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README.md

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+---
+tags:
+- mteb
+model-index:
+- name: embed-english-light-v3.0
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 78.62686567164178
+    - type: ap
+      value: 43.50072127690769
+    - type: f1
+      value: 73.12414870629323
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 94.795
+    - type: ap
+      value: 92.14178233328848
+    - type: f1
+      value: 94.79269356571955
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 51.016000000000005
+    - type: f1
+      value: 48.9266470039522
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 50.806
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 46.19304218375896
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 37.57785041962193
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 60.11396377106911
+    - type: mrr
+      value: 72.9068284746955
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.59354737468067
+    - type: cos_sim_spearman
+      value: 81.71933190993215
+    - type: euclidean_pearson
+      value: 81.39212345994983
+    - type: euclidean_spearman
+      value: 81.71933190993215
+    - type: manhattan_pearson
+      value: 81.29257414603093
+    - type: manhattan_spearman
+      value: 81.80246633432691
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 79.69805194805193
+    - type: f1
+      value: 79.07431143559548
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 38.973417975095934
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 34.51608057107556
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 46.615
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 45.383
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 57.062999999999995
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 37.201
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 27.473
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 41.868
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 42.059000000000005
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 38.885416666666664
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 32.134
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 28.052
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 38.237
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 37.875
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 32.665
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 28.901
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 41.028
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 52.745
+    - type: f1
+      value: 46.432564522368054
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 87.64
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 38.834999999999994
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 66.793
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 92.16680000000001
+    - type: ap
+      value: 88.9326260956379
+    - type: f1
+      value: 92.16197209455585
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 41.325
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 93.62517099863202
+    - type: f1
+      value: 93.3852826127328
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 64.93388052895577
+    - type: f1
+      value: 48.035548201830366
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 70.01344989912577
+    - type: f1
+      value: 68.01236893966525
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 76.34498991257564
+    - type: f1
+      value: 75.72876911765213
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 37.66326759167091
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 33.53562430544494
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 31.86814320224619
+    - type: mrr
+      value: 33.02567757581291
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 33.649
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 57.994
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 88.115
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 53.4970929237201
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 63.59086757472922
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 18.098
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.05019841005287
+    - type: cos_sim_spearman
+      value: 79.65240734965128
+    - type: euclidean_pearson
+      value: 82.33894047327843
+    - type: euclidean_spearman
+      value: 79.65240666088022
+    - type: manhattan_pearson
+      value: 82.33098051639543
+    - type: manhattan_spearman
+      value: 79.5592521956291
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.28561469269728
+    - type: cos_sim_spearman
+      value: 72.6022866501722
+    - type: euclidean_pearson
+      value: 77.89616448619745
+    - type: euclidean_spearman
+      value: 72.6022866429173
+    - type: manhattan_pearson
+      value: 77.9073648819866
+    - type: manhattan_spearman
+      value: 72.6928162672852
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.48271297318195
+    - type: cos_sim_spearman
+      value: 82.87639489647019
+    - type: euclidean_pearson
+      value: 82.24654676315204
+    - type: euclidean_spearman
+      value: 82.87642765399856
+    - type: manhattan_pearson
+      value: 82.19673632886851
+    - type: manhattan_spearman
