| --- |
| tags: |
| - mteb |
| model-index: |
| - name: multilingual-e5-small |
| results: |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (en) |
| 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: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (de) |
| 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: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (en-ext) |
| 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: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (ja) |
| 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: |
| type: mteb/amazon_polarity |
| name: MTEB AmazonPolarityClassification |
| 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: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (en) |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 44.69799999999999 |
| - type: f1 |
| value: 43.73187348654165 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (de) |
| config: de |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 40.245999999999995 |
| - type: f1 |
| value: 39.3863530637684 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (es) |
| config: es |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 40.394 |
| - type: f1 |
| value: 39.301223469483446 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (fr) |
| config: fr |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 38.864 |
| - type: f1 |
| value: 37.97974261868003 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (ja) |
| config: ja |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 37.682 |
| - type: f1 |
| value: 37.07399369768313 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (zh) |
| config: zh |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 37.504 |
| - type: f1 |
| value: 36.62317273874278 |
| - task: |
| type: Retrieval |
| dataset: |
| type: arguana |
| name: MTEB 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: |
| type: mteb/arxiv-clustering-p2p |
| name: MTEB ArxivClusteringP2P |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 39.22266660528253 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-s2s |
| name: MTEB ArxivClusteringS2S |
| config: default |
| split: test |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| metrics: |
| - type: v_measure |
| value: 30.79980849482483 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/askubuntudupquestions-reranking |
| name: MTEB AskUbuntuDupQuestions |
| config: default |
| split: test |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| metrics: |
| - type: map |
| value: 57.8790068352054 |
| - type: mrr |
| value: 71.78791276436706 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/biosses-sts |
| name: MTEB BIOSSES |
| 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: |
| type: mteb/bucc-bitext-mining |
| name: MTEB BUCC (de-en) |
| 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: |
| type: mteb/bucc-bitext-mining |
| name: MTEB BUCC (fr-en) |
| 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: |
| type: mteb/bucc-bitext-mining |
| name: MTEB BUCC (ru-en) |
| 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: |
| type: mteb/bucc-bitext-mining |
| name: MTEB BUCC (zh-en) |
| 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: |
| type: mteb/banking77 |
| name: MTEB Banking77Classification |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 79.41558441558442 |
| - type: f1 |
| value: 79.25886487487219 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-p2p |
| name: MTEB BiorxivClusteringP2P |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 35.747820820329736 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-s2s |
| name: MTEB BiorxivClusteringS2S |
| config: default |
| split: test |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| metrics: |
| - type: v_measure |
| value: 27.045143830596146 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackRetrieval |
| 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: |
| type: climate-fever |
| name: MTEB ClimateFEVER |
| 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: |
| type: dbpedia-entity |
| name: MTEB DBPedia |
| 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: |
| type: mteb/emotion |
| name: MTEB EmotionClassification |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 42.455 |
| - type: f1 |
| value: 37.59462649781862 |
| - task: |
| type: Retrieval |
| dataset: |
| type: fever |
| name: MTEB 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: |
| type: fiqa |
| name: MTEB FiQA2018 |
| 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: |
| type: hotpotqa |
| name: MTEB 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: |
| type: mteb/imdb |
| name: MTEB ImdbClassification |
| 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: |
| type: msmarco |
| name: MTEB 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: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (en) |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 91.06703146374831 |
| - type: f1 |
| value: 90.86867815863172 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (de) |
| config: de |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 87.46970977740209 |
| - type: f1 |
| value: 86.36832872036588 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (es) |
| config: es |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 89.26951300867245 |
| - type: f1 |
| value: 88.93561193959502 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (fr) |
| config: fr |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 84.22799874725963 |
| - type: f1 |
| value: 84.30490069236556 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (hi) |
| config: hi |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 86.02007888131948 |
| - type: f1 |
| value: 85.39376041027991 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (th) |
| config: th |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 85.34900542495481 |
| - type: f1 |
| value: 85.39859673336713 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (en) |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 71.078431372549 |
| - type: f1 |
| value: 53.45071102002276 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (de) |
| config: de |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 65.85798816568047 |
| - type: f1 |
| value: 46.53112748993529 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (es) |
| config: es |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 67.96864576384256 |
| - type: f1 |
| value: 45.966703022829506 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (fr) |
| config: fr |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 61.31537738803633 |
| - type: f1 |
| value: 45.52601712835461 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (hi) |
| config: hi |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
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| value: 66.29616349946218 |
| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (th) |
| config: th |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
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| - type: f1 |
| value: 49.463476319014276 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (af) |
| config: af |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
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| - type: f1 |
| value: 54.094921857502285 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (am) |
| config: am |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 51.960322797579025 |
| - type: f1 |
| value: 48.547371223370945 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (ar) |
| config: ar |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| - type: f1 |
| value: 50.47069202054312 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (az) |
| config: az |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (bn) |
| config: bn |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (cy) |
| config: cy |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (da) |
| config: da |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
| value: 59.36480066245562 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (de) |
| config: de |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (el) |
| config: el |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (en) |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (es) |
| config: es |
| split: test |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (fa) |
| config: fa |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (fi) |
