diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -1,109 +1,20 @@ --- -language: -- multilingual -- af -- am -- ar -- as -- az -- be -- bg -- bn -- br -- bs -- ca -- cs -- cy -- da -- de -- el -- en -- eo -- es -- et -- eu -- fa -- fi -- fr -- fy -- ga -- gd -- gl -- gu -- ha -- he -- hi -- hr -- hu -- hy -- id -- is -- it -- ja -- jv -- ka -- kk -- km -- kn -- ko -- ku -- ky -- la -- lo -- lt -- lv -- mg -- mk -- ml -- mn -- mr -- ms -- my -- ne -- nl -- 'no' -- om -- or -- pa -- pl -- ps -- pt -- ro -- ru -- sa -- sd -- si -- sk -- sl -- so -- sq -- sr -- su -- sv -- sw -- ta -- te -- th -- tl -- tr -- ug -- uk -- ur -- uz -- vi -- xh -- yi -- zh -license: mit +tags: +- mteb +- Sentence Transformers +- sentence-similarity +- sentence-transformers model-index: -- name: intfloat/multilingual-e5-small +- name: multilingual-e5-small results: - - dataset: - config: en + - task: + type: Classification + dataset: + type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) - revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + config: en split: test - type: mteb/amazon_counterfactual + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 73.79104477611939 @@ -111,14 +22,14 @@ model-index: value: 36.9996434842022 - type: f1 value: 67.95453679103099 - task: + - task: type: Classification - - dataset: - config: de + dataset: + type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (de) - revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + config: de split: test - type: mteb/amazon_counterfactual + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 71.64882226980728 @@ -126,14 +37,14 @@ model-index: value: 82.11942130026586 - type: f1 value: 69.87963421606715 - task: + - task: type: Classification - - dataset: - config: en-ext + dataset: + type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en-ext) - revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + config: en-ext split: test - type: mteb/amazon_counterfactual + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 75.8095952023988 @@ -141,14 +52,14 @@ model-index: value: 24.46869495579561 - type: f1 value: 63.00108480037597 - task: + - task: type: Classification - - dataset: - config: ja + dataset: + type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (ja) - revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + config: ja split: test - type: mteb/amazon_counterfactual + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 64.186295503212 @@ -156,14 +67,14 @@ model-index: value: 15.496804690197042 - type: f1 value: 52.07153895475031 - task: + - task: type: Classification - - dataset: - config: default + dataset: + type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification - revision: e2d317d38cd51312af73b3d32a06d1a08b442046 + config: default split: test - type: mteb/amazon_polarity + revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 88.699325 @@ -171,92 +82,92 @@ model-index: value: 85.27039559917269 - type: f1 value: 88.65556295032513 - task: + - task: type: Classification - - dataset: - config: en + dataset: + type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) - revision: 1399c76144fd37290681b995c656ef9b2e06e26d + config: en split: test - type: mteb/amazon_reviews_multi + revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 44.69799999999999 - type: f1 value: 43.73187348654165 - task: + - task: type: Classification - - dataset: - config: de + dataset: + type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (de) - revision: 1399c76144fd37290681b995c656ef9b2e06e26d + config: de split: test - type: mteb/amazon_reviews_multi + revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 40.245999999999995 - type: f1 value: 39.3863530637684 - task: + - task: type: Classification - - dataset: - config: es + dataset: + type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (es) - revision: 1399c76144fd37290681b995c656ef9b2e06e26d + config: es split: test - type: mteb/amazon_reviews_multi + revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 40.394 - type: f1 value: 39.301223469483446 - task: + - task: type: Classification - - dataset: - config: fr + dataset: + type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (fr) - revision: 1399c76144fd37290681b995c656ef9b2e06e26d + config: fr split: test - type: mteb/amazon_reviews_multi + revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 38.864 - type: f1 value: 37.97974261868003 - task: + - task: type: Classification - - dataset: - config: ja + dataset: + type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (ja) - revision: 1399c76144fd37290681b995c656ef9b2e06e26d + config: ja split: test - type: mteb/amazon_reviews_multi + revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 37.682 - type: f1 value: 37.07399369768313 - task: + - task: type: Classification - - dataset: - config: zh + dataset: + type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (zh) - revision: 1399c76144fd37290681b995c656ef9b2e06e26d + config: zh split: test - type: mteb/amazon_reviews_multi + revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 37.504 - type: f1 value: 36.62317273874278 - task: - type: Classification - - dataset: - config: default + - task: + type: Retrieval + dataset: + type: arguana name: MTEB ArguAna - revision: None + config: default split: test - type: arguana + revision: None metrics: - type: map_at_1 value: 19.061 @@ -318,49 +229,49 @@ model-index: value: 38.122 - type: recall_at_5 value: 47.155 - task: - type: Retrieval - - dataset: - config: default + - task: + type: Clustering + dataset: + type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P - revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d + config: default split: test - type: mteb/arxiv-clustering-p2p + revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 39.22266660528253 - task: + - task: type: Clustering - - dataset: - config: default + dataset: + type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S - revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 + config: default split: test - type: mteb/arxiv-clustering-s2s + revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 30.79980849482483 - task: - type: Clustering - - dataset: - config: default + - task: + type: Reranking + dataset: + type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions - revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 + config: default split: test - type: mteb/askubuntudupquestions-reranking + revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 57.8790068352054 - type: mrr value: 71.78791276436706 - task: - type: Reranking - - dataset: - config: default + - task: + type: STS + dataset: + type: mteb/biosses-sts name: MTEB BIOSSES - revision: d3fb88f8f02e40887cd149695127462bbcf29b4a + config: default split: test - type: mteb/biosses-sts + revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 82.36328364043163 @@ -374,14 +285,14 @@ model-index: value: 80.14484480692127 - type: manhattan_spearman value: 80.39279565980743 - task: - type: STS - - dataset: - config: de-en + - task: + type: BitextMining + dataset: + type: mteb/bucc-bitext-mining name: MTEB BUCC (de-en) - revision: d51519689f32196a32af33b075a01d0e7c51e252 + config: de-en split: test - type: mteb/bucc-bitext-mining + revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 98.0375782881002 @@ -391,14 +302,14 @@ model-index: value: 97.77139874739039 - type: recall value: 98.0375782881002 - task: + - task: type: BitextMining - - dataset: - config: fr-en + dataset: + type: mteb/bucc-bitext-mining name: MTEB BUCC (fr-en) - revision: d51519689f32196a32af33b075a01d0e7c51e252 + config: fr-en split: test - type: mteb/bucc-bitext-mining + revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 93.35241030156286 @@ -408,14 +319,14 @@ model-index: value: 92.3306919069631 - type: recall value: 93.35241030156286 - task: + - task: type: BitextMining - - dataset: - config: ru-en + dataset: + type: mteb/bucc-bitext-mining name: MTEB BUCC (ru-en) - revision: d51519689f32196a32af33b075a01d0e7c51e252 + config: ru-en split: test - type: mteb/bucc-bitext-mining + revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 94.0699688257707 @@ -425,14 +336,14 @@ model-index: value: 93.22791825424315 - type: recall value: 94.0699688257707 - task: + - task: type: BitextMining - - dataset: - config: zh-en + dataset: + type: mteb/bucc-bitext-mining name: MTEB BUCC (zh-en) - revision: d51519689f32196a32af33b075a01d0e7c51e252 + config: zh-en split: test - type: mteb/bucc-bitext-mining + revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 89.25750394944708 @@ -442,49 +353,49 @@ model-index: value: 88.57293312269616 - type: recall value: 89.25750394944708 - task: - type: BitextMining - - dataset: - config: default + - task: + type: Classification + dataset: + type: mteb/banking77 name: MTEB Banking77Classification - revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 + config: default split: test - type: mteb/banking77 + revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 79.41558441558442 - type: f1 value: 79.25886487487219 - task: - type: Classification - - dataset: - config: default + - task: + type: Clustering + dataset: + type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P - revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 + config: default split: test - type: mteb/biorxiv-clustering-p2p + revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 35.747820820329736 - task: + - task: type: Clustering - - dataset: - config: default + dataset: + type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S - revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 + config: default split: test - type: mteb/biorxiv-clustering-s2s + revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 27.045143830596146 - task: - type: Clustering - - dataset: - config: default + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval - revision: None + config: default split: test - type: BeIR/cqadupstack + revision: None metrics: - type: map_at_1 value: 24.252999999999997 @@ -546,14 +457,14 @@ model-index: value: 34.71941666666666 - type: recall_at_5 value: 39.46358333333333 - task: + - task: type: Retrieval - - dataset: - config: default + dataset: + type: climate-fever name: MTEB ClimateFEVER - revision: None + config: default split: test - type: climate-fever + revision: None metrics: - type: map_at_1 value: 9.024000000000001 @@ -615,14 +526,14 @@ model-index: value: 16.768 - type: recall_at_5 value: 20.737 - task: + - task: type: Retrieval - - dataset: - config: default + dataset: + type: dbpedia-entity name: MTEB DBPedia - revision: None + config: default split: test - type: dbpedia-entity + revision: None metrics: - type: map_at_1 value: 8.012 @@ -684,27 +595,27 @@ model-index: value: 14.043 - type: recall_at_5 value: 17.124 - task: - type: Retrieval - - dataset: - config: default + - task: + type: Classification + dataset: + type: mteb/emotion name: MTEB EmotionClassification - revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 + config: default split: test - type: mteb/emotion + revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 42.455 - type: f1 value: 37.59462649781862 - task: - type: Classification - - dataset: - config: default + - task: + type: Retrieval + dataset: + type: fever name: MTEB FEVER - revision: None + config: default split: test - type: fever + revision: None metrics: - type: map_at_1 value: 58.092 @@ -766,14 +677,14 @@ model-index: value: 78.45 - type: recall_at_5 value: 84.316 - task: + - task: type: Retrieval - - dataset: - config: default + dataset: + type: fiqa name: MTEB FiQA2018 - revision: None + config: default split: test - type: fiqa + revision: None metrics: - type: map_at_1 value: 16.649 @@ -835,14 +746,14 @@ model-index: value: 27.914 - type: recall_at_5 value: 33.289 - task: + - task: type: Retrieval - - dataset: - config: default + dataset: + type: hotpotqa name: MTEB HotpotQA - revision: None + config: default split: test - type: hotpotqa + revision: None metrics: - type: map_at_1 value: 36.253 @@ -904,14 +815,14 @@ model-index: value: 57.535000000000004 - type: recall_at_5 value: 63.282000000000004 - task: - type: Retrieval - - dataset: - config: default + - task: + type: Classification + dataset: + type: mteb/imdb name: MTEB ImdbClassification - revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 + config: default split: test - type: mteb/imdb + revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 80.82239999999999 @@ -919,14 +830,14 @@ model-index: value: 75.65895781725314 - type: f1 value: 80.75880969095746 - task: - type: Classification - - dataset: - config: default + - task: + type: Retrieval + dataset: + type: msmarco name: MTEB MSMARCO - revision: None + config: default split: dev - type: msmarco + revision: None metrics: - type: map_at_1 value: 21.624 @@ -988,1539 +899,1531 @@ model-index: value: 41.099999999999994 - type: recall_at_5 value: 50.381 - task: - type: Retrieval - - dataset: - config: en + - task: + type: Classification + dataset: + type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) - revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + config: en split: test - type: mteb/mtop_domain + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 91.06703146374831 - type: f1 value: 90.86867815863172 - task: + - task: type: Classification - - dataset: - config: de + dataset: + type: mteb/mtop_domain name: MTEB MTOPDomainClassification (de) - revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + config: de split: test - type: mteb/mtop_domain + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 87.46970977740209 - type: f1 value: 86.36832872036588 - task: + - task: type: Classification - - dataset: - config: es + dataset: + type: mteb/mtop_domain name: MTEB MTOPDomainClassification (es) - revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + config: es split: test - type: mteb/mtop_domain + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 89.26951300867245 - type: f1 value: 88.93561193959502 - task: + - task: type: Classification - - dataset: - config: fr + dataset: + type: mteb/mtop_domain name: MTEB MTOPDomainClassification (fr) - revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + config: fr split: test - type: mteb/mtop_domain + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 84.22799874725963 - type: f1 value: 84.30490069236556 - task: + - task: type: Classification - - dataset: - config: hi + dataset: + type: mteb/mtop_domain name: MTEB MTOPDomainClassification (hi) - revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + config: hi split: test - type: mteb/mtop_domain + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 86.02007888131948 - type: f1 value: 85.39376041027991 - task: + - task: type: Classification - - dataset: - config: th + dataset: + type: mteb/mtop_domain name: MTEB MTOPDomainClassification (th) - revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + config: th split: test - type: mteb/mtop_domain + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 85.34900542495481 - type: f1 value: 85.39859673336713 - task: + - task: type: Classification - - dataset: - config: en + dataset: + type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) - revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + config: en split: test - type: mteb/mtop_intent + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 71.078431372549 - type: f1 value: 53.45071102002276 - task: + - task: type: Classification - - dataset: - config: de + dataset: + type: mteb/mtop_intent name: MTEB MTOPIntentClassification (de) - revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + config: de split: test - type: mteb/mtop_intent + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 65.85798816568047 - type: f1 value: 46.53112748993529 - task: + - task: type: Classification - - dataset: - config: es + dataset: + type: mteb/mtop_intent name: MTEB MTOPIntentClassification (es) - revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + config: es split: test - type: mteb/mtop_intent + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 67.96864576384256 - type: f1 value: 45.966703022829506 - task: + - task: type: Classification - - dataset: - config: fr + dataset: + type: mteb/mtop_intent name: MTEB MTOPIntentClassification (fr) - revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + config: fr split: test - type: mteb/mtop_intent + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 61.31537738803633 - type: f1 value: 45.52601712835461 - task: + - task: type: Classification - - dataset: - config: hi + dataset: + type: mteb/mtop_intent name: MTEB MTOPIntentClassification (hi) - revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + config: hi split: test - type: mteb/mtop_intent + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 66.29616349946218 - type: f1 value: 47.24166485726613 - task: + - task: type: Classification - - dataset: - config: th + dataset: + type: mteb/mtop_intent name: MTEB MTOPIntentClassification (th) - revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + config: th split: test - type: mteb/mtop_intent + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 67.51537070524412 - type: f1 value: 49.463476319014276 - task: + - task: type: Classification - - dataset: - config: af + dataset: + type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (af) - revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + config: af split: test - type: mteb/amazon_massive_intent + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 57.06792199058508 - type: f1 value: 54.094921857502285 - task: + - task: type: Classification - - dataset: - config: am + dataset: + type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (am) - revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + config: am split: test - type: mteb/amazon_massive_intent + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 51.960322797579025 - type: f1 value: 48.547371223370945 - task: + - task: type: Classification - - dataset: - config: ar + dataset: + type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ar) - revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + config: ar split: test - type: mteb/amazon_massive_intent + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 54.425016812373904 - type: f1 value: 50.47069202054312 - task: + - task: type: Classification - - dataset: - config: az + dataset: + type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (az) - revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + config: az split: test - type: mteb/amazon_massive_intent + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 59.798251513113655 - type: f1 value: 57.05013069086648 - task: + - task: type: Classification - - dataset: - config: bn + dataset: + type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (bn) - revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + config: bn split: test - type: mteb/amazon_massive_intent + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 59.37794216543376 - type: f1 value: 56.3607992649805 - task: + - task: type: Classification - - dataset: - config: cy + dataset: + type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (cy) - revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + config: cy split: test - 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type: accuracy value: 67.44115669132482 - type: f1 value: 67.92227541674552 - task: + - task: type: Classification - - dataset: - config: zh-CN + dataset: + type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (zh-CN) - revision: 7d571f92784cd94a019292a1f45445077d0ef634 + config: zh-CN split: test - type: mteb/amazon_massive_scenario + revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 74.4687289845326 - type: f1 value: 74.16376793486025 - task: + - task: type: Classification - - dataset: - config: zh-TW + dataset: + type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (zh-TW) - revision: 7d571f92784cd94a019292a1f45445077d0ef634 + config: zh-TW split: test - type: mteb/amazon_massive_scenario + revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 