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+---
+tags:
+- mteb
+model-index:
+- name: multilingual-e5-base
+ results:
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_counterfactual
+ name: MTEB AmazonCounterfactualClassification (en)
+ config: en
+ split: test
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+ metrics:
+ - type: accuracy
+ value: 78.97014925373135
+ - type: ap
+ value: 43.69351129103008
+ - type: f1
+ value: 73.38075030070492
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_counterfactual
+ name: MTEB AmazonCounterfactualClassification (de)
+ config: de
+ split: test
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+ metrics:
+ - type: accuracy
+ value: 71.7237687366167
+ - type: ap
+ value: 82.22089859962671
+ - type: f1
+ value: 69.95532758884401
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_counterfactual
+ name: MTEB AmazonCounterfactualClassification (en-ext)
+ config: en-ext
+ split: test
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+ metrics:
+ - type: accuracy
+ value: 79.65517241379312
+ - type: ap
+ value: 28.507918657094738
+ - type: f1
+ value: 66.84516013726119
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_counterfactual
+ name: MTEB AmazonCounterfactualClassification (ja)
+ config: ja
+ split: test
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+ metrics:
+ - type: accuracy
+ value: 73.32976445396146
+ - type: ap
+ value: 20.720481637566014
+ - type: f1
+ value: 59.78002763416003
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_polarity
+ name: MTEB AmazonPolarityClassification
+ config: default
+ split: test
+ revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+ metrics:
+ - type: accuracy
+ value: 90.63775
+ - type: ap
+ value: 87.22277903861716
+ - type: f1
+ value: 90.60378636386807
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_reviews_multi
+ name: MTEB AmazonReviewsClassification (en)
+ config: en
+ split: test
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+ metrics:
+ - type: accuracy
+ value: 44.546
+ - type: f1
+ value: 44.05666638370923
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_reviews_multi
+ name: MTEB AmazonReviewsClassification (de)
+ config: de
+ split: test
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+ metrics:
+ - type: accuracy
+ value: 41.828
+ - type: f1
+ value: 41.2710255644252
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_reviews_multi
+ name: MTEB AmazonReviewsClassification (es)
+ config: es
+ split: test
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+ metrics:
+ - type: accuracy
+ value: 40.534
+ - type: f1
+ value: 39.820743174270326
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_reviews_multi
+ name: MTEB AmazonReviewsClassification (fr)
+ config: fr
+ split: test
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+ metrics:
+ - type: accuracy
+ value: 39.684
+ - type: f1
+ value: 39.11052682815307
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_reviews_multi
+ name: MTEB AmazonReviewsClassification (ja)
+ config: ja
+ split: test
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+ metrics:
+ - type: accuracy
+ value: 37.436
+ - type: f1
+ value: 37.07082931930871
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_reviews_multi
+ name: MTEB AmazonReviewsClassification (zh)
+ config: zh
+ split: test
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+ metrics:
+ - type: accuracy
+ value: 37.226000000000006
+ - type: f1
+ value: 36.65372077739185
+ - task:
+ type: Retrieval
+ dataset:
+ type: arguana
+ name: MTEB ArguAna
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 22.831000000000003
+ - type: map_at_10
+ value: 36.42
+ - type: map_at_100
+ value: 37.699
+ - type: map_at_1000
+ value: 37.724000000000004
+ - type: map_at_3
+ value: 32.207
+ - type: map_at_5
+ value: 34.312