| config: fi |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
| value: 58.0891846024637 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (fr) |
| config: fr |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| - type: f1 |
| value: 62.84830858877575 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (he) |
| config: he |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (hi) |
| config: hi |
| split: test |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (hu) |
| config: hu |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| - type: f1 |
| value: 57.07035922704846 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (hy) |
| config: hy |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| value: 57.404169468728995 |
| - type: f1 |
| value: 53.94259011839138 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (id) |
| config: id |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
| value: 61.337103431499365 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (is) |
| config: is |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| - type: f1 |
| value: 49.7610691598921 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (it) |
| config: it |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (ja) |
| config: ja |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
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| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (jv) |
| config: jv |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| value: 50.847343644922674 |
| - type: f1 |
| value: 47.8536963168393 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (ka) |
| config: ka |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
| value: 46.370078045805556 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (km) |
| config: km |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| value: 42.83120376597175 |
| - type: f1 |
| value: 39.68948521599982 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (kn) |
| config: kn |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
| value: 53.961876160401545 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (ko) |
| config: ko |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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| - type: f1 |
| value: 61.134223684676 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (lv) |
| config: lv |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| value: 54.98991257565569 |
| - type: f1 |
| value: 52.579862862826296 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (ml) |
| config: ml |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| value: 61.90316072629456 |
| - type: f1 |
| value: 58.203024538290336 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (mn) |
| config: mn |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| value: 57.09818426361802 |
| - type: f1 |
| value: 54.22718458445455 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (ms) |
| config: ms |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
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| value: 58.991257565568255 |
| - type: f1 |
| value: 55.84892781767421 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (my) |
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| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (pt) |
| config: pt |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 68.18090114324143 |
| - type: f1 |
| value: 68.03737625431621 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (ro) |
| config: ro |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 64.65030262273034 |
| - type: f1 |
| value: 63.792945486912856 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (ru) |
| config: ru |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 69.48217888365838 |
| - type: f1 |
| value: 69.96028997292197 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (sl) |
| config: sl |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 60.17821116341627 |
| - type: f1 |
| value: 59.3935969827171 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (sq) |
| config: sq |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 62.86146603900471 |
| - type: f1 |
| value: 60.133692735032376 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (sv) |
| config: sv |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 70.89441829186282 |
| - type: f1 |
| value: 70.03064076194089 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (sw) |
| config: sw |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 58.15063887020847 |
| - type: f1 |
| value: 56.23326278499678 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (ta) |
| config: ta |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 59.43846671149966 |
| - type: f1 |
| value: 57.70440450281974 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (te) |
| config: te |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 60.8507061197041 |
| - type: f1 |
| value: 59.22916396061171 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (th) |
| config: th |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 70.65568258238063 |
| - type: f1 |
| value: 69.90736239440633 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (tl) |
| config: tl |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 60.8843308675185 |
| - type: f1 |
| value: 59.30332663713599 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (tr) |
| config: tr |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 68.05312710154674 |
| - type: f1 |
| value: 67.44024062594775 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (ur) |
| config: ur |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 62.111634162743776 |
| - type: f1 |
| value: 60.89083013084519 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (vi) |
| config: vi |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 67.44115669132482 |
| - type: f1 |
| value: 67.92227541674552 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (zh-CN) |
| config: zh-CN |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 74.4687289845326 |
| - type: f1 |
| value: 74.16376793486025 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (zh-TW) |
| config: zh-TW |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 68.31876260928043 |
| - type: f1 |
| value: 68.5246745215607 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-p2p |
| name: MTEB MedrxivClusteringP2P |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 30.90431696479766 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-s2s |
| name: MTEB MedrxivClusteringS2S |
| config: default |
| split: test |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| metrics: |
| - type: v_measure |
| value: 27.259158476693774 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/mind_small |
| name: MTEB MindSmallReranking |
| config: default |
| split: test |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| metrics: |
| - type: map |
| value: 30.28445330838555 |
| - type: mrr |
| value: 31.15758529581164 |
| - task: |
| type: Retrieval |
| dataset: |
| type: nfcorpus |
| name: MTEB 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: |
| type: nq |
| name: MTEB 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 |
| - type: ndcg_at_10 |
| value: 56.293000000000006 |
| - type: ndcg_at_100 |
| value: 60.167 |
| - type: ndcg_at_1000 |
| value: 60.916000000000004 |
| - type: ndcg_at_3 |
| value: 48.903999999999996 |
| - type: ndcg_at_5 |
| value: 52.978 |
| - type: precision_at_1 |
| value: 38.007000000000005 |
| - type: precision_at_10 |
| value: 9.041 |
| - type: precision_at_100 |
| value: 1.1199999999999999 |
| - type: precision_at_1000 |
| value: 0.11900000000000001 |
| - type: precision_at_3 |
| value: 22.084 |
| - type: precision_at_5 |
| value: 15.608 |
| - type: recall_at_1 |
| value: 33.852 |
| - type: recall_at_10 |
| value: 75.893 |
| - type: recall_at_100 |
| value: 92.589 |
| - type: recall_at_1000 |
| value: 98.153 |
| - type: recall_at_3 |
| value: 56.969 |
| - type: recall_at_5 |
| value: 66.283 |
| - task: |
| type: Retrieval |
| dataset: |
| type: quora |
| name: MTEB QuoraRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 69.174 |
| - type: map_at_10 |
| value: 82.891 |
| - type: map_at_100 |
| value: 83.545 |
| - type: map_at_1000 |
| value: 83.56700000000001 |
| - type: map_at_3 |
| value: 79.944 |
| - type: map_at_5 |
| value: 81.812 |
| - type: mrr_at_1 |
| value: 79.67999999999999 |
| - type: mrr_at_10 |
| value: 86.279 |
| - type: mrr_at_100 |
| value: 86.39 |
