value: 80.656 + - type: recall_at_100 + value: 92.5 + - type: recall_at_1000 + value: 99.667 + - type: recall_at_3 + value: 67.744 + - type: recall_at_5 + value: 73.433 + - task: + type: PairClassification + dataset: + name: MTEB SprintDuplicateQuestions + type: mteb/sprintduplicatequestions-pairclassification + config: default + split: test + revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 + metrics: + - type: cos_sim_accuracy + value: 99.72772277227723 + - type: cos_sim_ap + value: 92.17845897992215 + - type: cos_sim_f1 + value: 85.9746835443038 + - type: cos_sim_precision + value: 87.07692307692308 + - type: cos_sim_recall + value: 84.89999999999999 + - type: dot_accuracy + value: 99.3039603960396 + - type: dot_ap + value: 60.70244020124878 + - type: dot_f1 + value: 59.92742353551063 + - type: dot_precision + value: 62.21743810548978 + - type: dot_recall + value: 57.8 + - type: euclidean_accuracy + value: 99.71683168316832 + - type: euclidean_ap + value: 91.53997039964659 + - type: euclidean_f1 + value: 84.88372093023257 + - type: euclidean_precision + value: 90.02242152466367 + - type: euclidean_recall + value: 80.30000000000001 + - type: manhattan_accuracy + value: 99.72376237623763 + - type: manhattan_ap + value: 91.80756777790289 + - type: manhattan_f1 + value: 85.48468106479157 + - type: manhattan_precision + value: 85.8728557013118 + - type: manhattan_recall + value: 85.1 + - type: max_accuracy + value: 99.72772277227723 + - type: max_ap + value: 92.17845897992215 + - type: max_f1 + value: 85.9746835443038 + - task: + type: Clustering + dataset: + name: MTEB StackExchangeClustering + type: mteb/stackexchange-clustering + config: default + split: test + revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 + metrics: + - type: v_measure + value: 53.52464042600003 + - task: + type: Clustering + dataset: + name: MTEB StackExchangeClusteringP2P + type: mteb/stackexchange-clustering-p2p + config: default + split: test + revision: 815ca46b2622cec33ccafc3735d572c266efdb44 + metrics: + - type: v_measure + value: 32.071631948736 + - task: + type: Reranking + dataset: + name: MTEB StackOverflowDupQuestions + type: mteb/stackoverflowdupquestions-reranking + config: default + split: test + revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 + metrics: + - type: map + value: 49.19552407604654 + - type: mrr + value: 49.95269130379425 + - task: + type: Summarization + dataset: + name: MTEB SummEval + type: mteb/summeval + config: default + split: test + revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c + metrics: + - type: cos_sim_pearson + value: 29.345293033095427 + - type: cos_sim_spearman + value: 29.976931423258403 + - type: dot_pearson + value: 27.047078008958408 + - type: dot_spearman + value: 27.75894368380218 + - task: + type: Retrieval + dataset: + name: MTEB TRECCOVID + type: trec-covid + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 0.22 + - type: map_at_10 + value: 1.706 + - type: map_at_100 + value: 9.634 + - type: map_at_1000 + value: 23.665 + - type: map_at_3 + value: 0.5950000000000001 + - type: map_at_5 + value: 0.95 + - type: mrr_at_1 + value: 86.0 + - type: mrr_at_10 + value: 91.8 + - type: mrr_at_100 + value: 91.8 + - type: mrr_at_1000 + value: 91.8 + - type: mrr_at_3 + value: 91.0 + - type: mrr_at_5 + value: 91.8 + - type: ndcg_at_1 + value: 80.0 + - type: ndcg_at_10 + value: 72.573 + - type: ndcg_at_100 + value: 53.954 + - type: ndcg_at_1000 + value: 47.760999999999996 + - type: ndcg_at_3 + value: 76.173 + - type: ndcg_at_5 + value: 75.264 + - type: precision_at_1 + value: 86.0 + - type: precision_at_10 + value: 76.4 + - type: precision_at_100 + value: 55.50000000000001 + - type: precision_at_1000 + value: 21.802 + - type: precision_at_3 + value: 81.333 + - type: precision_at_5 + value: 80.4 + - type: recall_at_1 + value: 0.22 + - type: recall_at_10 + value: 1.925 + - type: recall_at_100 + value: 12.762 + - type: recall_at_1000 + value: 44.946000000000005 + - type: recall_at_3 + value: 0.634 + - type: recall_at_5 + value: 1.051 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (sqi-eng) + type: mteb/tatoeba-bitext-mining + config: sqi-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 91.0 + - type: f1 + value: 88.55666666666666 + - type: precision + value: 87.46166666666667 + - type: recall + value: 91.0 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (fry-eng) + type: mteb/tatoeba-bitext-mining + config: fry-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 57.22543352601156 + - type: f1 + value: 51.03220478943021 + - type: precision + value: 48.8150289017341 + - type: recall + value: 57.22543352601156 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (kur-eng) + type: mteb/tatoeba-bitext-mining + config: kur-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 46.58536585365854 + - type: f1 + value: 39.66870798578116 + - type: precision + value: 37.416085946573745 + - type: recall + value: 46.58536585365854 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (tur-eng) + type: mteb/tatoeba-bitext-mining + config: tur-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 89.7 + - type: f1 + value: 86.77999999999999 + - type: precision + value: 85.45333333333332 + - type: recall + value: 89.7 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (deu-eng) + type: mteb/tatoeba-bitext-mining + config: deu-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 97.39999999999999 + - type: f1 + value: 96.58333333333331 + - type: precision + value: 96.2 + - type: recall + value: 97.39999999999999 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (nld-eng) + type: mteb/tatoeba-bitext-mining + config: nld-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 92.4 + - type: f1 + value: 90.3 + - type: precision + value: 89.31666666666668 + - type: recall + value: 92.4 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ron-eng) + type: mteb/tatoeba-bitext-mining + config: ron-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 86.9 + - type: f1 + value: 83.67190476190476 + - type: precision + value: 82.23333333333332 + - type: recall + value: 86.9 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ang-eng) + type: mteb/tatoeba-bitext-mining + config: ang-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 50.0 + - type: f1 + value: 42.23229092632078 + - type: precision + value: 39.851634683724235 + - type: recall + value: 50.0 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ido-eng) + type: mteb/tatoeba-bitext-mining + config: ido-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 76.3 + - type: f1 + value: 70.86190476190477 + - type: precision + value: 68.68777777777777 + - type: recall + value: 76.3 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (jav-eng) + type: mteb/tatoeba-bitext-mining + config: jav-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 57.073170731707314 + - type: f1 + value: 50.658958927251604 + - type: precision + value: 48.26480836236933 + - type: recall + value: 57.073170731707314 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (isl-eng) + type: mteb/tatoeba-bitext-mining + config: isl-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 68.2 + - type: f1 + value: 62.156507936507936 + - type: precision + value: 59.84964285714286 + - type: recall + value: 68.2 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (slv-eng) + type: mteb/tatoeba-bitext-mining + config: slv-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - 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type: accuracy + value: 89.8 + - type: f1 + value: 86.79 + - type: precision + value: 85.375 + - type: recall + value: 89.8 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (lat-eng) + type: mteb/tatoeba-bitext-mining + config: lat-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 47.199999999999996 + - type: f1 + value: 39.95484348984349 + - type: precision + value: 37.561071428571424 + - type: recall + value: 47.199999999999996 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (bel-eng) + type: mteb/tatoeba-bitext-mining + config: bel-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 87.8 + - type: f1 + value: 84.68190476190475 + - type: precision + value: 83.275 + - type: recall + value: 87.8 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (pms-eng) + type: mteb/tatoeba-bitext-mining + config: pms-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - 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type: accuracy + value: 83.39999999999999 + - type: f1 + value: 79.96380952380952 + - type: precision + value: 78.48333333333333 + - type: recall + value: 83.39999999999999 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (tgl-eng) + type: mteb/tatoeba-bitext-mining + config: tgl-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 83.2 + - type: f1 + value: 79.26190476190476 + - type: precision + value: 77.58833333333334 + - type: recall + value: 83.2 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ast-eng) + type: mteb/tatoeba-bitext-mining + config: ast-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 75.59055118110236 + - type: f1 + value: 71.66854143232096 + - type: precision + value: 70.30183727034121 + - type: recall + value: 75.59055118110236 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (mkd-eng) + type: mteb/tatoeba-bitext-mining + config: mkd-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 65.5 + - type: f1 + value: 59.26095238095238 + - type: precision + value: 56.81909090909092 + - type: recall + value: 65.5 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (khm-eng) + type: mteb/tatoeba-bitext-mining + config: khm-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 55.26315789473685 + - type: f1 + value: 47.986523325858506 + - type: precision + value: 45.33950006595436 + - type: recall + value: 55.26315789473685 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ces-eng) + type: mteb/tatoeba-bitext-mining + config: ces-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 82.89999999999999 + - type: f1 + value: 78.835 + - type: precision + value: 77.04761904761905 + - type: recall + value: 82.89999999999999 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (tzl-eng) + type: mteb/tatoeba-bitext-mining + config: tzl-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 43.269230769230774 + - type: f1 + value: 36.20421245421245 + - type: precision + value: 33.57371794871795 + - type: recall + value: 43.269230769230774 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (urd-eng) + type: mteb/tatoeba-bitext-mining + config: urd-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 88.0 + - type: f1 + value: 84.70666666666666 + - type: precision + value: 83.23166666666665 + - type: recall + value: 88.0 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ara-eng) + type: mteb/tatoeba-bitext-mining + config: ara-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 77.4 + - type: f1 + value: 72.54666666666667 + - type: precision + value: 70.54318181818181 + - type: recall + value: 77.4 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (kor-eng) + type: mteb/tatoeba-bitext-mining + config: kor-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 78.60000000000001 + - type: f1 + value: 74.1588888888889 + - type: precision + value: 72.30250000000001 + - type: recall + value: 78.60000000000001 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (yid-eng) + type: mteb/tatoeba-bitext-mining + config: yid-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 72.40566037735849 + - type: f1 + value: 66.82587328813744 + - type: precision + value: 64.75039308176099 + - type: recall + value: 72.40566037735849 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (fin-eng) + type: mteb/tatoeba-bitext-mining + config: fin-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 73.8 + - type: f1 + value: 68.56357142857144 + - type: precision + value: 66.3178822055138 + - type: recall + value: 73.8 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (tha-eng) + type: mteb/tatoeba-bitext-mining + config: tha-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 91.78832116788321 + - type: f1 + value: 89.3552311435523 + - type: precision + value: 88.20559610705597 + - type: recall + value: 91.78832116788321 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (wuu-eng) + type: mteb/tatoeba-bitext-mining + config: wuu-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 74.3 + - type: f1 + value: 69.05085581085581 + - type: precision + value: 66.955 + - type: recall + value: 74.3 + - task: + type: Retrieval + dataset: + name: MTEB Touche2020 + type: webis-touche2020 + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 2.896 + - type: map_at_10 + value: 8.993 + - type: map_at_100 + value: 14.133999999999999 + - type: map_at_1000 + value: 15.668000000000001 + - type: map_at_3 + value: 5.862 + - type: map_at_5 + value: 7.17 + - type: mrr_at_1 + value: 34.694 + - type: mrr_at_10 + value: 42.931000000000004 + - type: mrr_at_100 + value: 44.81 + - type: mrr_at_1000 + value: 44.81 + - type: mrr_at_3 + value: 38.435 + - type: mrr_at_5 + value: 41.701 + - type: ndcg_at_1 + value: 31.633 + - type: ndcg_at_10 + value: 21.163 + - type: ndcg_at_100 + value: 33.306000000000004 + - type: ndcg_at_1000 + value: 45.275999999999996 + - type: ndcg_at_3 + value: 25.685999999999996 + - type: ndcg_at_5 + value: 23.732 + - type: precision_at_1 + value: 34.694 + - type: precision_at_10 + value: 17.755000000000003 + - type: precision_at_100 + value: 6.938999999999999 + - type: precision_at_1000 + value: 1.48 + - type: precision_at_3 + value: 25.85 + - type: precision_at_5 + value: 23.265 + - type: recall_at_1 + value: 2.896 + - type: recall_at_10 + value: 13.333999999999998 + - type: recall_at_100 + value: 43.517 + - type: recall_at_1000 + value: 79.836 + - type: recall_at_3 + value: 6.306000000000001 + - type: recall_at_5 + value: 8.825 + - task: + type: Classification + dataset: + name: MTEB ToxicConversationsClassification + type: mteb/toxic_conversations_50k + config: default + split: test + revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c + metrics: + - type: accuracy + value: 69.3874 + - type: ap + value: 13.829909072469423 + - type: f1 + value: 53.54534203543492 + - task: + type: Classification + dataset: + name: MTEB TweetSentimentExtractionClassification + type: mteb/tweet_sentiment_extraction + config: default + split: test + revision: d604517c81ca91fe16a244d1248fc021f9ecee7a + metrics: + - type: accuracy + value: 62.62026032823995 + - type: f1 + value: 62.85251350485221 + - task: + type: Clustering + dataset: + name: MTEB TwentyNewsgroupsClustering + type: mteb/twentynewsgroups-clustering + config: default + split: test + revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 + metrics: + - type: v_measure + value: 33.21527881409797 + - task: + type: PairClassification + dataset: + name: MTEB TwitterSemEval2015 + type: mteb/twittersemeval2015-pairclassification + config: default + split: test + revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 + metrics: + - type: cos_sim_accuracy + value: 84.97943613280086 + - type: cos_sim_ap + value: 70.75454316885921 + - type: cos_sim_f1 + value: 65.38274012676743 + - type: cos_sim_precision + value: 60.761214318078835 + - type: cos_sim_recall + value: 70.76517150395777 + - type: dot_accuracy + value: 79.0546581629612 + - type: dot_ap + value: 47.3197121792147 + - type: dot_f1 + value: 49.20106524633821 + - type: dot_precision + value: 42.45499808502489 + - type: dot_recall + value: 58.49604221635884 + - type: euclidean_accuracy + value: 85.08076533349228 + - type: euclidean_ap + value: 70.95016106374474 + - type: euclidean_f1 + value: 65.43987900176455 + - type: euclidean_precision + value: 62.64478764478765 + - type: euclidean_recall + value: 68.49604221635884 + - type: manhattan_accuracy + value: 84.93771234428085 + - type: manhattan_ap + value: 70.63668388755362 + - type: manhattan_f1 + value: 65.23895401262398 + - type: manhattan_precision + value: 56.946084218811485 + - type: manhattan_recall + value: 76.35883905013192 + - type: max_accuracy + value: 85.08076533349228 + - type: max_ap + value: 70.95016106374474 + - type: max_f1 + value: 65.43987900176455 + - task: + type: PairClassification + dataset: + name: MTEB TwitterURLCorpus + type: mteb/twitterurlcorpus-pairclassification + config: default + split: test + revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf + metrics: + - type: cos_sim_accuracy + value: 88.69096130709822 + - type: cos_sim_ap + value: 84.82526278228542 + - type: cos_sim_f1 + value: 77.65485060585536 + - type: cos_sim_precision + value: 75.94582658619167 + - type: cos_sim_recall + value: 79.44256236526024 + - type: dot_accuracy + value: 80.97954748321496 + - type: dot_ap + value: 64.81642914145866 + - type: dot_f1 + value: 60.631996987229975 + - type: dot_precision + value: 54.5897293631712 + - type: dot_recall + value: 68.17831844779796 + - type: euclidean_accuracy + value: 88.6987231730508 + - type: euclidean_ap + value: 84.80003825477253 + - type: euclidean_f1 + value: 77.67194179854496 + - type: euclidean_precision + value: 75.7128235122094 + - type: euclidean_recall + value: 79.73514012935017 + - type: manhattan_accuracy + value: 88.62692591298949 + - type: manhattan_ap + value: 84.80451408255276 + - type: manhattan_f1 + value: 77.69888949572183 + - type: manhattan_precision + value: 73.70311528631622 + - type: manhattan_recall + value: 82.15275639051433 + - type: max_accuracy + value: 88.6987231730508 + - type: max_ap + value: 84.82526278228542 + - type: max_f1 + value: 77.69888949572183 +--- + +# multilingual-e5-small-mlx +This model was converted to MLX format from [`intfloat/multilingual-e5-small`](). +Refer to the [original model card](https://huggingface.co/intfloat/multilingual-e5-small) for more details on the model. +## Use with mlx +```bash +pip install mlx +git clone https://github.com/ml-explore/mlx-examples.git +cd mlx-examples/llms/hf_llm +python generate.py --model mlx-community/multilingual-e5-small-mlx --prompt "My name is" +```