68.31876260928043 - type: f1 value: 68.5246745215607 - task: - type: Classification - - dataset: - config: default + - task: + type: Clustering + dataset: + type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P - revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 + config: default split: test - type: mteb/medrxiv-clustering-p2p + revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 30.90431696479766 - task: + - task: type: Clustering - - dataset: - config: default + dataset: + type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S - revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 + config: default split: test - type: mteb/medrxiv-clustering-s2s + revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 27.259158476693774 - task: - type: Clustering - - dataset: - config: default + - task: + type: Reranking + dataset: + type: mteb/mind_small name: MTEB MindSmallReranking - revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 + config: default split: test - type: mteb/mind_small + revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 30.28445330838555 - type: mrr value: 31.15758529581164 - task: - type: Reranking - - dataset: - config: default + - task: + type: Retrieval + dataset: + type: nfcorpus name: MTEB NFCorpus - revision: None + config: default split: test - type: nfcorpus + revision: None metrics: - type: map_at_1 value: 5.353 @@ -2582,14 +2485,14 @@ model-index: value: 9.792 - type: recall_at_5 value: 11.882 - task: + - task: type: Retrieval - - dataset: - config: default + dataset: + type: nq name: MTEB NQ - revision: None + config: default split: test - type: nq + revision: None metrics: - type: map_at_1 value: 33.852 @@ -2651,14 +2554,14 @@ model-index: value: 56.969 - type: recall_at_5 value: 66.283 - task: + - task: type: Retrieval - - dataset: - config: default + dataset: + type: quora name: MTEB QuoraRetrieval - revision: None + config: default split: test - type: quora + revision: None metrics: - type: map_at_1 value: 69.174 @@ -2720,36 +2623,36 @@ model-index: value: 85.86200000000001 - type: recall_at_5 value: 90.501 - task: - type: Retrieval - - dataset: - config: default + - task: + type: Clustering + dataset: + type: mteb/reddit-clustering name: MTEB RedditClustering - revision: 24640382cdbf8abc73003fb0fa6d111a705499eb + config: default split: test - type: mteb/reddit-clustering + revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 39.13064340585255 - task: + - task: type: Clustering - - dataset: - config: default + dataset: + type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P - revision: 282350215ef01743dc01b456c7f5241fa8937f16 + config: default split: test - type: mteb/reddit-clustering-p2p + revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 58.97884249325877 - task: - type: Clustering - - dataset: - config: default + - task: + type: Retrieval + dataset: + type: scidocs name: MTEB SCIDOCS - revision: None + config: default split: test - type: scidocs + revision: None metrics: - type: map_at_1 value: 3.4680000000000004 @@ -2811,14 +2714,14 @@ model-index: value: 7.483 - type: recall_at_5 value: 10.173 - task: - type: Retrieval - - dataset: - config: default + - task: + type: STS + dataset: + type: mteb/sickr-sts name: MTEB SICK-R - revision: a6ea5a8cab320b040a23452cc28066d9beae2cee + config: default split: test - type: mteb/sickr-sts + revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 83.04084311714061 @@ -2832,14 +2735,14 @@ model-index: value: 80.03105964262431 - type: manhattan_spearman value: 77.22373689514794 - task: + - task: type: STS - - dataset: - config: default + dataset: + type: mteb/sts12-sts name: MTEB STS12 - revision: a0d554a64d88156834ff5ae9920b964011b16384 + config: default split: test - type: mteb/sts12-sts + revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 84.1680158034387 @@ -2853,14 +2756,14 @@ model-index: value: 79.75959151517357 - type: manhattan_spearman value: 75.42330344141912 - task: + - task: type: STS - - dataset: - config: default + dataset: + type: mteb/sts13-sts name: MTEB STS13 - revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca + config: default split: test - type: mteb/sts13-sts + revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 76.48898993209346 @@ -2874,14 +2777,14 @@ model-index: value: 76.6944095091912 - type: manhattan_spearman value: 76.61096912972553 - task: + - task: type: STS - - dataset: - config: default + dataset: + type: mteb/sts14-sts name: MTEB STS14 - revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 + config: default split: test - type: mteb/sts14-sts + revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 77.85082366246944 @@ -2895,14 +2798,14 @@ model-index: value: 77.06193941833494 - type: manhattan_spearman value: 75.31003701700112 - task: + - task: type: STS - - dataset: - config: default + dataset: + type: mteb/sts15-sts name: MTEB STS15 - revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 + config: default split: test - type: mteb/sts15-sts + revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 86.36305246526497 @@ -2916,14 +2819,14 @@ model-index: value: 86.0805106816633 - type: manhattan_spearman value: 86.52798366512229 - task: + - task: type: STS - - dataset: - config: default + dataset: + type: mteb/sts16-sts name: MTEB STS16 - revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 + config: default split: test - type: mteb/sts16-sts + revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 82.18536255599724 @@ -2937,14 +2840,14 @@ model-index: value: 83.11941806582371 - type: manhattan_spearman value: 83.84251281019304 - task: + - task: type: STS - - dataset: - config: ko-ko + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (ko-ko) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: ko-ko split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 78.95816528475514 @@ -2958,14 +2861,14 @@ model-index: value: 78.32367302808157 - type: manhattan_spearman value: 78.90277699624637 - task: + - task: type: STS - - dataset: - config: ar-ar + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (ar-ar) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: ar-ar split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 72.89126914997624 @@ -2979,14 +2882,14 @@ model-index: value: 71.47421463379519 - type: manhattan_spearman value: 73.03383242946575 - task: + - task: type: STS - - dataset: - config: en-ar + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-ar) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: en-ar split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 59.22923684492637 @@ -3000,14 +2903,14 @@ model-index: value: 59.60157142786555 - type: manhattan_spearman value: 59.14069604103739 - task: + - task: type: STS - - dataset: - config: en-de + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-de) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: en-de split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 76.24345978774299 @@ -3021,14 +2924,14 @@ model-index: value: 76.05303324760429 - type: manhattan_spearman value: 76.96353149912348 - task: + - task: type: STS - - dataset: - config: en-en + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-en) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: en-en split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 85.50879160160852 @@ -3042,14 +2945,14 @@ model-index: value: 86.10916255616904 - type: manhattan_spearman value: 86.07346068198953 - task: + - task: type: STS - - dataset: - config: en-tr + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-tr) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: en-tr split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 58.39803698977196 @@ -3063,14 +2966,14 @@ model-index: value: 57.333358138183286 - type: manhattan_spearman value: 54.04614023149965 - task: + - task: type: STS - - dataset: - config: es-en + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (es-en) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: es-en split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 70.98304089637197 @@ -3084,14 +2987,14 @@ model-index: value: 71.21098311547406 - type: manhattan_spearman value: 72.93405764824821 - task: + - task: type: STS - - dataset: - config: es-es + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (es-es) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: es-es split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 85.99792397466308 @@ -3105,14 +3008,14 @@ model-index: value: 85.89570850150801 - type: manhattan_spearman value: 84.95806105313007 - task: + - task: type: STS - - dataset: - config: fr-en + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (fr-en) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: fr-en split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 72.21850322994712 @@ -3126,14 +3029,14 @@ model-index: value: 71.8659633964841 - type: manhattan_spearman value: 71.57817425823303 - task: + - task: type: STS - - dataset: - config: it-en + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (it-en) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: it-en split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 75.80921368595645 @@ -3147,14 +3050,14 @@ model-index: value: 76.13530186637601 - type: manhattan_spearman value: 78.00701437666875 - task: + - task: type: STS - - dataset: - config: nl-en + dataset: + type: mteb/sts17-crosslingual-sts name: MTEB STS17 (nl-en) - revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + config: nl-en split: test - type: mteb/sts17-crosslingual-sts + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 74.74980608267349 @@ -3168,14 +3071,14 @@ model-index: value: 74.62642745918002 - type: manhattan_spearman value: 75.18619716592303 - task: + - task: type: STS - - dataset: - config: en + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: en split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 59.632662289205584 @@ -3189,14 +3092,14 @@ model-index: value: 61.75494698945686 - type: manhattan_spearman value: 60.92726195322362 - task: + - task: type: STS - - dataset: - config: de + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: de split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 45.283470551557244 @@ -3210,14 +3113,14 @@ model-index: value: 41.17482200420659 - type: manhattan_spearman value: 53.82180269276363 - task: + - task: type: STS - - dataset: - config: es + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: es split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 60.5069165306236 @@ -3231,14 +3134,14 @@ model-index: value: 63.59789526178922 - type: manhattan_spearman value: 66.86555009875066 - task: + - task: type: STS - - dataset: - config: pl + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (pl) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: pl split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 28.23026196280264 @@ -3252,14 +3155,14 @@ model-index: value: 17.77134274219677 - type: manhattan_spearman value: 35.98107902846267 - task: + - task: type: STS - - dataset: - config: tr + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (tr) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: tr split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 56.51946541393812 @@ -3273,14 +3176,14 @@ model-index: value: 58.579416468759185 - type: manhattan_spearman value: 62.459738981727 - task: + - task: type: STS - - dataset: - config: ar + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (ar) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: ar split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 48.76009839569795 @@ -3294,41 +3197,35 @@ model-index: value: 50.76220659606342 - type: manhattan_spearman value: 55.517347595391456 - task: + - task: type: STS - - dataset: - config: ru + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (ru) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: ru split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - - type: cosine_pearson - value: 50.724322379215934 - - type: cosine_spearman - value: 59.90449732164651 + - type: cos_sim_pearson + value: 51.232731157702425 + - type: cos_sim_spearman + value: 59.89531877658345 - type: euclidean_pearson - value: 50.227545226784024 + value: 49.937914570348376 - type: euclidean_spearman - value: 59.898906527601085 - - type: main_score - value: 59.90449732164651 + value: 60.220905659334036 - type: manhattan_pearson - value: 50.21762139819405 + value: 50.00987996844193 - type: manhattan_spearman - value: 59.761039813759 - - type: pearson - value: 50.724322379215934 - - type: spearman - value: 59.90449732164651 - task: + value: 60.081341480977926 + - task: type: STS - - dataset: - config: zh + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (zh) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: zh split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 54.717524559088005 @@ -3342,14 +3239,14 @@ model-index: value: 58.78638572916807 - type: manhattan_spearman value: 66.58684161046335 - task: + - task: type: STS - - dataset: - config: fr + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (fr) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: fr split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 73.2962042954962 @@ -3363,14 +3260,14 @@ model-index: value: 75.75565853870485 - type: manhattan_spearman value: 76.90208974949428 - task: + - task: type: STS - - dataset: - config: de-en + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-en) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: de-en split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 54.47396266924846 @@ -3384,14 +3281,14 @@ model-index: value: 54.873172394430995 - type: manhattan_spearman value: 56.58111534551218 - task: + - task: type: STS - - dataset: - config: es-en + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es-en) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: es-en split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 69.87177267688686 @@ -3405,14 +3302,14 @@ model-index: value: 71.38245248369536 - type: manhattan_spearman value: 74.53102232732175 - task: + - task: type: STS - - dataset: - config: it + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (it) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: it split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 72.80225656959544 @@ -3426,14 +3323,14 @@ model-index: value: 73.89679971946774 - type: manhattan_spearman value: 76.60886958161574 - task: + - task: type: STS - - dataset: - config: pl-en + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (pl-en) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: pl-en split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 70.70844249898789 @@ -3447,14 +3344,14 @@ model-index: value: 71.29840508203515 - type: manhattan_spearman value: 71.86264441749513 - task: + - task: type: STS - - dataset: - config: zh-en + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (zh-en) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: zh-en split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 58.647478923935694 @@ -3468,14 +3365,14 @@ model-index: value: 58.59735509491861 - type: manhattan_spearman value: 62.082503844627404 - task: + - task: type: STS - - dataset: - config: es-it + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es-it) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: es-it split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 65.8722516867162 @@ -3489,14 +3386,14 @@ model-index: value: 68.07884688638924 - type: manhattan_spearman value: 72.34210325803069 - task: + - task: type: STS - - dataset: - config: de-fr + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-fr) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: de-fr split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 54.5405814240949 @@ -3510,14 +3407,14 @@ model-index: value: 53.623067729338494 - type: manhattan_spearman value: 58.018756154446926 - task: + - task: type: STS - - dataset: - config: de-pl + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-pl) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: de-pl split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 13.611046866216112 @@ -3531,14 +3428,14 @@ model-index: value: 21.969771178698387 - type: manhattan_spearman value: 32.456985088607475 - task: + - task: type: STS - - dataset: - config: fr-pl + dataset: + type: mteb/sts22-crosslingual-sts name: MTEB STS22 (fr-pl) - revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + config: fr-pl split: test - type: mteb/sts22-crosslingual-sts + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 74.58077407011655 @@ -3552,14 +3449,14 @@ model-index: value: 75.15335973101396 - type: manhattan_spearman value: 84.51542547285167 - task: + - task: type: STS - - dataset: - config: default + dataset: + type: mteb/stsbenchmark-sts name: MTEB STSBenchmark - revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 + config: default split: test - type: mteb/stsbenchmark-sts + revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 82.0739825531578 @@ -3573,27 +3470,27 @@ model-index: value: 83.75323603028978 - type: manhattan_spearman value: 83.89677983727685 - task: - type: STS - - dataset: - config: default + - task: + type: Reranking + dataset: + type: mteb/scidocs-reranking name: MTEB SciDocsRR - revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab + config: default split: test - type: mteb/scidocs-reranking + revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 78.12945623123957 - type: mrr value: 93.87738713719106 - task: - type: Reranking - - dataset: - config: default + - task: + type: Retrieval + dataset: + type: scifact name: MTEB SciFact - revision: None + config: default split: test - type: scifact + revision: None metrics: - type: map_at_1 value: 52.983000000000004 @@ -3655,14 +3552,14 @@ model-index: value: 67.744 - type: recall_at_5 value: 73.433 - task: - type: Retrieval - - dataset: - config: default + - task: + type: PairClassification + dataset: + type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions - revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 + config: default split: test - type: mteb/sprintduplicatequestions-pairclassification + revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.72772277227723 @@ -3710,49 +3607,49 @@ model-index: value: 92.17845897992215 - type: max_f1 value: 85.9746835443038 - task: - type: PairClassification - - dataset: - config: default + - task: + type: Clustering + dataset: + type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering - revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 + config: default split: test - type: mteb/stackexchange-clustering + revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 53.52464042600003 - task: + - task: type: Clustering - - dataset: - config: default + dataset: + type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P - revision: 815ca46b2622cec33ccafc3735d572c266efdb44 + config: default split: test - type: mteb/stackexchange-clustering-p2p + revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 32.071631948736 - task: - type: Clustering - - dataset: - config: default + - task: + type: Reranking + dataset: + type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions - revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 + config: default split: test - type: mteb/stackoverflowdupquestions-reranking + revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 49.19552407604654 - type: mrr value: 49.95269130379425 - task: - type: Reranking - - dataset: - config: default + - task: + type: Summarization + dataset: + type: mteb/summeval name: MTEB SummEval - revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c + config: default split: test - type: mteb/summeval + revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 29.345293033095427 @@ -3762,14 +3659,14 @@ model-index: value: 27.047078008958408 - type: dot_spearman value: 27.75894368380218 - task: - type: Summarization - - dataset: - config: default + - task: + type: Retrieval + dataset: + type: trec-covid name: MTEB TRECCOVID - revision: None + config: default split: test - type: trec-covid + revision: None metrics: - type: map_at_1 value: 0.22 @@ -3831,14 +3728,14 @@ model-index: value: 0.634 - type: recall_at_5 value: 1.051 - task: - type: Retrieval - - dataset: - config: sqi-eng + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (sqi-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: sqi-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 91.0 @@ -3848,14 +3745,14 @@ model-index: value: 87.46166666666667 - type: recall value: 91.0 - task: + - task: type: BitextMining - - dataset: - config: fry-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (fry-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: fry-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 57.22543352601156 @@ -3865,14 +3762,14 @@ model-index: value: 48.8150289017341 - type: recall value: 57.22543352601156 - task: + - task: type: BitextMining - - dataset: - config: kur-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (kur-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: kur-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 46.58536585365854 @@ -3882,14 +3779,14 @@ model-index: value: 37.416085946573745 - type: recall value: 46.58536585365854 - task: + - task: type: BitextMining - - dataset: - config: tur-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tur-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: tur-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 89.7 @@ -3899,14 +3796,14 @@ model-index: value: 85.45333333333332 - type: recall value: 89.7 - task: + - task: type: BitextMining - - dataset: - config: deu-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (deu-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: deu-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 97.39999999999999 @@ -3916,14 +3813,14 @@ model-index: value: 96.2 - type: recall value: 97.39999999999999 - task: + - task: type: BitextMining - - dataset: - config: nld-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (nld-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: nld-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 92.4 @@ -3933,14 +3830,14 @@ model-index: value: 89.31666666666668 - type: recall value: 92.4 - task: + - task: type: BitextMining - - dataset: - config: ron-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ron-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ron-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 86.9 @@ -3950,14 +3847,14 @@ model-index: value: 82.23333333333332 - type: recall value: 86.9 - task: + - task: type: BitextMining - - dataset: - config: ang-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ang-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ang-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 50.0 @@ -3967,14 +3864,14 @@ model-index: value: 39.851634683724235 - type: recall value: 50.0 - task: + - task: type: BitextMining - - dataset: - config: ido-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ido-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ido-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 76.3 @@ -3984,14 +3881,14 @@ model-index: value: 68.68777777777777 - type: recall value: 76.3 - task: + - task: type: BitextMining - - dataset: - config: jav-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (jav-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: jav-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 57.073170731707314 @@ -4001,14 +3898,14 @@ model-index: value: 48.26480836236933 - type: recall value: 57.073170731707314 - task: + - task: type: BitextMining - - dataset: - config: isl-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (isl-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: isl-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 68.2 @@ -4018,14 +3915,14 @@ model-index: value: 59.84964285714286 - type: recall value: 68.2 - task: + - task: type: BitextMining - - dataset: - config: slv-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (slv-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: slv-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 77.52126366950182 @@ -4035,14 +3932,14 @@ model-index: value: 70.92171498003819 - type: recall value: 77.52126366950182 - task: + - task: type: BitextMining - - dataset: - config: cym-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (cym-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: cym-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 70.78260869565217 @@ -4052,14 +3949,14 @@ model-index: value: 63.063067367415194 - type: recall value: 70.78260869565217 - task: + - task: type: BitextMining - - dataset: - config: kaz-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (kaz-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: kaz-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 78.43478260869566 @@ -4069,14 +3966,14 @@ model-index: value: 70.63768115942028 - type: recall value: 78.43478260869566 - task: + - task: type: BitextMining - - dataset: - config: est-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (est-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: est-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 60.9 @@ -4086,14 +3983,14 @@ model-index: value: 53.130476190476195 - type: recall value: 60.9 - task: + - task: type: BitextMining - - dataset: - config: heb-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (heb-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: heb-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 72.89999999999999 @@ -4103,14 +4000,14 @@ model-index: value: 65.82595238095237 - type: recall value: 72.89999999999999 - task: + - task: type: BitextMining - - dataset: - config: gla-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (gla-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: gla-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 46.80337756332931 @@ -4120,14 +4017,14 @@ model-index: value: 36.97101116280851 - type: recall value: 46.80337756332931 - task: + - task: type: BitextMining - - dataset: - config: mar-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (mar-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: mar-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 89.8 @@ -4137,14 +4034,14 @@ model-index: value: 85.375 - type: recall value: 89.8 - task: + - task: type: BitextMining - - dataset: - config: lat-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (lat-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: lat-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 47.199999999999996 @@ -4154,14 +4051,14 @@ model-index: value: 37.561071428571424 - type: recall value: 47.199999999999996 - task: + - task: type: BitextMining - - dataset: - config: bel-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (bel-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: bel-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 87.8 @@ -4171,14 +4068,14 @@ model-index: value: 83.275 - type: recall value: 87.8 - task: + - task: type: BitextMining - - dataset: - config: pms-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (pms-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: pms-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 48.76190476190476 @@ -4188,14 +4085,14 @@ model-index: value: 39.96743626743626 - type: recall value: 48.76190476190476 - task: + - task: type: BitextMining - - dataset: - config: gle-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (gle-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: gle-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 66.10000000000001 @@ -4205,14 +4102,14 @@ model-index: value: 57.150238095238095 - type: recall value: 66.10000000000001 - task: + - task: type: BitextMining - - dataset: - config: pes-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (pes-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: pes-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 87.3 @@ -4222,14 +4119,14 @@ model-index: value: 82.48666666666666 - type: recall value: 87.3 - task: + - task: type: BitextMining - - dataset: - config: nob-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (nob-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: nob-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 90.4 @@ -4239,14 +4136,14 @@ model-index: value: 86.6 - type: recall value: 90.4 - task: + - task: type: BitextMining - - dataset: - config: bul-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (bul-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: bul-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 87.0 @@ -4256,14 +4153,14 @@ model-index: value: 82.36666666666666 - type: recall value: 87.0 - task: + - task: type: BitextMining - - dataset: - config: cbk-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (cbk-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: cbk-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 63.9 @@ -4273,14 +4170,14 @@ model-index: value: 55.50595238095239 - type: recall value: 63.9 - task: + - task: type: BitextMining - - dataset: - config: hun-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (hun-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: hun-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 76.1 @@ -4290,14 +4187,14 @@ model-index: value: 70.04928571428573 - type: recall value: 76.1 - task: + - task: type: BitextMining - - dataset: - config: uig-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (uig-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: uig-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 66.3 @@ -4307,33 +4204,31 @@ model-index: value: 56.62535714285713 - type: recall value: 66.3 - task: + - task: type: BitextMining - - dataset: - config: rus-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (rus-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: rus-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy - value: 92.10000000000001 + value: 90.60000000000001 - type: f1 - value: 89.76666666666667 - - type: main_score - value: 89.76666666666667 + value: 87.96333333333334 - type: precision - value: 88.64999999999999 + value: 