| - type: mrr_at_1000 |
| value: 86.392 |
| - type: mrr_at_3 |
| value: 85.21 |
| - type: mrr_at_5 |
| value: 85.92999999999999 |
| - type: ndcg_at_1 |
| value: 79.69000000000001 |
| - type: ndcg_at_10 |
| value: 86.929 |
| - type: ndcg_at_100 |
| value: 88.266 |
| - type: ndcg_at_1000 |
| value: 88.428 |
| - type: ndcg_at_3 |
| value: 83.899 |
| - type: ndcg_at_5 |
| value: 85.56700000000001 |
| - type: precision_at_1 |
| value: 79.69000000000001 |
| - type: precision_at_10 |
| value: 13.161000000000001 |
| - type: precision_at_100 |
| value: 1.513 |
| - type: precision_at_1000 |
| value: 0.156 |
| - type: precision_at_3 |
| value: 36.603 |
| - type: precision_at_5 |
| value: 24.138 |
| - type: recall_at_1 |
| value: 69.174 |
| - type: recall_at_10 |
| value: 94.529 |
| - type: recall_at_100 |
| value: 99.15 |
| - type: recall_at_1000 |
| value: 99.925 |
| - type: recall_at_3 |
| value: 85.86200000000001 |
| - type: recall_at_5 |
| value: 90.501 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering |
| name: MTEB RedditClustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 39.13064340585255 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering-p2p |
| name: MTEB RedditClusteringP2P |
| config: default |
| split: test |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| metrics: |
| - type: v_measure |
| value: 58.97884249325877 |
| - task: |
| type: Retrieval |
| dataset: |
| type: scidocs |
| name: MTEB 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 |
| - type: mrr_at_1000 |
| value: 26.889000000000003 |
| - type: mrr_at_3 |
| value: 22.8 |
| - type: mrr_at_5 |
| value: 24.26 |
| - type: ndcg_at_1 |
| value: 17.0 |
| - type: ndcg_at_10 |
| value: 13.895 |
| - type: ndcg_at_100 |
| value: 20.491999999999997 |
| - type: ndcg_at_1000 |
| value: 25.759999999999998 |
| - type: ndcg_at_3 |
| value: 13.347999999999999 |
| - type: ndcg_at_5 |
| value: 11.61 |
| - type: precision_at_1 |
| value: 17.0 |
| - type: precision_at_10 |
| value: 7.090000000000001 |
| - type: precision_at_100 |
| value: 1.669 |
| - type: precision_at_1000 |
| value: 0.294 |
| - type: precision_at_3 |
| value: 12.3 |
| - type: precision_at_5 |
| value: 10.02 |
| - type: recall_at_1 |
| value: 3.4680000000000004 |
| - type: recall_at_10 |
| value: 14.363000000000001 |
| - type: recall_at_100 |
| value: 33.875 |
| - type: recall_at_1000 |
| value: 59.711999999999996 |
| - type: recall_at_3 |
| value: 7.483 |
| - type: recall_at_5 |
| value: 10.173 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sickr-sts |
| name: MTEB SICK-R |
| config: default |
| split: test |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| metrics: |
| - type: cos_sim_pearson |
| value: 83.04084311714061 |
| - type: cos_sim_spearman |
| value: 77.51342467443078 |
| - type: euclidean_pearson |
| value: 80.0321166028479 |
| - type: euclidean_spearman |
| value: 77.29249114733226 |
| - type: manhattan_pearson |
| value: 80.03105964262431 |
| - type: manhattan_spearman |
| value: 77.22373689514794 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts12-sts |
| name: MTEB STS12 |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 84.1680158034387 |
| - type: cos_sim_spearman |
| value: 76.55983344071117 |
| - type: euclidean_pearson |
| value: 79.75266678300143 |
| - type: euclidean_spearman |
| value: 75.34516823467025 |
| - type: manhattan_pearson |
| value: 79.75959151517357 |
| - type: manhattan_spearman |
| value: 75.42330344141912 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts13-sts |
| name: MTEB STS13 |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 76.48898993209346 |
| - type: cos_sim_spearman |
| value: 76.96954120323366 |
| - type: euclidean_pearson |
| value: 76.94139109279668 |
| - type: euclidean_spearman |
| value: 76.85860283201711 |
| - type: manhattan_pearson |
| value: 76.6944095091912 |
| - type: manhattan_spearman |
| value: 76.61096912972553 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts14-sts |
| name: MTEB STS14 |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 77.85082366246944 |
| - type: cos_sim_spearman |
| value: 75.52053350101731 |
| - type: euclidean_pearson |
| value: 77.1165845070926 |
| - type: euclidean_spearman |
| value: 75.31216065884388 |
| - type: manhattan_pearson |
| value: 77.06193941833494 |
| - type: manhattan_spearman |
| value: 75.31003701700112 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts15-sts |
| name: MTEB STS15 |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 86.36305246526497 |
| - type: cos_sim_spearman |
| value: 87.11704613927415 |
| - type: euclidean_pearson |
| value: 86.04199125810939 |
| - type: euclidean_spearman |
| value: 86.51117572414263 |
| - type: manhattan_pearson |
| value: 86.0805106816633 |
| - type: manhattan_spearman |
| value: 86.52798366512229 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts16-sts |
| name: MTEB STS16 |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 82.18536255599724 |
| - type: cos_sim_spearman |
| value: 83.63377151025418 |
| - type: euclidean_pearson |
| value: 83.24657467993141 |
| - type: euclidean_spearman |
| value: 84.02751481993825 |
| - type: manhattan_pearson |
| value: 83.11941806582371 |
| - type: manhattan_spearman |
| value: 83.84251281019304 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (ko-ko) |
| config: ko-ko |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 78.95816528475514 |
| - type: cos_sim_spearman |
| value: 78.86607380120462 |
| - type: euclidean_pearson |
| value: 78.51268699230545 |
| - type: euclidean_spearman |
| value: 79.11649316502229 |
| - type: manhattan_pearson |
| value: 78.32367302808157 |
| - type: manhattan_spearman |
| value: 78.90277699624637 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (ar-ar) |
| config: ar-ar |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 72.89126914997624 |
| - type: cos_sim_spearman |
| value: 73.0296921832678 |
| - type: euclidean_pearson |
| value: 71.50385903677738 |
| - type: euclidean_spearman |
| value: 73.13368899716289 |
| - type: manhattan_pearson |
| value: 71.47421463379519 |
| - type: manhattan_spearman |
| value: 73.03383242946575 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (en-ar) |
| config: en-ar |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 59.22923684492637 |
| - type: cos_sim_spearman |
| value: 57.41013211368396 |
| - type: euclidean_pearson |
| value: 61.21107388080905 |
| - type: euclidean_spearman |
| value: 60.07620768697254 |
| - type: manhattan_pearson |
| value: 59.60157142786555 |
| - type: manhattan_spearman |
| value: 59.14069604103739 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (en-de) |
| config: en-de |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 76.24345978774299 |
| - type: cos_sim_spearman |
| value: 77.24225743830719 |
| - type: euclidean_pearson |
| value: 76.66226095469165 |
| - type: euclidean_spearman |
| value: 77.60708820493146 |
| - type: manhattan_pearson |
| value: 76.05303324760429 |
| - type: manhattan_spearman |
| value: 76.96353149912348 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (en-en) |
| config: en-en |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.50879160160852 |
| - type: cos_sim_spearman |
| value: 86.43594662965224 |
| - type: euclidean_pearson |
| value: 86.06846012826577 |
| - type: euclidean_spearman |
| value: 86.02041395794136 |
| - type: manhattan_pearson |
| value: 86.10916255616904 |
| - type: manhattan_spearman |
| value: 86.07346068198953 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (en-tr) |
| config: en-tr |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 58.39803698977196 |
| - type: cos_sim_spearman |
| value: 55.96910950423142 |
| - type: euclidean_pearson |
| value: 58.17941175613059 |
| - type: euclidean_spearman |
| value: 55.03019330522745 |
| - type: manhattan_pearson |
| value: 57.333358138183286 |
| - type: manhattan_spearman |
| value: 54.04614023149965 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (es-en) |
| config: es-en |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 70.98304089637197 |
| - type: cos_sim_spearman |
| value: 72.44071656215888 |
| - type: euclidean_pearson |
| value: 72.19224359033983 |
| - type: euclidean_spearman |
| value: 73.89871188913025 |
| - type: manhattan_pearson |
| value: 71.21098311547406 |
| - type: manhattan_spearman |
| value: 72.93405764824821 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (es-es) |
| config: es-es |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.99792397466308 |