+      value: 82.822727205448
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.74140104895864
+    - type: cos_sim_spearman
+      value: 79.74024708732993
+    - type: euclidean_pearson
+      value: 82.50081856448949
+    - type: euclidean_spearman
+      value: 79.74024708732993
+    - type: manhattan_pearson
+      value: 82.36588991657912
+    - type: manhattan_spearman
+      value: 79.59022658604357
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.30124436614311
+    - type: cos_sim_spearman
+      value: 86.97688974734349
+    - type: euclidean_pearson
+      value: 86.36868875097032
+    - type: euclidean_spearman
+      value: 86.97688974734349
+    - type: manhattan_pearson
+      value: 86.37787059133234
+    - type: manhattan_spearman
+      value: 86.96666693570158
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.27590066451398
+    - type: cos_sim_spearman
+      value: 84.40811627278994
+    - type: euclidean_pearson
+      value: 83.77341566536141
+    - type: euclidean_spearman
+      value: 84.40811627278994
+    - type: manhattan_pearson
+      value: 83.72567664904311
+    - type: manhattan_spearman
+      value: 84.42172336387632
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 89.13791942173916
+    - type: cos_sim_spearman
+      value: 89.22016928873572
+    - type: euclidean_pearson
+      value: 89.43583792557924
+    - type: euclidean_spearman
+      value: 89.22016928873572
+    - type: manhattan_pearson
+      value: 89.47307915863284
+    - type: manhattan_spearman
+      value: 89.20752264220539
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 64.92003328655028
+    - type: cos_sim_spearman
+      value: 65.42027229611072
+    - type: euclidean_pearson
+      value: 66.68765284942059
+    - type: euclidean_spearman
+      value: 65.42027229611072
+    - type: manhattan_pearson
+      value: 66.85383496796447
+    - type: manhattan_spearman
+      value: 65.53490117706689
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.97445894753297
+    - type: cos_sim_spearman
+      value: 86.57651994952795
+    - type: euclidean_pearson
+      value: 86.7061296897819
+    - type: euclidean_spearman
+      value: 86.57651994952795
+    - type: manhattan_pearson
+      value: 86.66411668551642
+    - type: manhattan_spearman
+      value: 86.53200653755397
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 81.62235389081138
+    - type: mrr
+      value: 94.65811965811966
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 66.687
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.86435643564356
+    - type: cos_sim_ap
+      value: 96.59150882873165
+    - type: cos_sim_f1
+      value: 93.07030854830552
+    - type: cos_sim_precision
+      value: 94.16581371545547
+    - type: cos_sim_recall
+      value: 92.0
+    - type: dot_accuracy
+      value: 99.86435643564356
+    - type: dot_ap
+      value: 96.59150882873165
+    - type: dot_f1
+      value: 93.07030854830552
+    - type: dot_precision
+      value: 94.16581371545547
+    - type: dot_recall
+      value: 92.0
+    - type: euclidean_accuracy
+      value: 99.86435643564356
+    - type: euclidean_ap
+      value: 96.59150882873162
+    - type: euclidean_f1
+      value: 93.07030854830552
+    - type: euclidean_precision
+      value: 94.16581371545547
+    - type: euclidean_recall
+      value: 92.0
+    - type: manhattan_accuracy
+      value: 99.86336633663366
+    - type: manhattan_ap
+      value: 96.58123246795022
+    - type: manhattan_f1
+      value: 92.9591836734694
+    - type: manhattan_precision
+      value: 94.89583333333333
+    - type: manhattan_recall
+      value: 91.10000000000001
+    - type: max_accuracy
+      value: 99.86435643564356
+    - type: max_ap
+      value: 96.59150882873165
+    - type: max_f1
+      value: 93.07030854830552
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 62.938055854344455
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 36.479716154538224
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 50.75827388766867
+    - type: mrr
+      value: 51.65291305916306
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.81419421090782
+    - type: cos_sim_spearman
+      value: 31.287464634068492
+    - type: dot_pearson
+      value: 31.814195589790177
+    - type: dot_spearman
+      value: 31.287464634068492
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 79.364
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: ndcg_at_10
+      value: 31.927
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 73.0414
+    - type: ap
+      value: 16.06723077348852
+    - type: f1
+      value: 56.73470421774399
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 64.72269383135257
+    - type: f1
+      value: 64.70143593421479
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 46.06343037695152
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 85.59337187816654
+    - type: cos_sim_ap
+      value: 72.23331527941706
+    - type: cos_sim_f1
+      value: 67.22915138175593
+    - type: cos_sim_precision
+      value: 62.64813126709207
+    - type: cos_sim_recall
+      value: 72.53298153034301
+    - type: dot_accuracy
+      value: 85.59337187816654
+    - type: dot_ap
+      value: 72.23332517262921
+    - type: dot_f1
+      value: 67.22915138175593
+    - type: dot_precision