+ - type: mrr_at_1
+ value: 23.257
+ - type: mrr_at_10
+ value: 36.574
+ - type: mrr_at_100
+ value: 37.854
+ - type: mrr_at_1000
+ value: 37.878
+ - type: mrr_at_3
+ value: 32.385000000000005
+ - type: mrr_at_5
+ value: 34.48
+ - type: ndcg_at_1
+ value: 22.831000000000003
+ - type: ndcg_at_10
+ value: 44.230000000000004
+ - type: ndcg_at_100
+ value: 49.974000000000004
+ - type: ndcg_at_1000
+ value: 50.522999999999996
+ - type: ndcg_at_3
+ value: 35.363
+ - type: ndcg_at_5
+ value: 39.164
+ - type: precision_at_1
+ value: 22.831000000000003
+ - type: precision_at_10
+ value: 6.935
+ - type: precision_at_100
+ value: 0.9520000000000001
+ - type: precision_at_1000
+ value: 0.099
+ - type: precision_at_3
+ value: 14.841
+ - type: precision_at_5
+ value: 10.754
+ - type: recall_at_1
+ value: 22.831000000000003
+ - type: recall_at_10
+ value: 69.346
+ - type: recall_at_100
+ value: 95.235
+ - type: recall_at_1000
+ value: 99.36
+ - type: recall_at_3
+ value: 44.523
+ - type: recall_at_5
+ value: 53.769999999999996
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/arxiv-clustering-p2p
+ name: MTEB ArxivClusteringP2P
+ config: default
+ split: test
+ revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+ metrics:
+ - type: v_measure
+ value: 40.27789869854063
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/arxiv-clustering-s2s
+ name: MTEB ArxivClusteringS2S
+ config: default
+ split: test
+ revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+ metrics:
+ - type: v_measure
+ value: 35.41979463347428
+ - task:
+ type: Reranking
+ dataset:
+ type: mteb/askubuntudupquestions-reranking
+ name: MTEB AskUbuntuDupQuestions
+ config: default
+ split: test
+ revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+ metrics:
+ - type: map
+ value: 58.22752045109304
+ - type: mrr
+ value: 71.51112430198303
+ - task:
+ type: STS
+ dataset:
+ type: mteb/biosses-sts
+ name: MTEB BIOSSES
+ config: default
+ split: test
+ revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+ metrics:
+ - type: cos_sim_pearson
+ value: 84.71147646622866
+ - type: cos_sim_spearman
+ value: 85.059167046486
+ - type: euclidean_pearson
+ value: 75.88421613600647
+ - type: euclidean_spearman
+ value: 75.12821787150585
+ - type: manhattan_pearson
+ value: 75.22005646957604
+ - type: manhattan_spearman
+ value: 74.42880434453272
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/bucc-bitext-mining
+ name: MTEB BUCC (de-en)
+ config: de-en
+ split: test
+ revision: d51519689f32196a32af33b075a01d0e7c51e252
+ metrics:
+ - type: accuracy
+ value: 99.23799582463465
+ - type: f1
+ value: 99.12665274878218
+ - type: precision
+ value: 99.07098121085595
+ - type: recall
+ value: 99.23799582463465
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/bucc-bitext-mining
+ name: MTEB BUCC (fr-en)
+ config: fr-en
+ split: test
+ revision: d51519689f32196a32af33b075a01d0e7c51e252
+ metrics:
+ - type: accuracy
+ value: 97.88685890380806
+ - type: f1
+ value: 97.59336708489249
+ - type: precision
+ value: 97.44662117543473
+ - type: recall
+ value: 97.88685890380806
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/bucc-bitext-mining
+ name: MTEB BUCC (ru-en)
+ config: ru-en
+ split: test
+ revision: d51519689f32196a32af33b075a01d0e7c51e252
+ metrics:
+ - type: accuracy
+ value: 97.47142362313821
+ - type: f1
+ value: 97.1989377670015
+ - type: precision
+ value: 97.06384944001847
+ - type: recall
+ value: 97.47142362313821
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/bucc-bitext-mining
+ name: MTEB BUCC (zh-en)
+ config: zh-en
+ split: test
+ revision: d51519689f32196a32af33b075a01d0e7c51e252
+ metrics:
+ - type: accuracy
+ value: 98.4728804634018
+ - type: f1
+ value: 98.2973494821836
+ - type: precision
+ value: 98.2095839915745
+ - type: recall
+ value: 98.4728804634018