| - type: cos_sim_spearman |
| value: 84.83824377879495 |
| - type: euclidean_pearson |
| value: 85.70043288694438 |
| - type: euclidean_spearman |
| value: 84.70627558703686 |
| - type: manhattan_pearson |
| value: 85.89570850150801 |
| - type: manhattan_spearman |
| value: 84.95806105313007 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (fr-en) |
| config: fr-en |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 72.21850322994712 |
| - type: cos_sim_spearman |
| value: 72.28669398117248 |
| - type: euclidean_pearson |
| value: 73.40082510412948 |
| - type: euclidean_spearman |
| value: 73.0326539281865 |
| - type: manhattan_pearson |
| value: 71.8659633964841 |
| - type: manhattan_spearman |
| value: 71.57817425823303 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (it-en) |
| config: it-en |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 75.80921368595645 |
| - type: cos_sim_spearman |
| value: 77.33209091229315 |
| - type: euclidean_pearson |
| value: 76.53159540154829 |
| - type: euclidean_spearman |
| value: 78.17960842810093 |
| - type: manhattan_pearson |
| value: 76.13530186637601 |
| - type: manhattan_spearman |
| value: 78.00701437666875 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (nl-en) |
| config: nl-en |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 74.74980608267349 |
| - type: cos_sim_spearman |
| value: 75.37597374318821 |
| - type: euclidean_pearson |
| value: 74.90506081911661 |
| - type: euclidean_spearman |
| value: 75.30151613124521 |
| - type: manhattan_pearson |
| value: 74.62642745918002 |
| - type: manhattan_spearman |
| value: 75.18619716592303 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (en) |
| config: en |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 59.632662289205584 |
| - type: cos_sim_spearman |
| value: 60.938543391610914 |
| - type: euclidean_pearson |
| value: 62.113200529767056 |
| - type: euclidean_spearman |
| value: 61.410312633261164 |
| - type: manhattan_pearson |
| value: 61.75494698945686 |
| - type: manhattan_spearman |
| value: 60.92726195322362 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (de) |
| config: de |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 45.283470551557244 |
| - type: cos_sim_spearman |
| value: 53.44833015864201 |
| - type: euclidean_pearson |
| value: 41.17892011120893 |
| - type: euclidean_spearman |
| value: 53.81441383126767 |
| - type: manhattan_pearson |
| value: 41.17482200420659 |
| - type: manhattan_spearman |
| value: 53.82180269276363 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (es) |
| config: es |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 60.5069165306236 |
| - type: cos_sim_spearman |
| value: 66.87803259033826 |
| - type: euclidean_pearson |
| value: 63.5428979418236 |
| - type: euclidean_spearman |
| value: 66.9293576586897 |
| - type: manhattan_pearson |
| value: 63.59789526178922 |
| - type: manhattan_spearman |
| value: 66.86555009875066 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (pl) |
| config: pl |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 28.23026196280264 |
| - type: cos_sim_spearman |
| value: 35.79397812652861 |
| - type: euclidean_pearson |
| value: 17.828102102767353 |
| - type: euclidean_spearman |
| value: 35.721501145568894 |
| - type: manhattan_pearson |
| value: 17.77134274219677 |
| - type: manhattan_spearman |
| value: 35.98107902846267 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (tr) |
| config: tr |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 56.51946541393812 |
| - type: cos_sim_spearman |
| value: 63.714686006214485 |
| - type: euclidean_pearson |
| value: 58.32104651305898 |
| - type: euclidean_spearman |
| value: 62.237110895702216 |
| - type: manhattan_pearson |
| value: 58.579416468759185 |
| - type: manhattan_spearman |
| value: 62.459738981727 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (ar) |
| config: ar |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 48.76009839569795 |
| - type: cos_sim_spearman |
| value: 56.65188431953149 |
| - type: euclidean_pearson |
| value: 50.997682160915595 |
| - type: euclidean_spearman |
| value: 55.99910008818135 |
| - type: manhattan_pearson |
| value: 50.76220659606342 |
| - type: manhattan_spearman |
| value: 55.517347595391456 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (ru) |
| config: ru |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 51.232731157702425 |
| - type: cos_sim_spearman |
| value: 59.89531877658345 |
| - type: euclidean_pearson |
| value: 49.937914570348376 |
| - type: euclidean_spearman |
| value: 60.220905659334036 |
| - type: manhattan_pearson |
| value: 50.00987996844193 |
| - type: manhattan_spearman |
| value: 60.081341480977926 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (zh) |
| config: zh |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 54.717524559088005 |
| - type: cos_sim_spearman |
| value: 66.83570886252286 |
| - type: euclidean_pearson |
| value: 58.41338625505467 |
| - type: euclidean_spearman |
| value: 66.68991427704938 |
| - type: manhattan_pearson |
| value: 58.78638572916807 |
| - type: manhattan_spearman |
| value: 66.58684161046335 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (fr) |
| config: fr |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 73.2962042954962 |
| - type: cos_sim_spearman |
| value: 76.58255504852025 |
| - type: euclidean_pearson |
| value: 75.70983192778257 |
| - type: euclidean_spearman |
| value: 77.4547684870542 |
| - type: manhattan_pearson |
| value: 75.75565853870485 |
| - type: manhattan_spearman |
| value: 76.90208974949428 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (de-en) |
| config: de-en |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 54.47396266924846 |
| - type: cos_sim_spearman |
| value: 56.492267162048606 |
| - type: euclidean_pearson |
| value: 55.998505203070195 |
| - type: euclidean_spearman |
| value: 56.46447012960222 |
| - type: manhattan_pearson |
| value: 54.873172394430995 |
| - type: manhattan_spearman |
| value: 56.58111534551218 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (es-en) |
| config: es-en |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 69.87177267688686 |
| - type: cos_sim_spearman |
| value: 74.57160943395763 |
| - type: euclidean_pearson |
| value: 70.88330406826788 |
| - type: euclidean_spearman |
| value: 74.29767636038422 |
| - type: manhattan_pearson |
| value: 71.38245248369536 |
| - type: manhattan_spearman |
| value: 74.53102232732175 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (it) |
| config: it |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 72.80225656959544 |
| - type: cos_sim_spearman |
| value: 76.52646173725735 |
| - type: euclidean_pearson |
| value: 73.95710720200799 |
| - type: euclidean_spearman |
| value: 76.54040031984111 |
| - type: manhattan_pearson |
| value: 73.89679971946774 |
| - type: manhattan_spearman |
| value: 76.60886958161574 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (pl-en) |
| config: pl-en |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 70.70844249898789 |
| - type: cos_sim_spearman |
| value: 72.68571783670241 |
| - type: euclidean_pearson |
| value: 72.38800772441031 |
| - type: euclidean_spearman |
| value: 72.86804422703312 |
| - type: manhattan_pearson |
| value: 71.29840508203515 |
| - type: manhattan_spearman |
| value: 71.86264441749513 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (zh-en) |
| config: zh-en |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 58.647478923935694 |
| - type: cos_sim_spearman |
| value: 63.74453623540931 |
| - type: euclidean_pearson |
| value: 59.60138032437505 |
| - type: euclidean_spearman |
| value: 63.947930832166065 |
| - type: manhattan_pearson |
| value: 58.59735509491861 |
| - type: manhattan_spearman |
| value: 62.082503844627404 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (es-it) |
| config: es-it |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 65.8722516867162 |
| - type: cos_sim_spearman |
| value: 71.81208592523012 |
| - type: euclidean_pearson |
| value: 67.95315252165956 |
| - type: euclidean_spearman |
| value: 73.00749822046009 |
| - type: manhattan_pearson |
| value: 68.07884688638924 |
| - type: manhattan_spearman |
| value: 72.34210325803069 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (de-fr) |
| config: de-fr |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 54.5405814240949 |
| - type: cos_sim_spearman |
| value: 60.56838649023775 |