86.73333333333333 - type: recall - value: 92.10000000000001 - task: + value: 90.60000000000001 + - task: type: BitextMining - - dataset: - config: spa-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (spa-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: spa-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 93.10000000000001 @@ -4343,14 +4238,14 @@ model-index: value: 90.16666666666666 - type: recall value: 93.10000000000001 - task: + - task: type: BitextMining - - dataset: - config: hye-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (hye-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: hye-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 85.71428571428571 @@ -4360,14 +4255,14 @@ model-index: value: 80.8076626877166 - type: recall value: 85.71428571428571 - task: + - task: type: BitextMining - - dataset: - config: tel-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tel-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: tel-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.88888888888889 @@ -4377,14 +4272,14 @@ model-index: value: 84.43732193732193 - type: recall value: 88.88888888888889 - task: + - task: type: BitextMining - - dataset: - config: afr-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (afr-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: afr-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.5 @@ -4394,14 +4289,14 @@ model-index: value: 84.43333333333332 - type: recall value: 88.5 - task: + - task: type: BitextMining - - dataset: - config: mon-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (mon-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: mon-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 82.72727272727273 @@ -4411,14 +4306,14 @@ model-index: value: 76.18181818181819 - type: recall value: 82.72727272727273 - task: + - task: type: BitextMining - - dataset: - config: arz-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (arz-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: arz-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 61.0062893081761 @@ -4428,14 +4323,14 @@ model-index: value: 52.92112499659669 - type: recall value: 61.0062893081761 - task: + - task: type: BitextMining - - dataset: - config: hrv-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (hrv-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: hrv-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 89.5 @@ -4445,14 +4340,14 @@ model-index: value: 85.69166666666668 - type: recall value: 89.5 - task: + - task: type: BitextMining - - dataset: - config: nov-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (nov-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: nov-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 73.54085603112841 @@ -4462,14 +4357,14 @@ model-index: value: 66.53047989623866 - type: recall value: 73.54085603112841 - task: + - task: type: BitextMining - - dataset: - config: gsw-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (gsw-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: gsw-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 43.58974358974359 @@ -4479,14 +4374,14 @@ model-index: value: 33.81155881155882 - type: recall value: 43.58974358974359 - task: + - task: type: BitextMining - - dataset: - config: nds-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (nds-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: nds-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 59.599999999999994 @@ -4496,14 +4391,14 @@ model-index: value: 50.869166666666665 - type: recall value: 59.599999999999994 - task: + - task: type: BitextMining - - dataset: - config: ukr-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ukr-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ukr-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 85.2 @@ -4513,14 +4408,14 @@ model-index: value: 80.02833333333335 - type: recall value: 85.2 - task: + - task: type: BitextMining - - dataset: - config: uzb-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (uzb-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: uzb-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 63.78504672897196 @@ -4530,14 +4425,14 @@ model-index: value: 55.815809968847354 - type: recall value: 63.78504672897196 - task: + - task: type: BitextMining - - dataset: - config: lit-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (lit-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: lit-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 66.5 @@ -4547,14 +4442,14 @@ model-index: value: 59.622363699102834 - type: recall value: 66.5 - task: + - task: type: BitextMining - - dataset: - config: ina-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ina-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ina-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.6 @@ -4564,14 +4459,14 @@ model-index: value: 84.27916666666665 - type: recall value: 88.6 - task: + - task: type: BitextMining - - dataset: - config: lfn-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (lfn-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: lfn-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 58.699999999999996 @@ -4581,14 +4476,14 @@ model-index: value: 50.63214035964035 - type: recall value: 58.699999999999996 - task: + - task: type: BitextMining - - dataset: - config: zsm-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (zsm-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: zsm-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 92.10000000000001 @@ -4598,14 +4493,14 @@ model-index: value: 89.03333333333333 - type: recall value: 92.10000000000001 - task: + - task: type: BitextMining - - dataset: - config: ita-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ita-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ita-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 90.10000000000001 @@ -4615,14 +4510,14 @@ model-index: value: 86.36166666666668 - type: recall value: 90.10000000000001 - task: + - task: type: BitextMining - - dataset: - config: cmn-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (cmn-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: cmn-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 91.4 @@ -4632,14 +4527,14 @@ model-index: value: 87.71166666666666 - type: recall value: 91.4 - task: + - task: type: BitextMining - - dataset: - config: lvs-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (lvs-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: lvs-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 65.7 @@ -4649,14 +4544,14 @@ model-index: value: 58.71785714285714 - type: recall value: 65.7 - task: + - task: type: BitextMining - - dataset: - config: glg-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (glg-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: glg-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 85.39999999999999 @@ -4666,14 +4561,14 @@ model-index: value: 80.37833333333333 - type: recall value: 85.39999999999999 - task: + - task: type: BitextMining - - dataset: - config: ceb-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ceb-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ceb-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 47.833333333333336 @@ -4683,14 +4578,14 @@ model-index: value: 40.077380952380956 - type: recall value: 47.833333333333336 - task: + - task: type: BitextMining - - dataset: - config: bre-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (bre-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: bre-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 10.4 @@ -4700,14 +4595,14 @@ model-index: value: 7.664597069597071 - type: recall value: 10.4 - task: + - task: type: BitextMining - - dataset: - config: ben-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ben-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ben-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 82.6 @@ -4717,14 +4612,14 @@ model-index: value: 75.57833333333332 - type: recall value: 82.6 - task: + - task: type: BitextMining - - dataset: - config: swg-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (swg-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: swg-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 52.67857142857143 @@ -4734,14 +4629,14 @@ model-index: value: 41.49801587301587 - type: recall value: 52.67857142857143 - task: + - task: type: BitextMining - - dataset: - config: arq-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (arq-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: arq-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 28.3205268935236 @@ -4751,14 +4646,14 @@ model-index: value: 20.685900116470915 - type: recall value: 28.3205268935236 - task: + - task: type: BitextMining - - dataset: - config: kab-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (kab-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: kab-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 22.7 @@ -4768,14 +4663,14 @@ model-index: value: 16.407335164835164 - type: recall value: 22.7 - task: + - task: type: BitextMining - - dataset: - config: fra-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (fra-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: fra-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 92.2 @@ -4785,14 +4680,14 @@ model-index: value: 88.87 - type: recall value: 92.2 - task: + - task: type: BitextMining - - dataset: - config: por-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (por-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: por-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 91.4 @@ -4802,14 +4697,14 @@ model-index: value: 88.21666666666667 - type: recall value: 91.4 - task: + - task: type: BitextMining - - dataset: - config: tat-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tat-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: tat-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 69.19999999999999 @@ -4819,14 +4714,14 @@ model-index: value: 61.14773809523809 - type: recall value: 69.19999999999999 - task: + - task: type: BitextMining - - dataset: - config: oci-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (oci-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: oci-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 48.8 @@ -4836,14 +4731,14 @@ model-index: value: 40.770287114845935 - type: recall value: 48.8 - task: + - task: type: BitextMining - - dataset: - config: pol-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (pol-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: pol-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.8 @@ -4853,14 +4748,14 @@ model-index: value: 84.54166666666666 - type: recall value: 88.8 - task: + - task: type: BitextMining - - dataset: - config: war-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (war-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: war-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 46.6 @@ -4870,14 +4765,14 @@ model-index: value: 38.838223114604695 - type: recall value: 46.6 - task: + - task: type: BitextMining - - dataset: - config: aze-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (aze-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: aze-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 84.0 @@ -4887,14 +4782,14 @@ model-index: value: 78.45333333333333 - type: recall value: 84.0 - task: + - task: type: BitextMining - - dataset: - config: vie-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (vie-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: vie-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 90.5 @@ -4904,14 +4799,14 @@ model-index: value: 86.5 - type: recall value: 90.5 - task: + - task: type: BitextMining - - dataset: - config: nno-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (nno-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: nno-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 74.5 @@ -4921,14 +4816,14 @@ model-index: value: 67.51869047619049 - type: recall value: 74.5 - task: + - task: type: BitextMining - - dataset: - config: cha-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (cha-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: cha-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 32.846715328467155 @@ -4938,14 +4833,14 @@ model-index: value: 26.63451511991658 - type: recall value: 32.846715328467155 - task: + - task: type: BitextMining - - dataset: - config: mhr-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (mhr-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: mhr-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 8.0 @@ -4955,14 +4850,14 @@ model-index: value: 5.544177607179943 - type: recall value: 8.0 - task: + - task: type: BitextMining - - dataset: - config: dan-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (dan-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: dan-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 87.6 @@ -4972,14 +4867,14 @@ model-index: value: 82.91583333333334 - type: recall value: 87.6 - task: + - task: type: BitextMining - - dataset: - config: ell-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ell-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ell-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 87.5 @@ -4989,14 +4884,14 @@ model-index: value: 82.47333333333333 - type: recall value: 87.5 - task: + - task: type: BitextMining - - dataset: - config: amh-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (amh-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: amh-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 80.95238095238095 @@ -5006,14 +4901,14 @@ model-index: value: 74.05753968253967 - type: recall value: 80.95238095238095 - task: + - task: type: BitextMining - - dataset: - config: pam-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (pam-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: pam-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 8.799999999999999 @@ -5023,14 +4918,14 @@ model-index: value: 6.557814916172301 - type: recall value: 8.799999999999999 - task: + - task: type: BitextMining - - dataset: - config: hsb-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (hsb-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: hsb-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 44.099378881987576 @@ -5040,14 +4935,14 @@ model-index: value: 34.69420618488942 - type: recall value: 44.099378881987576 - task: + - task: type: BitextMining - - dataset: - config: srp-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (srp-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: srp-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 84.3 @@ -5057,14 +4952,14 @@ model-index: value: 78.60666666666665 - type: recall value: 84.3 - task: + - task: type: BitextMining - - dataset: - config: epo-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (epo-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: epo-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 92.5 @@ -5074,14 +4969,14 @@ model-index: value: 89.56666666666668 - type: recall value: 92.5 - task: + - task: type: BitextMining - - dataset: - config: kzj-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (kzj-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: kzj-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 10.0 @@ -5091,14 +4986,14 @@ model-index: value: 7.878118605532398 - type: recall value: 10.0 - task: + - task: type: BitextMining - - dataset: - config: awa-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (awa-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: awa-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 79.22077922077922 @@ -5108,14 +5003,14 @@ model-index: value: 72.28715728715729 - type: recall value: 79.22077922077922 - task: + - task: type: BitextMining - - dataset: - config: fao-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (fao-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: fao-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 65.64885496183206 @@ -5125,14 +5020,14 @@ model-index: value: 55.992366412213734 - type: recall value: 65.64885496183206 - task: + - task: type: BitextMining - - dataset: - config: mal-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (mal-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: mal-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 96.06986899563319 @@ -5142,14 +5037,14 @@ model-index: value: 94.15332362930616 - type: recall value: 96.06986899563319 - task: + - task: type: BitextMining - - dataset: - config: ile-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ile-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ile-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 77.2 @@ -5159,14 +5054,14 @@ model-index: value: 69.41000000000001 - type: recall value: 77.2 - task: + - task: type: BitextMining - - dataset: - config: bos-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (bos-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: bos-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 86.4406779661017 @@ -5176,14 +5071,14 @@ model-index: value: 81.74199623352166 - type: recall value: 86.4406779661017 - task: + - task: type: BitextMining - - dataset: - config: cor-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (cor-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: cor-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 8.4 @@ -5193,14 +5088,14 @@ model-index: value: 5.4829865484756795 - type: recall value: 8.4 - task: + - task: type: BitextMining - - dataset: - config: cat-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (cat-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: cat-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 83.5 @@ -5210,14 +5105,14 @@ model-index: value: 78.04837662337664 - type: recall value: 83.5 - task: + - task: type: BitextMining - - dataset: - config: eus-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (eus-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: eus-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 60.4 @@ -5227,14 +5122,14 @@ model-index: value: 52.23242424242424 - type: recall value: 60.4 - task: + - task: type: BitextMining - - dataset: - config: yue-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (yue-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: yue-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 74.9 @@ -5244,14 +5139,14 @@ model-index: value: 67.59873015873016 - type: recall value: 74.9 - task: + - task: type: BitextMining - - dataset: - config: swe-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (swe-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: swe-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.0 @@ -5261,14 +5156,14 @@ model-index: value: 83.66166666666666 - type: recall value: 88.0 - task: + - task: type: BitextMining - - dataset: - config: dtp-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (dtp-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: dtp-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 9.1 @@ -5278,14 +5173,14 @@ model-index: value: 7.370043290043291 - type: recall value: 9.1 - task: + - task: type: BitextMining - - dataset: - config: kat-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (kat-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: kat-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 80.9651474530831 @@ -5295,14 +5190,14 @@ model-index: value: 75.19606398962966 - type: recall value: 80.9651474530831 - task: + - task: type: BitextMining - - dataset: - config: jpn-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (jpn-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: jpn-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 86.9 @@ -5312,14 +5207,14 @@ model-index: value: 82.3120634920635 - type: recall value: 86.9 - task: + - task: type: BitextMining - - dataset: - config: csb-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (csb-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: csb-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 29.64426877470356 @@ -5329,14 +5224,14 @@ model-index: value: 22.506399397703746 - type: recall value: 29.64426877470356 - task: + - task: type: BitextMining - - dataset: - config: xho-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (xho-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: xho-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 70.4225352112676 @@ -5346,14 +5241,14 @@ model-index: value: 59.56572769953053 - type: recall value: 70.4225352112676 - task: + - task: type: BitextMining - - dataset: - config: orv-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (orv-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: orv-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 19.64071856287425 @@ -5363,14 +5258,14 @@ model-index: value: 13.865019261197494 - type: recall value: 19.64071856287425 - task: + - task: type: BitextMining - - dataset: - config: ind-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ind-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ind-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 90.2 @@ -5380,14 +5275,14 @@ model-index: value: 86.70833333333331 - type: recall value: 90.2 - task: + - task: type: BitextMining - - dataset: - config: tuk-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tuk-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: tuk-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 23.15270935960591 @@ -5397,14 +5292,14 @@ model-index: value: 16.982385430661292 - type: recall value: 23.15270935960591 - task: + - task: type: BitextMining - - dataset: - config: max-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (max-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: max-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 55.98591549295775 @@ -5414,14 +5309,14 @@ model-index: value: 47.77864154624717 - type: recall value: 55.98591549295775 - task: + - task: type: BitextMining - - dataset: - config: swh-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (swh-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: swh-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 73.07692307692307 @@ -5431,14 +5326,14 @@ model-index: value: 64.06837606837607 - type: recall value: 73.07692307692307 - task: + - task: type: BitextMining - - dataset: - config: hin-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (hin-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: hin-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 94.89999999999999 @@ -5448,14 +5343,14 @@ model-index: value: 92.43333333333332 - type: recall value: 94.89999999999999 - task: + - task: type: BitextMining - - dataset: - config: dsb-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (dsb-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: dsb-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 37.78705636743215 @@ -5465,14 +5360,14 @@ model-index: value: 29.72264397629742 - type: recall value: 37.78705636743215 - task: + - task: type: BitextMining - - dataset: - config: ber-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ber-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ber-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 21.6 @@ -5482,14 +5377,14 @@ model-index: value: 15.71225147075147 - type: recall value: 21.6 - task: + - task: type: BitextMining - - dataset: - config: tam-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tam-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: tam-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 85.01628664495115 @@ -5499,14 +5394,14 @@ model-index: value: 79.83170466883823 - type: recall value: 85.01628664495115 - task: + - task: type: BitextMining - - dataset: - config: slk-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (slk-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: slk-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 83.39999999999999 @@ -5516,14 +5411,14 @@ model-index: value: 78.48333333333333 - type: recall value: 83.39999999999999 - task: + - task: type: BitextMining - - dataset: - config: tgl-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tgl-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: tgl-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 83.2 @@ -5533,14 +5428,14 @@ model-index: value: 77.58833333333334 - type: recall value: 83.2 - task: + - task: type: BitextMining - - dataset: - config: ast-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ast-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ast-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 75.59055118110236 @@ -5550,14 +5445,14 @@ model-index: value: 70.30183727034121 - type: recall value: 75.59055118110236 - task: + - task: type: BitextMining - - dataset: - config: mkd-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (mkd-eng) - 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type: recall value: 88.0 - task: + - task: type: BitextMining - - dataset: - config: ara-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ara-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: ara-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 77.4 @@ -5652,14 +5547,14 @@ model-index: value: 70.54318181818181 - type: recall value: 77.4 - task: + - task: type: BitextMining - - dataset: - config: kor-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (kor-eng) - revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + config: kor-eng split: test - type: mteb/tatoeba-bitext-mining + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 78.60000000000001 @@ -5669,14 +5564,14 @@ model-index: value: 72.30250000000001 - type: recall value: 78.60000000000001 - task: + - task: type: BitextMining - - dataset: - config: yid-eng + dataset: + type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (yid-eng) - 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value: 1.0 - - type: precision_at_1000 - value: 0.1 - - type: precision_at_20 - value: 4.987 - - type: precision_at_3 - value: 32.658 - - type: precision_at_5 - value: 19.781000000000002 - - type: recall_at_1 - value: 90.802 - - type: recall_at_10 - value: 99.494 - - type: recall_at_100 - value: 100.0 - - type: recall_at_1000 - value: 100.0 - - type: recall_at_20 - value: 99.747 - - type: recall_at_3 - value: 97.975 - - type: recall_at_5 - value: 98.90299999999999 - task: - type: Retrieval -tags: -- mteb -- Sentence Transformers -- sentence-similarity -- sentence-transformers +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 --- +### Optimized and quantized of the original model -## Multilingual-E5-small - -[Multilingual E5 Text Embeddings: A Technical Report](https://arxiv.org/pdf/2402.05672). -Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei, arXiv 2024 - -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']) - -# 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/2402.05672](https://arxiv.org/pdf/2402.05672). - -## Benchmark Results on [Mr. TyDi](https://arxiv.org/abs/2108.08787) - -| Model | Avg MRR@10 | | ar | bn | en | fi | id | ja | ko | ru | sw | te | th | -|-----------------------|------------|-------|------| --- | --- | --- | --- | --- | --- | --- |------| --- | --- | -| BM25 | 33.3 | | 36.7 | 41.3 | 15.1 | 28.8 | 38.2 | 21.7 | 28.1 | 32.9 | 39.6 | 42.4 | 41.7 | -| mDPR | 16.7 | | 26.0 | 25.8 | 16.2 | 11.3 | 14.6 | 18.1 | 21.9 | 18.5 | 7.3 | 10.6 | 13.5 | -| BM25 + mDPR | 41.7 | | 49.1 | 53.5 | 28.4 | 36.5 | 45.5 | 35.5 | 36.2 | 42.7 | 40.5 | 42.0 | 49.2 | -| | | -| multilingual-e5-small | 64.4 | | 71.5 | 66.3 | 54.5 | 57.7 | 63.2 | 55.4 | 54.3 | 60.8 | 65.4 | 89.1 | 70.1 | -| multilingual-e5-base | 65.9 | | 72.3 | 65.0 | 58.5 | 60.8 | 64.9 | 56.6 | 55.8 | 62.7 | 69.0 | 86.6 | 72.7 | -| multilingual-e5-large | **70.5** | | 77.5 | 73.2 | 60.8 | 66.8 | 68.5 | 62.5 | 61.6 | 65.8 | 72.7 | 90.2 | 76.2 | - -## MTEB 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). - -## Support for Sentence Transformers - -Below is an example for usage with sentence_transformers. -```python -from sentence_transformers import SentenceTransformer -model = SentenceTransformer('intfloat/multilingual-e5-small') -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 i s 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or traini ng 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" -] -embeddings = model.encode(input_texts, normalize_embeddings=True) -``` - -Package requirements - -`pip install sentence_transformers~=2.2.2` - -Contributors: [michaelfeil](https://huggingface.co/michaelfeil) - -## FAQ - -**1. Do I need to add the prefix "query: " and "passage: " to input texts?** - -Yes, this is how the model is trained, otherwise you will see a performance degradation. - -Here are some rules of thumb: -- Use "query: " and "passage: " correspondingly for asymmetric tasks such as passage retrieval in open QA, ad-hoc information retrieval. - -- Use "query: " prefix for symmetric tasks such as semantic similarity, bitext mining, paraphrase retrieval. - -- Use "query: " prefix if you want to use embeddings as features, such as linear probing classification, clustering. - -**2. Why are my reproduced results slightly different from reported in the model card?** - -Different versions of `transformers` and `pytorch` could cause negligible but non-zero performance differences. - -**3. Why does the cosine similarity scores distribute around 0.7 to 1.0?** - -This is a known and expected behavior as we use a low temperature 0.01 for InfoNCE contrastive loss. - -For text embedding tasks like text retrieval or semantic similarity, -what matters is the relative order of the scores instead of the absolute values, -so this should not be an issue. - -## Citation - -If you find our paper or models helpful, please consider cite as follows: - -``` -@article{wang2024multilingual, - title={Multilingual E5 Text Embeddings: A Technical Report}, - author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Yang, Linjun and Majumder, Rangan and Wei, Furu}, - journal={arXiv preprint arXiv:2402.05672}, - year={2024} -} -``` - -## Limitations - -Long texts will be truncated to at most 512 tokens. +Optimization format: `ONNX` +Quantization: `int8` +Available at [intfloat/multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small) \ No newline at end of file