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/banking77
+ name: MTEB Banking77Classification
+ config: default
+ split: test
+ revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+ metrics:
+ - type: accuracy
+ value: 82.74025974025975
+ - type: f1
+ value: 82.67420447730439
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/biorxiv-clustering-p2p
+ name: MTEB BiorxivClusteringP2P
+ config: default
+ split: test
+ revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+ metrics:
+ - type: v_measure
+ value: 35.0380848063507
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/biorxiv-clustering-s2s
+ name: MTEB BiorxivClusteringS2S
+ config: default
+ split: test
+ revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+ metrics:
+ - type: v_measure
+ value: 29.45956405670166
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackAndroidRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 32.122
+ - type: map_at_10
+ value: 42.03
+ - type: map_at_100
+ value: 43.364000000000004
+ - type: map_at_1000
+ value: 43.474000000000004
+ - type: map_at_3
+ value: 38.804
+ - type: map_at_5
+ value: 40.585
+ - type: mrr_at_1
+ value: 39.914
+ - type: mrr_at_10
+ value: 48.227
+ - type: mrr_at_100
+ value: 49.018
+ - type: mrr_at_1000
+ value: 49.064
+ - type: mrr_at_3
+ value: 45.994
+ - type: mrr_at_5
+ value: 47.396
+ - type: ndcg_at_1
+ value: 39.914
+ - type: ndcg_at_10
+ value: 47.825
+ - type: ndcg_at_100
+ value: 52.852
+ - type: ndcg_at_1000
+ value: 54.891
+ - type: ndcg_at_3
+ value: 43.517
+ - type: ndcg_at_5
+ value: 45.493
+ - type: precision_at_1
+ value: 39.914
+ - type: precision_at_10
+ value: 8.956
+ - type: precision_at_100
+ value: 1.388
+ - type: precision_at_1000
+ value: 0.182
+ - type: precision_at_3
+ value: 20.791999999999998
+ - type: precision_at_5
+ value: 14.821000000000002
+ - type: recall_at_1
+ value: 32.122
+ - type: recall_at_10
+ value: 58.294999999999995
+ - type: recall_at_100
+ value: 79.726
+ - type: recall_at_1000
+ value: 93.099
+ - type: recall_at_3
+ value: 45.017
+ - type: recall_at_5
+ value: 51.002
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackEnglishRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 29.677999999999997
+ - type: map_at_10
+ value: 38.684000000000005
+ - type: map_at_100
+ value: 39.812999999999995
+ - type: map_at_1000
+ value: 39.945
+ - type: map_at_3
+ value: 35.831
+ - type: map_at_5
+ value: 37.446
+ - type: mrr_at_1
+ value: 37.771
+ - type: mrr_at_10
+ value: 44.936
+ - type: mrr_at_100
+ value: 45.583
+ - type: mrr_at_1000
+ value: 45.634
+ - type: mrr_at_3
+ value: 42.771
+ - type: mrr_at_5
+ value: 43.994
+ - type: ndcg_at_1
+ value: 37.771
+ - type: ndcg_at_10
+ value: 44.059
+ - type: ndcg_at_100
+ value: 48.192
+ - type: ndcg_at_1000
+ value: 50.375
+ - type: ndcg_at_3
+ value: 40.172000000000004
+ - type: ndcg_at_5
+ value: 41.899
+ - type: precision_at_1
+ value: 37.771
+ - type: precision_at_10
+ value: 8.286999999999999
+ - type: precision_at_100
+ value: 1.322
+ - type: precision_at_1000
+ value: 0.178
+ - type: precision_at_3
+ value: 19.406000000000002
+ - type: precision_at_5
+ value: 13.745
+ - type: recall_at_1
+ value: 29.677999999999997
+ - type: recall_at_10
+ value: 53.071
+ - type: recall_at_100
+ value: 70.812
+ - type: recall_at_1000
+ value: 84.841
+ - type: recall_at_3
+ value: 41.016000000000005
+ - type: recall_at_5
+ value: 46.22
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackGamingRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 42.675000000000004
+ - type: map_at_10
+ value: 53.93599999999999
+ - type: map_at_100
+ value: 54.806999999999995
+ - type: map_at_1000
+ value: 54.867
+ - type: map_at_3
+ value: 50.934000000000005
+ - type: map_at_5
+ value: 52.583
+ - type: mrr_at_1
+ value: 48.339
+ - type: mrr_at_10
+ value: 57.265
+ - type: mrr_at_100
+ value: 57.873