| - 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: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (de-pl) |
| 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: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (fr-pl) |
| 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: |
| type: mteb/stsbenchmark-sts |
| name: MTEB STSBenchmark |
| 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: |
| type: mteb/scidocs-reranking |
| name: MTEB SciDocsRR |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 78.12945623123957 |
| - type: mrr |
| value: 93.87738713719106 |
| - task: |
| type: Retrieval |
| dataset: |
| type: scifact |
| name: MTEB 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: |
| type: mteb/sprintduplicatequestions-pairclassification |
| name: MTEB SprintDuplicateQuestions |
| 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: |
| type: mteb/stackexchange-clustering |
| name: MTEB StackExchangeClustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 53.52464042600003 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering-p2p |
| name: MTEB StackExchangeClusteringP2P |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 32.071631948736 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/stackoverflowdupquestions-reranking |
| name: MTEB StackOverflowDupQuestions |
| config: default |
| split: test |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| metrics: |
| - type: map |
| value: 49.19552407604654 |
| - type: mrr |
| value: 49.95269130379425 |
| - task: |
| type: Summarization |
| dataset: |
| type: mteb/summeval |
| name: 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: |
| type: trec-covid |
| name: MTEB TRECCOVID |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (sqi-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (fry-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (kur-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (tur-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (deu-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (nld-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ron-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ang-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ido-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (jav-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (isl-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (slv-eng) |
| config: slv-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 77.52126366950182 |
| - type: f1 |
| value: 72.8496210148701 |
| - type: precision |
| value: 70.92171498003819 |
| - type: recall |
| value: 77.52126366950182 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (cym-eng) |
| config: cym-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 70.78260869565217 |
| - type: f1 |
| value: 65.32422360248447 |
| - type: precision |
| value: 63.063067367415194 |
| - type: recall |
| value: 70.78260869565217 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (kaz-eng) |
| config: kaz-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 78.43478260869566 |
| - type: f1 |
| value: 73.02608695652172 |
| - type: precision |
| value: 70.63768115942028 |
| - type: recall |
| value: 78.43478260869566 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (est-eng) |
| config: est-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 60.9 |
| - type: f1 |
| value: 55.309753694581275 |
| - type: precision |
| value: 53.130476190476195 |
| - type: recall |
| value: 60.9 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (heb-eng) |
| config: heb-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 72.89999999999999 |
| - type: f1 |
| value: 67.92023809523809 |
| - type: precision |
| value: 65.82595238095237 |
| - type: recall |
| value: 72.89999999999999 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (gla-eng) |
| config: gla-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 46.80337756332931 |
| - type: f1 |
| value: 39.42174900558496 |
| - type: precision |
| value: 36.97101116280851 |
| - type: recall |
| value: 46.80337756332931 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (mar-eng) |
| config: mar-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 89.8 |
| - type: f1 |
| value: 86.79 |
| - type: precision |
| value: 85.375 |
| - type: recall |
| value: 89.8 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (lat-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (bel-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (pms-eng) |
| config: pms-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 48.76190476190476 |
| - type: f1 |
| value: 42.14965986394558 |
| - type: precision |
| value: 39.96743626743626 |
| - type: recall |
| value: 48.76190476190476 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (gle-eng) |
| config: gle-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 66.10000000000001 |
| - type: f1 |
| value: 59.58580086580086 |
| - type: precision |
| value: 57.150238095238095 |
| - type: recall |
| value: 66.10000000000001 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (pes-eng) |
| config: pes-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 87.3 |
| - type: f1 |
| value: 84.0 |
| - type: precision |
| value: 82.48666666666666 |
| - type: recall |
| value: 87.3 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (nob-eng) |
| config: nob-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 90.4 |
| - type: f1 |
| value: 87.79523809523809 |
| - type: precision |
| value: 86.6 |
| - type: recall |
| value: 90.4 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (bul-eng) |
| config: bul-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 87.0 |
| - type: f1 |
| value: 83.81 |
| - type: precision |
| value: 82.36666666666666 |
| - type: recall |
| value: 87.0 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (cbk-eng) |
| config: cbk-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 63.9 |
| - type: f1 |
| value: 57.76533189033189 |
| - type: precision |
| value: 55.50595238095239 |
| - type: recall |
| value: 63.9 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (hun-eng) |
| config: hun-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 76.1 |
| - type: f1 |
| value: 71.83690476190478 |
| - type: precision |
| value: 70.04928571428573 |
| - type: recall |
| value: 76.1 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (uig-eng) |
| config: uig-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 66.3 |
| - type: f1 |
| value: 59.32626984126984 |
| - type: precision |
| value: 56.62535714285713 |
| - type: recall |
| value: 66.3 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (rus-eng) |
| config: rus-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 90.60000000000001 |
| - type: f1 |
| value: 87.96333333333334 |
| - type: precision |
| value: 86.73333333333333 |
| - type: recall |
| value: 90.60000000000001 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (spa-eng) |
| config: spa-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 93.10000000000001 |
| - type: f1 |
| value: 91.10000000000001 |
| - type: precision |
| value: 90.16666666666666 |
| - type: recall |
| value: 93.10000000000001 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (hye-eng) |
| config: hye-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 85.71428571428571 |
| - type: f1 |
| value: 82.29142600436403 |
| - type: precision |
| value: 80.8076626877166 |
| - type: recall |
| value: 85.71428571428571 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (tel-eng) |
| config: tel-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 88.88888888888889 |
| - type: f1 |
| value: 85.7834757834758 |
| - type: precision |
| value: 84.43732193732193 |
| - type: recall |
| value: 88.88888888888889 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (afr-eng) |
| config: afr-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 88.5 |
| - type: f1 |
| value: 85.67190476190476 |
| - type: precision |
| value: 84.43333333333332 |
| - type: recall |
| value: 88.5 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (mon-eng) |
| config: mon-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 82.72727272727273 |
| - type: f1 |
| value: 78.21969696969695 |
| - type: precision |
| value: 76.18181818181819 |
| - type: recall |
| value: 82.72727272727273 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (arz-eng) |
| config: arz-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 61.0062893081761 |
| - type: f1 |
| value: 55.13976240391334 |
| - type: precision |
| value: 52.92112499659669 |