+      value: 62.64813126709207
+    - type: dot_recall
+      value: 72.53298153034301
+    - type: euclidean_accuracy
+      value: 85.59337187816654
+    - type: euclidean_ap
+      value: 72.23331029091486
+    - type: euclidean_f1
+      value: 67.22915138175593
+    - type: euclidean_precision
+      value: 62.64813126709207
+    - type: euclidean_recall
+      value: 72.53298153034301
+    - type: manhattan_accuracy
+      value: 85.4622399713894
+    - type: manhattan_ap
+      value: 72.05180729774357
+    - type: manhattan_f1
+      value: 67.12683347713546
+    - type: manhattan_precision
+      value: 62.98866527874162
+    - type: manhattan_recall
+      value: 71.84696569920844
+    - type: max_accuracy
+      value: 85.59337187816654
+    - type: max_ap
+      value: 72.23332517262921
+    - type: max_f1
+      value: 67.22915138175593
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.08681647067955
+    - type: cos_sim_ap
+      value: 86.31913876322757
+    - type: cos_sim_f1
+      value: 78.678007640741
+    - type: cos_sim_precision
+      value: 73.95988616343678
+    - type: cos_sim_recall
+      value: 84.03911302740991
+    - type: dot_accuracy
+      value: 89.08681647067955
+    - type: dot_ap
+      value: 86.31913976395484
+    - type: dot_f1
+      value: 78.678007640741
+    - type: dot_precision
+      value: 73.95988616343678
+    - type: dot_recall
+      value: 84.03911302740991
+    - type: euclidean_accuracy
+      value: 89.08681647067955
+    - type: euclidean_ap
+      value: 86.31913869004254
+    - type: euclidean_f1
+      value: 78.678007640741
+    - type: euclidean_precision
+      value: 73.95988616343678
+    - type: euclidean_recall
+      value: 84.03911302740991
+    - type: manhattan_accuracy
+      value: 89.06547133930997
+    - type: manhattan_ap
+      value: 86.24122868846949
+    - type: manhattan_f1
+      value: 78.74963094183643
+    - type: manhattan_precision
+      value: 75.62375956903884
+    - type: manhattan_recall
+      value: 82.14505697566985
+    - type: max_accuracy
+      value: 89.08681647067955
+    - type: max_ap
+      value: 86.31913976395484
+    - type: max_f1
+      value: 78.74963094183643
+---
+
+
+# Cohere embed-english-light-v3.0
+
+This repository contains the tokenizer for the Cohere `embed-english-light-v3.0` model. See our blogpost [Cohere Embed V3](https://txt.cohere.com/introducing-embed-v3/) for more details on this model.
+
+You can use the embedding model either via the Cohere API, AWS SageMaker or in your private deployments.
+
+## Usage Cohere API
+
+The following code snippet shows the usage of the Cohere API. Install the cohere SDK via:
+```
+pip install -U cohere
+```
+
+Get your free API key on: www.cohere.com
+
+
+```python
+# This snippet shows and example how to use the Cohere Embed V3 models for semantic search.
+# Make sure to have the Cohere SDK in at least v4.30 install: pip install -U cohere 
+# Get your API key from: www.cohere.com
+import cohere
+import numpy as np
+
+cohere_key = "{YOUR_COHERE_API_KEY}"   #Get your API key from www.cohere.com
+co = cohere.Client(cohere_key)
+
+docs = ["The capital of France is Paris",
+        "PyTorch is a machine learning framework based on the Torch library.",
+        "The average cat lifespan is between 13-17 years"]
+
+
+#Encode your documents with input type 'search_document'
+doc_emb = co.embed(docs, input_type="search_document", model="embed-english-light-v3.0").embeddings
+doc_emb = np.asarray(doc_emb)
+
+
+#Encode your query with input type 'search_query'
+query = "What is Pytorch"
+query_emb = co.embed([query], input_type="search_query", model="embed-english-light-v3.0").embeddings
+query_emb = np.asarray(query_emb)
+query_emb.shape
+
+#Compute the dot product between query embedding and document embedding
+scores = np.dot(query_emb, doc_emb.T)[0]
+
+#Find the highest scores
+max_idx = np.argsort(-scores)
+
+print(f"Query: {query}")
+for idx in max_idx:
+  print(f"Score: {scores[idx]:.2f}")
+  print(docs[idx])
+  print("--------")
+```
+
+## Usage AWS SageMaker
+The embedding model can be privately deployed in your AWS Cloud using our [AWS SageMaker marketplace offering](https://aws.amazon.com/marketplace/pp/prodview-z6huxszcqc25i). It runs privately in your VPC, with latencies as low as 5ms for query encoding.
+
+## Usage AWS Bedrock
+Soon the model will also be available via AWS Bedrock. Stay tuned
+
+## Private Deployment
+You want to run the model on your own hardware? [Contact Sales](https://cohere.com/contact-sales) to learn more.
+
+## Supported Languages
+This model was trained on nearly 1B English training pairs. 
+
+Evaluation results can be found in the [Embed V3.0 Benchmark Results spreadsheet](https://docs.google.com/spreadsheets/d/1w7gnHWMDBdEUrmHgSfDnGHJgVQE5aOiXCCwO3uNH_mI/edit?usp=sharing).

added_tokens.json

@@ -0,0 +1,5 @@
+{
+  "[COHERE_CLUSTERING_ID]": 30524,
+  "[COHERE_SEARCH_DOCUMENT_ID]": 30522,
+  "[COHERE_SEARCH_QUERY_ID]": 30523
+}

config.json

@@ -0,0 +1,4 @@
+{
+	"n_positions": 512,
+	"hidden_dim": 384
+}

special_tokens_map.json

@@ -0,0 +1,7 @@
+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

@@ -0,0 +1,19 @@
+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "max_length": null,
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}