| --- |
| tags: |
| - mteb |
| model-index: |
| - name: embed-multilingual-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: 77.85074626865672 |
| - type: ap |
| value: 41.53151744002314 |
| - type: f1 |
| value: 71.94656880817726 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_polarity |
| name: MTEB AmazonPolarityClassification |
| config: default |
| split: test |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| metrics: |
| - type: accuracy |
| value: 95.600375 |
| - type: ap |
| value: 93.57882128753579 |
| - type: f1 |
| value: 95.59945484944305 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (en) |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 49.794 |
| - type: f1 |
| value: 48.740439663130985 |
| - task: |
| type: Retrieval |
| dataset: |
| type: arguana |
| name: MTEB ArguAna |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 55.105000000000004 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-p2p |
| name: MTEB ArxivClusteringP2P |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 48.15653426568874 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-s2s |
| name: MTEB ArxivClusteringS2S |
| config: default |
| split: test |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| metrics: |
| - type: v_measure |
| value: 40.78876256237919 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/askubuntudupquestions-reranking |
| name: MTEB AskUbuntuDupQuestions |
| config: default |
| split: test |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| metrics: |
| - type: map |
| value: 62.12873500780318 |
| - type: mrr |
| value: 75.87037769863255 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/biosses-sts |
| name: MTEB BIOSSES |
| config: default |
| split: test |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| metrics: |
| - type: cos_sim_pearson |
| value: 86.01183720167818 |
| - type: cos_sim_spearman |
| value: 85.00916590717613 |
| - type: euclidean_pearson |
| value: 84.072733561361 |
| - type: euclidean_spearman |
| value: 85.00916590717613 |
| - type: manhattan_pearson |
| value: 83.89233507343208 |
| - type: manhattan_spearman |
| value: 84.87482549674115 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/banking77 |
| name: MTEB Banking77Classification |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 86.09415584415584 |
| - type: f1 |
| value: 86.05173549773973 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-p2p |
| name: MTEB BiorxivClusteringP2P |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 40.49773000165541 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-s2s |
| name: MTEB BiorxivClusteringS2S |
| config: default |
| split: test |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| metrics: |
| - type: v_measure |
| value: 36.909633073998876 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackAndroidRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 49.481 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackEnglishRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 47.449999999999996 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackGamingRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 59.227 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackGisRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 37.729 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackMathematicaRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 29.673 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackPhysicsRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 44.278 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackProgrammersRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 43.218 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 40.63741666666667 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackStatsRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 33.341 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackTexRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 29.093999999999998 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackUnixRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 40.801 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackWebmastersRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 40.114 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackWordpressRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 33.243 |
| - task: |
| type: Retrieval |
| dataset: |
| type: climate-fever |
| name: MTEB ClimateFEVER |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 29.958000000000002 |
| - task: |
| type: Retrieval |
| dataset: |
| type: dbpedia-entity |
| name: MTEB DBPedia |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 41.004000000000005 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/emotion |
| name: MTEB EmotionClassification |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 48.150000000000006 |
| - type: f1 |
| value: 43.69803436468346 |
| - task: |