| - type: recall |
| value: 61.0062893081761 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (hrv-eng) |
| config: hrv-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 89.5 |
| - type: f1 |
| value: 86.86666666666666 |
| - type: precision |
| value: 85.69166666666668 |
| - type: recall |
| value: 89.5 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (nov-eng) |
| config: nov-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 73.54085603112841 |
| - type: f1 |
| value: 68.56031128404669 |
| - type: precision |
| value: 66.53047989623866 |
| - type: recall |
| value: 73.54085603112841 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (gsw-eng) |
| config: gsw-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 43.58974358974359 |
| - type: f1 |
| value: 36.45299145299145 |
| - type: precision |
| value: 33.81155881155882 |
| - type: recall |
| value: 43.58974358974359 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (nds-eng) |
| config: nds-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 59.599999999999994 |
| - type: f1 |
| value: 53.264689754689755 |
| - type: precision |
| value: 50.869166666666665 |
| - type: recall |
| value: 59.599999999999994 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ukr-eng) |
| config: ukr-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 85.2 |
| - type: f1 |
| value: 81.61666666666665 |
| - type: precision |
| value: 80.02833333333335 |
| - type: recall |
| value: 85.2 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (uzb-eng) |
| config: uzb-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 63.78504672897196 |
| - type: f1 |
| value: 58.00029669188548 |
| - type: precision |
| value: 55.815809968847354 |
| - type: recall |
| value: 63.78504672897196 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (lit-eng) |
| config: lit-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 66.5 |
| - type: f1 |
| value: 61.518333333333345 |
| - type: precision |
| value: 59.622363699102834 |
| - type: recall |
| value: 66.5 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ina-eng) |
| config: ina-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 88.6 |
| - type: f1 |
| value: 85.60222222222221 |
| - type: precision |
| value: 84.27916666666665 |
| - type: recall |
| value: 88.6 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (lfn-eng) |
| config: lfn-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 58.699999999999996 |
| - type: f1 |
| value: 52.732375957375965 |
| - type: precision |
| value: 50.63214035964035 |
| - type: recall |
| value: 58.699999999999996 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (zsm-eng) |
| config: zsm-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 92.10000000000001 |
| - type: f1 |
| value: 89.99666666666667 |
| - type: precision |
| value: 89.03333333333333 |
| - type: recall |
| value: 92.10000000000001 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ita-eng) |
| config: ita-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 90.10000000000001 |
| - type: f1 |
| value: 87.55666666666667 |
| - type: precision |
| value: 86.36166666666668 |
| - type: recall |
| value: 90.10000000000001 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (cmn-eng) |
| config: cmn-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 91.4 |
| - type: f1 |
| value: 88.89000000000001 |
| - type: precision |
| value: 87.71166666666666 |
| - type: recall |
| value: 91.4 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (lvs-eng) |
| config: lvs-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 65.7 |
| - type: f1 |
| value: 60.67427750410509 |
| - type: precision |
| value: 58.71785714285714 |
| - type: recall |
| value: 65.7 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (glg-eng) |
| config: glg-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 85.39999999999999 |
| - type: f1 |
| value: 81.93190476190475 |
| - type: precision |
| value: 80.37833333333333 |
| - type: recall |
| value: 85.39999999999999 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ceb-eng) |
| config: ceb-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 47.833333333333336 |
| - type: f1 |
| value: 42.006625781625786 |
| - type: precision |
| value: 40.077380952380956 |
| - type: recall |
| value: 47.833333333333336 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (bre-eng) |
| config: bre-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 10.4 |
| - type: f1 |
| value: 8.24465007215007 |
| - type: precision |
| value: 7.664597069597071 |
| - type: recall |
| value: 10.4 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ben-eng) |
| config: ben-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 82.6 |
| - type: f1 |
| value: 77.76333333333334 |
| - type: precision |
| value: 75.57833333333332 |
| - type: recall |
| value: 82.6 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (swg-eng) |
| config: swg-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 52.67857142857143 |
| - type: f1 |
| value: 44.302721088435376 |
| - type: precision |
| value: 41.49801587301587 |
| - type: recall |
| value: 52.67857142857143 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (arq-eng) |
| config: arq-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 28.3205268935236 |
| - type: f1 |
| value: 22.426666605171157 |
| - type: precision |
| value: 20.685900116470915 |
| - type: recall |
| value: 28.3205268935236 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (kab-eng) |
| config: kab-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 22.7 |
| - type: f1 |
| value: 17.833970473970474 |
| - type: precision |
| value: 16.407335164835164 |
| - type: recall |
| value: 22.7 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (fra-eng) |
| config: fra-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 92.2 |
| - type: f1 |
| value: 89.92999999999999 |
| - type: precision |
| value: 88.87 |
| - type: recall |
| value: 92.2 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (por-eng) |
| config: por-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 91.4 |
| - type: f1 |
| value: 89.25 |
| - type: precision |
| value: 88.21666666666667 |
| - type: recall |
| value: 91.4 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (tat-eng) |
| config: tat-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 69.19999999999999 |
| - type: f1 |
| value: 63.38269841269841 |
| - type: precision |
| value: 61.14773809523809 |
| - type: recall |
| value: 69.19999999999999 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (oci-eng) |
| config: oci-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 48.8 |
| - type: f1 |
| value: 42.839915639915645 |
| - type: precision |
| value: 40.770287114845935 |
| - type: recall |
| value: 48.8 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (pol-eng) |
| config: pol-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 88.8 |
| - type: f1 |
| value: 85.90666666666668 |
| - type: precision |
| value: 84.54166666666666 |
| - type: recall |
| value: 88.8 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (war-eng) |
| config: war-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 46.6 |
| - type: f1 |
| value: 40.85892920804686 |
| - type: precision |
| value: 38.838223114604695 |
| - type: recall |
| value: 46.6 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (aze-eng) |
| config: aze-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 84.0 |
| - type: f1 |
| value: 80.14190476190475 |
| - type: precision |
| value: 78.45333333333333 |
| - type: recall |
| value: 84.0 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (vie-eng) |
| config: vie-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 90.5 |
| - type: f1 |
| value: 87.78333333333333 |
| - type: precision |
| value: 86.5 |
| - type: recall |
| value: 90.5 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (nno-eng) |
| config: nno-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 74.5 |
| - type: f1 |
| value: 69.48397546897547 |
| - type: precision |
| value: 67.51869047619049 |
| - type: recall |
| value: 74.5 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (cha-eng) |
| config: cha-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 32.846715328467155 |
| - type: f1 |
| value: 27.828177499710343 |
| - type: precision |
| value: 26.63451511991658 |
| - type: recall |
| value: 32.846715328467155 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (mhr-eng) |
| config: mhr-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 8.0 |