+ - type: mrr_at_1000
+ value: 57.906
+ - type: mrr_at_3
+ value: 55.193000000000005
+ - type: mrr_at_5
+ value: 56.303000000000004
+ - type: ndcg_at_1
+ value: 48.339
+ - type: ndcg_at_10
+ value: 59.19799999999999
+ - type: ndcg_at_100
+ value: 62.743
+ - type: ndcg_at_1000
+ value: 63.99399999999999
+ - type: ndcg_at_3
+ value: 54.367
+ - type: ndcg_at_5
+ value: 56.548
+ - type: precision_at_1
+ value: 48.339
+ - type: precision_at_10
+ value: 9.216000000000001
+ - type: precision_at_100
+ value: 1.1809999999999998
+ - type: precision_at_1000
+ value: 0.134
+ - type: precision_at_3
+ value: 23.72
+ - type: precision_at_5
+ value: 16.025
+ - type: recall_at_1
+ value: 42.675000000000004
+ - type: recall_at_10
+ value: 71.437
+ - type: recall_at_100
+ value: 86.803
+ - type: recall_at_1000
+ value: 95.581
+ - type: recall_at_3
+ value: 58.434
+ - type: recall_at_5
+ value: 63.754
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackGisRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 23.518
+ - type: map_at_10
+ value: 30.648999999999997
+ - type: map_at_100
+ value: 31.508999999999997
+ - type: map_at_1000
+ value: 31.604
+ - type: map_at_3
+ value: 28.247
+ - type: map_at_5
+ value: 29.65
+ - type: mrr_at_1
+ value: 25.650000000000002
+ - type: mrr_at_10
+ value: 32.771
+ - type: mrr_at_100
+ value: 33.554
+ - type: mrr_at_1000
+ value: 33.629999999999995
+ - type: mrr_at_3
+ value: 30.433
+ - type: mrr_at_5
+ value: 31.812
+ - type: ndcg_at_1
+ value: 25.650000000000002
+ - type: ndcg_at_10
+ value: 34.929
+ - type: ndcg_at_100
+ value: 39.382
+ - type: ndcg_at_1000
+ value: 41.913
+ - type: ndcg_at_3
+ value: 30.292
+ - type: ndcg_at_5
+ value: 32.629999999999995
+ - type: precision_at_1
+ value: 25.650000000000002
+ - type: precision_at_10
+ value: 5.311
+ - type: precision_at_100
+ value: 0.792
+ - type: precision_at_1000
+ value: 0.105
+ - type: precision_at_3
+ value: 12.58
+ - type: precision_at_5
+ value: 8.994
+ - type: recall_at_1
+ value: 23.518
+ - type: recall_at_10
+ value: 46.19
+ - type: recall_at_100
+ value: 67.123
+ - type: recall_at_1000
+ value: 86.442
+ - type: recall_at_3
+ value: 33.678000000000004
+ - type: recall_at_5
+ value: 39.244
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackMathematicaRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 15.891
+ - type: map_at_10
+ value: 22.464000000000002
+ - type: map_at_100
+ value: 23.483
+ - type: map_at_1000
+ value: 23.613
+ - type: map_at_3
+ value: 20.080000000000002
+ - type: map_at_5
+ value: 21.526
+ - type: mrr_at_1
+ value: 20.025000000000002
+ - type: mrr_at_10
+ value: 26.712999999999997
+ - type: mrr_at_100
+ value: 27.650000000000002
+ - type: mrr_at_1000
+ value: 27.737000000000002
+ - type: mrr_at_3
+ value: 24.274
+ - type: mrr_at_5
+ value: 25.711000000000002
+ - type: ndcg_at_1
+ value: 20.025000000000002
+ - type: ndcg_at_10
+ value: 27.028999999999996
+ - type: ndcg_at_100
+ value: 32.064
+ - type: ndcg_at_1000
+ value: 35.188
+ - type: ndcg_at_3
+ value: 22.512999999999998
+ - type: ndcg_at_5
+ value: 24.89
+ - type: precision_at_1
+ value: 20.025000000000002
+ - type: precision_at_10
+ value: 4.776
+ - type: precision_at_100
+ value: 0.8500000000000001
+ - type: precision_at_1000
+ value: 0.125
+ - type: precision_at_3
+ value: 10.531
+ - type: precision_at_5
+ value: 7.811
+ - type: recall_at_1
+ value: 15.891
+ - type: recall_at_10
+ value: 37.261
+ - type: recall_at_100
+ value: 59.12
+ - type: recall_at_1000
+ value: 81.356
+ - type: recall_at_3
+ value: 24.741
+ - type: recall_at_5
+ value: 30.753999999999998
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackPhysicsRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 27.544
+ - type: map_at_10
+ value: 36.283
+ - type: map_at_100
+ value: 37.467
+ - type: map_at_1000
+ value: 37.574000000000005