| type: Retrieval |
| dataset: |
| type: fever |
| name: MTEB FEVER |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 88.532 |
| - task: |
| type: Retrieval |
| dataset: |
| type: fiqa |
| name: MTEB FiQA2018 |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 44.105 |
| - task: |
| type: Retrieval |
| dataset: |
| type: hotpotqa |
| name: MTEB HotpotQA |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 70.612 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/imdb |
| name: MTEB ImdbClassification |
| config: default |
| split: test |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| metrics: |
| - type: accuracy |
| value: 93.9672 |
| - type: ap |
| value: 90.72947025321227 |
| - type: f1 |
| value: 93.96271599852622 |
| - task: |
| type: Retrieval |
| dataset: |
| type: msmarco |
| name: MTEB MSMARCO |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 43.447 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (en) |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 94.92476060191517 |
| - type: f1 |
| value: 94.69383758972194 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (en) |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 78.8873689010488 |
| - type: f1 |
| value: 62.537485052253885 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (en) |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 74.51244115669132 |
| - type: f1 |
| value: 72.40074466830153 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (en) |
| config: en |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 79.00470746469401 |
| - type: f1 |
| value: 79.03758200183096 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-p2p |
| name: MTEB MedrxivClusteringP2P |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 36.183215937303736 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-s2s |
| name: MTEB MedrxivClusteringS2S |
| config: default |
| split: test |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| metrics: |
| - type: v_measure |
| value: 33.443759055792135 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/mind_small |
| name: MTEB MindSmallReranking |
| config: default |
| split: test |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| metrics: |
| - type: map |
| value: 32.58713095176127 |
| - type: mrr |
| value: 33.7326038566206 |
| - task: |
| type: Retrieval |
| dataset: |
| type: nfcorpus |
| name: MTEB NFCorpus |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 36.417 |
| - task: |
| type: Retrieval |
| dataset: |
| type: nq |
| name: MTEB NQ |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 63.415 |
| - task: |
| type: Retrieval |
| dataset: |
| type: quora |
| name: MTEB QuoraRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 88.924 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering |
| name: MTEB RedditClustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 58.10997801688676 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering-p2p |
| name: MTEB RedditClusteringP2P |
| config: default |
| split: test |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| metrics: |
| - type: v_measure |
| value: 65.02444843766075 |
| - task: |
| type: Retrieval |
| dataset: |
| type: scidocs |
| name: MTEB SCIDOCS |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 19.339000000000002 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sickr-sts |
| name: MTEB SICK-R |
| config: default |
| split: test |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| metrics: |
| - type: cos_sim_pearson |
| value: 86.61540076033945 |
| - type: cos_sim_spearman |
| value: 82.1820253476181 |
| - type: euclidean_pearson |
| value: 83.73901215845989 |
| - type: euclidean_spearman |
| value: 82.182021064594 |
| - type: manhattan_pearson |
| value: 83.76685139192031 |
| - type: manhattan_spearman |
| value: 82.14074705306663 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts12-sts |
| name: MTEB STS12 |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.62241109228789 |
| - type: cos_sim_spearman |
| value: 77.62042143066208 |
| - type: euclidean_pearson |
| value: 82.77237785274072 |
| - type: euclidean_spearman |
| value: 77.62042142290566 |
| - type: manhattan_pearson |
| value: 82.70945589621266 |
| - type: manhattan_spearman |
| value: 77.57245632826351 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts13-sts |
| name: MTEB STS13 |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 84.8307075352031 |
| - type: cos_sim_spearman |
| value: 85.15620774806095 |
| - type: euclidean_pearson |
| value: 84.21956724564915 |
| - type: euclidean_spearman |
| value: 85.15620774806095 |
| - type: manhattan_pearson |
| value: 84.0677597021641 |
| - type: manhattan_spearman |
| value: 85.02572172855729 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts14-sts |
| name: MTEB STS14 |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 83.33749463516592 |
| - type: cos_sim_spearman |
| value: 80.01967438481185 |