| - type: f1 |
| value: 6.07664116764988 |
| - type: precision |
| value: 5.544177607179943 |
| - type: recall |
| value: 8.0 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (dan-eng) |
| config: dan-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 87.6 |
| - type: f1 |
| value: 84.38555555555554 |
| - type: precision |
| value: 82.91583333333334 |
| - type: recall |
| value: 87.6 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ell-eng) |
| config: ell-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 87.5 |
| - type: f1 |
| value: 84.08333333333331 |
| - type: precision |
| value: 82.47333333333333 |
| - type: recall |
| value: 87.5 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (amh-eng) |
| config: amh-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 80.95238095238095 |
| - type: f1 |
| value: 76.13095238095238 |
| - type: precision |
| value: 74.05753968253967 |
| - type: recall |
| value: 80.95238095238095 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (pam-eng) |
| config: pam-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 8.799999999999999 |
| - type: f1 |
| value: 6.971422975172975 |
| - type: precision |
| value: 6.557814916172301 |
| - type: recall |
| value: 8.799999999999999 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (hsb-eng) |
| config: hsb-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 44.099378881987576 |
| - type: f1 |
| value: 37.01649742022413 |
| - type: precision |
| value: 34.69420618488942 |
| - type: recall |
| value: 44.099378881987576 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (srp-eng) |
| config: srp-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 84.3 |
| - type: f1 |
| value: 80.32666666666667 |
| - type: precision |
| value: 78.60666666666665 |
| - type: recall |
| value: 84.3 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (epo-eng) |
| config: epo-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 92.5 |
| - type: f1 |
| value: 90.49666666666666 |
| - type: precision |
| value: 89.56666666666668 |
| - type: recall |
| value: 92.5 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (kzj-eng) |
| config: kzj-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 10.0 |
| - type: f1 |
| value: 8.268423529875141 |
| - type: precision |
| value: 7.878118605532398 |
| - type: recall |
| value: 10.0 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (awa-eng) |
| config: awa-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 79.22077922077922 |
| - type: f1 |
| value: 74.27128427128426 |
| - type: precision |
| value: 72.28715728715729 |
| - type: recall |
| value: 79.22077922077922 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (fao-eng) |
| config: fao-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 65.64885496183206 |
| - type: f1 |
| value: 58.87495456197747 |
| - type: precision |
| value: 55.992366412213734 |
| - type: recall |
| value: 65.64885496183206 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (mal-eng) |
| config: mal-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 96.06986899563319 |
| - type: f1 |
| value: 94.78408539543909 |
| - type: precision |
| value: 94.15332362930616 |
| - type: recall |
| value: 96.06986899563319 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ile-eng) |
| config: ile-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 77.2 |
| - type: f1 |
| value: 71.72571428571428 |
| - type: precision |
| value: 69.41000000000001 |
| - type: recall |
| value: 77.2 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (bos-eng) |
| config: bos-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 86.4406779661017 |
| - type: f1 |
| value: 83.2391713747646 |
| - type: precision |
| value: 81.74199623352166 |
| - type: recall |
| value: 86.4406779661017 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (cor-eng) |
| config: cor-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 8.4 |
| - type: f1 |
| value: 6.017828743398003 |
| - type: precision |
| value: 5.4829865484756795 |
| - type: recall |
| value: 8.4 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (cat-eng) |
| config: cat-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 83.5 |
| - type: f1 |
| value: 79.74833333333333 |
| - type: precision |
| value: 78.04837662337664 |
| - type: recall |
| value: 83.5 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (eus-eng) |
| config: eus-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 60.4 |
| - type: f1 |
| value: 54.467301587301584 |
| - type: precision |
| value: 52.23242424242424 |
| - type: recall |
| value: 60.4 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (yue-eng) |
| config: yue-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 74.9 |
| - type: f1 |
| value: 69.68699134199134 |
| - type: precision |
| value: 67.59873015873016 |
| - type: recall |
| value: 74.9 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (swe-eng) |
| config: swe-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 88.0 |
| - type: f1 |
| value: 84.9652380952381 |
| - type: precision |
| value: 83.66166666666666 |
| - type: recall |
| value: 88.0 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (dtp-eng) |
| config: dtp-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 9.1 |
| - type: f1 |
| value: 7.681244588744588 |
| - type: precision |
| value: 7.370043290043291 |
| - type: recall |
| value: 9.1 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (kat-eng) |
| config: kat-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 80.9651474530831 |
| - type: f1 |
| value: 76.84220605132133 |
| - type: precision |
| value: 75.19606398962966 |
| - type: recall |
| value: 80.9651474530831 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (jpn-eng) |
| config: jpn-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 86.9 |
| - type: f1 |
| value: 83.705 |
| - type: precision |
| value: 82.3120634920635 |
| - type: recall |
| value: 86.9 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (csb-eng) |
| config: csb-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 29.64426877470356 |
| - type: f1 |
| value: 23.98763072676116 |
| - type: precision |
| value: 22.506399397703746 |
| - type: recall |
| value: 29.64426877470356 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (xho-eng) |
| config: xho-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 70.4225352112676 |
| - type: f1 |
| value: 62.84037558685445 |
| - type: precision |
| value: 59.56572769953053 |
| - type: recall |
| value: 70.4225352112676 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (orv-eng) |
| config: orv-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 19.64071856287425 |
| - type: f1 |
| value: 15.125271011207756 |
| - type: precision |
| value: 13.865019261197494 |
| - type: recall |
| value: 19.64071856287425 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ind-eng) |
| config: ind-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 90.2 |
| - type: f1 |
| value: 87.80666666666666 |
| - type: precision |
| value: 86.70833333333331 |
| - type: recall |
| value: 90.2 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (tuk-eng) |
| config: tuk-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 23.15270935960591 |
| - type: f1 |
| value: 18.407224958949097 |
| - type: precision |
| value: 16.982385430661292 |
| - type: recall |
| value: 23.15270935960591 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (max-eng) |
| config: max-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 55.98591549295775 |
| - type: f1 |
| value: 49.94718309859154 |
| - type: precision |
| value: 47.77864154624717 |
| - type: recall |
| value: 55.98591549295775 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (swh-eng) |
| config: swh-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 73.07692307692307 |
| - type: f1 |
| value: 66.74358974358974 |
| - type: precision |
| value: 64.06837606837607 |
| - type: recall |
| value: 73.07692307692307 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (hin-eng) |
| config: hin-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 94.89999999999999 |
| - type: f1 |
| value: 93.25 |
| - type: precision |
| value: 92.43333333333332 |
| - type: recall |
| value: 94.89999999999999 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (dsb-eng) |
| config: dsb-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 37.78705636743215 |
| - type: f1 |
| value: 31.63899658680452 |
| - type: precision |
| value: 29.72264397629742 |
| - type: recall |
| value: 37.78705636743215 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ber-eng) |
| config: ber-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 21.6 |
| - type: f1 |
| value: 16.91697302697303 |
| - type: precision |
| value: 15.71225147075147 |
| - type: recall |
| value: 21.6 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (tam-eng) |
| config: tam-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 85.01628664495115 |
| - type: f1 |
| value: 81.38514037536838 |
| - type: precision |
| value: 79.83170466883823 |
| - type: recall |
| value: 85.01628664495115 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (slk-eng) |
| config: slk-eng |
| split: test |
| revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| metrics: |
| - type: accuracy |
| value: 83.39999999999999 |
| - type: f1 |
| value: 79.96380952380952 |
| - type: precision |
| value: 78.48333333333333 |
| - type: recall |
| value: 83.39999999999999 |
| - task: |
| type: BitextMining |
| dataset: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (tgl-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ast-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (mkd-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (khm-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ces-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (tzl-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (urd-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (ara-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (kor-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (yid-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (fin-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (tha-eng) |
| 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: |
| type: mteb/tatoeba-bitext-mining |
| name: MTEB Tatoeba (wuu-eng) |
| 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: |
| type: webis-touche2020 |
| name: MTEB 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: |
| type: mteb/toxic_conversations_50k |
| name: MTEB ToxicConversationsClassification |
| 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: |
| type: mteb/tweet_sentiment_extraction |
| name: MTEB TweetSentimentExtractionClassification |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 62.62026032823995 |
| - type: f1 |
| value: 62.85251350485221 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/twentynewsgroups-clustering |
| name: MTEB TwentyNewsgroupsClustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 33.21527881409797 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twittersemeval2015-pairclassification |
| name: MTEB TwitterSemEval2015 |
| 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: |
| type: mteb/twitterurlcorpus-pairclassification |
| name: MTEB TwitterURLCorpus |
| 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 |
| 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 |
| --- |
| |
| ## Multilingual-E5-small |
|
|
| [Text Embeddings by Weakly-Supervised Contrastive Pre-training](https://arxiv.org/pdf/2212.03533.pdf). |
| Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022 |
|
|
| This model has 12 layers and the embedding size is 384. |
|
|
| ## Usage |
|
|
| Below is an example to encode queries and passages from the MS-MARCO passage ranking dataset. |
|
|
| ```python |
| import torch.nn.functional as F |
| |
| from torch import Tensor |
| from transformers import AutoTokenizer, AutoModel |
| |
| |
| def average_pool(last_hidden_states: Tensor, |
| attention_mask: Tensor) -> Tensor: |
| last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0) |
| return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None] |
| |
| |
| # Each input text should start with "query: " or "passage: ", even for non-English texts. |
| # For tasks other than retrieval, you can simply use the "query: " prefix. |
| input_texts = ['query: how much protein should a female eat', |
| 'query: 南瓜的家常做法', |
| "passage: As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.", |
| "passage: 1.清炒南瓜丝 原料:嫩南瓜半个 调料:葱、盐、白糖、鸡精 做法: 1、南瓜用刀薄薄的削去表面一层皮,用勺子刮去瓤 2、擦成细丝(没有擦菜板就用刀慢慢切成细丝) 3、锅烧热放油,入葱花煸出香味 4、入南瓜丝快速翻炒一分钟左右,放盐、一点白糖和鸡精调味出锅 2.香葱炒南瓜 原料:南瓜1只 调料:香葱、蒜末、橄榄油、盐 做法: 1、将南瓜去皮,切成片 2、油锅8成热后,将蒜末放入爆香 3、爆香后,将南瓜片放入,翻炒 4、在翻炒的同时,可以不时地往锅里加水,但不要太多 5、放入盐,炒匀 6、南瓜差不多软和绵了之后,就可以关火 7、撒入香葱,即可出锅"] |
| |
| tokenizer = AutoTokenizer.from_pretrained('intfloat/multilingual-e5-small') |
| model = AutoModel.from_pretrained('intfloat/multilingual-e5-small') |
| |
| # Tokenize the input texts |
| batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt') |
| |
| outputs = model(**batch_dict) |
| embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask']) |
| |
| # (Optionally) normalize embeddings |
| embeddings = F.normalize(embeddings, p=2, dim=1) |
| scores = (embeddings[:2] @ embeddings[2:].T) * 100 |
| print(scores.tolist()) |
| ``` |
|
|
| ## Supported Languages |
|
|
| This model is initialized from [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) |
| and continually trained on a mixture of multilingual datasets. |
| It supports 100 languages from xlm-roberta, |
| but low-resource languages may see performance degradation. |
|
|
| ## Training Details |
|
|
| **Initialization**: [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) |
|
|
| **First stage**: contrastive pre-training with weak supervision |
|
|
| | Dataset | Weak supervision | # of text pairs | |
| |--------------------------------------------------------------------------------------------------------|---------------------------------------|-----------------| |
| | Filtered [mC4](https://huggingface.co/datasets/mc4) | (title, page content) | 1B | |
| | [CC News](https://huggingface.co/datasets/intfloat/multilingual_cc_news) | (title, news content) | 400M | |
| | [NLLB](https://huggingface.co/datasets/allenai/nllb) | translation pairs | 2.4B | |
| | [Wikipedia](https://huggingface.co/datasets/intfloat/wikipedia) | (hierarchical section title, passage) | 150M | |
| | Filtered [Reddit](https://www.reddit.com/) | (comment, response) | 800M | |
| | [S2ORC](https://github.com/allenai/s2orc) | (title, abstract) and citation pairs | 100M | |
| | [Stackexchange](https://stackexchange.com/) | (question, answer) | 50M | |
| | [xP3](https://huggingface.co/datasets/bigscience/xP3) | (input prompt, response) | 80M | |
| | [Miscellaneous unsupervised SBERT data](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) | - | 10M | |
|
|
| **Second stage**: supervised fine-tuning |
|
|
| | Dataset | Language | # of text pairs | |
| |----------------------------------------------------------------------------------------|--------------|-----------------| |
| | [MS MARCO](https://microsoft.github.io/msmarco/) | English | 500k | |
| | [NQ](https://github.com/facebookresearch/DPR) | English | 70k | |
| | [Trivia QA](https://github.com/facebookresearch/DPR) | English | 60k | |
| | [NLI from SimCSE](https://github.com/princeton-nlp/SimCSE) | English | <300k | |
| | [ELI5](https://huggingface.co/datasets/eli5) | English | 500k | |
| | [DuReader Retrieval](https://github.com/baidu/DuReader/tree/master/DuReader-Retrieval) | Chinese | 86k | |
| | [KILT Fever](https://huggingface.co/datasets/kilt_tasks) | English | 70k | |
| | [KILT HotpotQA](https://huggingface.co/datasets/kilt_tasks) | English | 70k | |
| | [SQuAD](https://huggingface.co/datasets/squad) | English | 87k | |
| | [Quora](https://huggingface.co/datasets/quora) | English | 150k | |
| | [Mr. TyDi](https://huggingface.co/datasets/castorini/mr-tydi) | 11 languages | 50k | |
| | [MIRACL](https://huggingface.co/datasets/miracl/miracl) | 16 languages | 40k | |
|
|
| For all labeled datasets, we only use its training set for fine-tuning. |
|
|
| For other training details, please refer to our paper at [https://arxiv.org/pdf/2212.03533.pdf](https://arxiv.org/pdf/2212.03533.pdf). |
|
|
| ## Benchmark Evaluation |
|
|
| Check out [unilm/e5](https://github.com/microsoft/unilm/tree/master/e5) to reproduce evaluation results |
| on the [BEIR](https://arxiv.org/abs/2104.08663) and [MTEB benchmark](https://arxiv.org/abs/2210.07316). |
|
|
| ## Citation |
|
|
| If you find our paper or models helpful, please consider cite as follows: |
|
|
| ``` |
| @article{wang2022text, |
| title={Text Embeddings by Weakly-Supervised Contrastive Pre-training}, |
| author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu}, |
| journal={arXiv preprint arXiv:2212.03533}, |
| year={2022} |
| } |
| ``` |
|
|
| ## Limitations |
|
|
| Long texts will be truncated to at most 512 tokens. |
|
|
|
|