| - type: euclidean_pearson |
| value: 82.16884494022196 |
| - type: euclidean_spearman |
| value: 80.01967218194336 |
| - type: manhattan_pearson |
| value: 81.94431512413773 |
| - type: manhattan_spearman |
| value: 79.81636247503731 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts15-sts |
| name: MTEB STS15 |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 88.2070761097028 |
| - type: cos_sim_spearman |
| value: 88.92297656560552 |
| - type: euclidean_pearson |
| value: 87.95961374550303 |
| - type: euclidean_spearman |
| value: 88.92298798854765 |
| - type: manhattan_pearson |
| value: 87.85515971478168 |
| - type: manhattan_spearman |
| value: 88.8100644762342 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts16-sts |
| name: MTEB STS16 |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.48103354546488 |
| - type: cos_sim_spearman |
| value: 86.91850928862898 |
| - type: euclidean_pearson |
| value: 86.06766986527145 |
| - type: euclidean_spearman |
| value: 86.91850928862898 |
| - type: manhattan_pearson |
| value: 86.02705585360717 |
| - type: manhattan_spearman |
| value: 86.86666545434721 |
| - 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: 90.30267248880148 |
| - type: cos_sim_spearman |
| value: 90.08752166657892 |
| - type: euclidean_pearson |
| value: 90.4697525265135 |
| - type: euclidean_spearman |
| value: 90.08752166657892 |
| - type: manhattan_pearson |
| value: 90.57174978064741 |
| - type: manhattan_spearman |
| value: 90.212834942229 |
| - 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: 67.10616236380835 |
| - type: cos_sim_spearman |
| value: 66.81483164137016 |
| - type: euclidean_pearson |
| value: 68.48505128040803 |
| - type: euclidean_spearman |
| value: 66.81483164137016 |
| - type: manhattan_pearson |
| value: 68.46133268524885 |
| - type: manhattan_spearman |
| value: 66.83684227990202 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/stsbenchmark-sts |
| name: MTEB STSBenchmark |
| config: default |
| split: test |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| metrics: |
| - type: cos_sim_pearson |
| value: 87.12768629069949 |
| - type: cos_sim_spearman |
| value: 88.78683817318573 |
| - type: euclidean_pearson |
| value: 88.47603251297261 |
| - type: euclidean_spearman |
| value: 88.78683817318573 |
| - type: manhattan_pearson |
| value: 88.46483630890225 |
| - type: manhattan_spearman |
| value: 88.76593424921617 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/scidocs-reranking |
| name: MTEB SciDocsRR |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 84.30886658431281 |
| - type: mrr |
| value: 95.5964251797585 |
| - task: |
| type: Retrieval |
| dataset: |
| type: scifact |
| name: MTEB SciFact |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 70.04599999999999 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/sprintduplicatequestions-pairclassification |
| name: MTEB SprintDuplicateQuestions |
| config: default |
| split: test |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 99.87524752475248 |
| - type: cos_sim_ap |
| value: 96.79160651306724 |
| - type: cos_sim_f1 |
| value: 93.57798165137615 |
| - type: cos_sim_precision |
| value: 95.42619542619542 |
| - type: cos_sim_recall |
| value: 91.8 |
| - type: dot_accuracy |
| value: 99.87524752475248 |
| - type: dot_ap |
| value: 96.79160651306724 |
| - type: dot_f1 |
| value: 93.57798165137615 |
| - type: dot_precision |
| value: 95.42619542619542 |
| - type: dot_recall |
| value: 91.8 |
| - type: euclidean_accuracy |
| value: 99.87524752475248 |
| - type: euclidean_ap |
| value: 96.79160651306724 |
| - type: euclidean_f1 |
| value: 93.57798165137615 |
| - type: euclidean_precision |
| value: 95.42619542619542 |
| - type: euclidean_recall |
| value: 91.8 |
| - type: manhattan_accuracy |
| value: 99.87326732673267 |
| - type: manhattan_ap |
| value: 96.7574606340297 |
| - type: manhattan_f1 |
| value: 93.45603271983639 |
| - type: manhattan_precision |
| value: 95.60669456066945 |
| - type: manhattan_recall |
| value: 91.4 |
| - type: max_accuracy |
| value: 99.87524752475248 |
| - type: max_ap |
| value: 96.79160651306724 |
| - type: max_f1 |
| value: 93.57798165137615 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering |
| name: MTEB StackExchangeClustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 68.12288811917144 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering-p2p |
| name: MTEB StackExchangeClusteringP2P |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 35.22267280169542 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/stackoverflowdupquestions-reranking |
| name: MTEB StackOverflowDupQuestions |
| config: default |
| split: test |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| metrics: |
| - type: map |
| value: 52.39780995606098 |
| - type: mrr |
| value: 53.26826563958916 |
| - task: |
| type: Summarization |
| dataset: |
| type: mteb/summeval |
| name: MTEB SummEval |
| config: default |
| split: test |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| metrics: |
| - type: cos_sim_pearson |
| value: 31.15118979569649 |
| - type: cos_sim_spearman |
| value: 30.99428921914572 |
| - type: dot_pearson |
| value: 31.151189338601924 |
| - type: dot_spearman |
| value: 30.99428921914572 |
| - task: |
| type: Retrieval |
| dataset: |
| type: trec-covid |
| name: MTEB TRECCOVID |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 83.372 |
| - task: |
| type: Retrieval |
| dataset: |
| type: webis-touche2020 |
| name: MTEB Touche2020 |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: ndcg_at_10 |
| value: 32.698 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/toxic_conversations_50k |
| name: MTEB ToxicConversationsClassification |
| config: default |
| split: test |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
| metrics: |
| - type: accuracy |
| value: 71.1998 |
| - type: ap |
| value: 14.646205259325157 |
| - type: f1 |
| value: 54.96172518137252 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/tweet_sentiment_extraction |
| name: MTEB TweetSentimentExtractionClassification |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 62.176004527447645 |
| - type: f1 |
| value: 62.48549068096645 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/twentynewsgroups-clustering |
| name: MTEB TwentyNewsgroupsClustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 50.13767789739772 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twittersemeval2015-pairclassification |
| name: MTEB TwitterSemEval2015 |
| config: default |
| split: test |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 86.38016331882935 |
| - type: cos_sim_ap |
| value: 75.1635976260804 |
| - type: cos_sim_f1 |
| value: 69.29936305732484 |
| - type: cos_sim_precision |
| value: 66.99507389162561 |
| - type: cos_sim_recall |
| value: 71.76781002638522 |
| - type: dot_accuracy |
| value: 86.38016331882935 |
| - type: dot_ap |
| value: 75.16359359202374 |
| - type: dot_f1 |
| value: 69.29936305732484 |
| - type: dot_precision |
| value: 66.99507389162561 |
| - type: dot_recall |
| value: 71.76781002638522 |
| - type: euclidean_accuracy |
| value: 86.38016331882935 |
| - type: euclidean_ap |
| value: 75.16360246558416 |
| - type: euclidean_f1 |
| value: 69.29936305732484 |
| - type: euclidean_precision |
| value: 66.99507389162561 |
| - type: euclidean_recall |
| value: 71.76781002638522 |
| - type: manhattan_accuracy |
| value: 86.27883411813792 |
| - type: manhattan_ap |
| value: 75.02872038741897 |
| - type: manhattan_f1 |
| value: 69.29256284011403 |
| - type: manhattan_precision |
| value: 68.07535641547861 |
| - type: manhattan_recall |
| value: 70.55408970976254 |
| - type: max_accuracy |
| value: 86.38016331882935 |
| - type: max_ap |
| value: 75.16360246558416 |
| - type: max_f1 |
| value: 69.29936305732484 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twitterurlcorpus-pairclassification |
| name: MTEB TwitterURLCorpus |
| config: default |
| split: test |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| metrics: |
| - type: cos_sim_accuracy |
| value: 89.39729110878255 |
| - type: cos_sim_ap |
| value: 86.48560260020555 |
| - type: cos_sim_f1 |
| value: 79.35060602690982 |
| - type: cos_sim_precision |
| value: 76.50632549496105 |
| - type: cos_sim_recall |
| value: 82.41453649522637 |
| - type: dot_accuracy |
| value: 89.39729110878255 |
| - type: dot_ap |
| value: 86.48559829915334 |
| - type: dot_f1 |
| value: 79.35060602690982 |
| - type: dot_precision |
| value: 76.50632549496105 |
| - type: dot_recall |
| value: 82.41453649522637 |
| - type: euclidean_accuracy |
| value: 89.39729110878255 |
| - type: euclidean_ap |
| value: 86.48559993122497 |
| - type: euclidean_f1 |
| value: 79.35060602690982 |
| - type: euclidean_precision |
| value: 76.50632549496105 |
| - type: euclidean_recall |
| value: 82.41453649522637 |
| - type: manhattan_accuracy |
| value: 89.36042224550782 |
| - type: manhattan_ap |
| value: 86.47238558562499 |
| - type: manhattan_f1 |
| value: 79.24500641378047 |
| - type: manhattan_precision |
| value: 75.61726236273344 |
| - type: manhattan_recall |
| value: 83.23837388358484 |
| - type: max_accuracy |
| value: 89.39729110878255 |
| - type: max_ap |
| value: 86.48560260020555 |
| - type: max_f1 |
| value: 79.35060602690982 |
| --- |
| |
|
|
| # Cohere embed-multilingual-v3.0 |
|
|
| This repository contains the tokenizer for the Cohere `embed-multilingual-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-multilingual-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-multilingual-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 and nearly 0.5B Non-English training pairs from 100+ languages. |
|
|
| Evaluation results can be found in the [Embed V3.0 Benchmark Results spreadsheet](https://docs.google.com/spreadsheets/d/1w7gnHWMDBdEUrmHgSfDnGHJgVQE5aOiXCCwO3uNH_mI/edit?usp=sharing). |