+ - type: map_at_3
+ value: 33.528999999999996
+ - type: map_at_5
+ value: 35.028999999999996
+ - type: mrr_at_1
+ value: 34.166999999999994
+ - type: mrr_at_10
+ value: 41.866
+ - type: mrr_at_100
+ value: 42.666
+ - type: mrr_at_1000
+ value: 42.716
+ - type: mrr_at_3
+ value: 39.541
+ - type: mrr_at_5
+ value: 40.768
+ - type: ndcg_at_1
+ value: 34.166999999999994
+ - type: ndcg_at_10
+ value: 41.577
+ - type: ndcg_at_100
+ value: 46.687
+ - type: ndcg_at_1000
+ value: 48.967
+ - type: ndcg_at_3
+ value: 37.177
+ - type: ndcg_at_5
+ value: 39.097
+ - type: precision_at_1
+ value: 34.166999999999994
+ - type: precision_at_10
+ value: 7.420999999999999
+ - type: precision_at_100
+ value: 1.165
+ - type: precision_at_1000
+ value: 0.154
+ - type: precision_at_3
+ value: 17.291999999999998
+ - type: precision_at_5
+ value: 12.166
+ - type: recall_at_1
+ value: 27.544
+ - type: recall_at_10
+ value: 51.99399999999999
+ - type: recall_at_100
+ value: 73.738
+ - type: recall_at_1000
+ value: 89.33
+ - type: recall_at_3
+ value: 39.179
+ - type: recall_at_5
+ value: 44.385999999999996
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackProgrammersRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 26.661
+ - type: map_at_10
+ value: 35.475
+ - type: map_at_100
+ value: 36.626999999999995
+ - type: map_at_1000
+ value: 36.741
+ - type: map_at_3
+ value: 32.818000000000005
+ - type: map_at_5
+ value: 34.397
+ - type: mrr_at_1
+ value: 32.647999999999996
+ - type: mrr_at_10
+ value: 40.784
+ - type: mrr_at_100
+ value: 41.602
+ - type: mrr_at_1000
+ value: 41.661
+ - type: mrr_at_3
+ value: 38.68
+ - type: mrr_at_5
+ value: 39.838
+ - type: ndcg_at_1
+ value: 32.647999999999996
+ - type: ndcg_at_10
+ value: 40.697
+ - type: ndcg_at_100
+ value: 45.799
+ - type: ndcg_at_1000
+ value: 48.235
+ - type: ndcg_at_3
+ value: 36.516
+ - type: ndcg_at_5
+ value: 38.515
+ - type: precision_at_1
+ value: 32.647999999999996
+ - type: precision_at_10
+ value: 7.202999999999999
+ - type: precision_at_100
+ value: 1.1360000000000001
+ - type: precision_at_1000
+ value: 0.151
+ - type: precision_at_3
+ value: 17.314
+ - type: precision_at_5
+ value: 12.145999999999999
+ - type: recall_at_1
+ value: 26.661
+ - type: recall_at_10
+ value: 50.995000000000005
+ - type: recall_at_100
+ value: 73.065
+ - type: recall_at_1000
+ value: 89.781
+ - type: recall_at_3
+ value: 39.073
+ - type: recall_at_5
+ value: 44.395
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 25.946583333333333
+ - type: map_at_10
+ value: 33.79725
+ - type: map_at_100
+ value: 34.86408333333333
+ - type: map_at_1000
+ value: 34.9795
+ - type: map_at_3
+ value: 31.259999999999998
+ - type: map_at_5
+ value: 32.71541666666666
+ - type: mrr_at_1
+ value: 30.863749999999996
+ - type: mrr_at_10
+ value: 37.99183333333333
+ - type: mrr_at_100
+ value: 38.790499999999994
+ - type: mrr_at_1000
+ value: 38.85575000000001
+ - type: mrr_at_3
+ value: 35.82083333333333
+ - type: mrr_at_5
+ value: 37.07533333333333
+ - type: ndcg_at_1
+ value: 30.863749999999996
+ - type: ndcg_at_10
+ value: 38.52141666666667
+ - type: ndcg_at_100
+ value: 43.17966666666667
+ - type: ndcg_at_1000
+ value: 45.64608333333333
+ - type: ndcg_at_3
+ value: 34.333000000000006
+ - type: ndcg_at_5
+ value: 36.34975
+ - type: precision_at_1
+ value: 30.863749999999996
+ - type: precision_at_10
+ value: 6.598999999999999
+ - type: precision_at_100
+ value: 1.0502500000000001
+ - type: precision_at_1000
+ value: 0.14400000000000002
+ - type: precision_at_3
+ value: 15.557583333333334
+ - type: precision_at_5
+ value: 11.020000000000001
+ - type: recall_at_1
+ value: 25.946583333333333
+ - type: recall_at_10
+ value: 48.36991666666666
+ - type: recall_at_100
+ value: 69.02408333333334
+ - type: recall_at_1000
+ value: 86.43858333333331
+ - type: recall_at_3
+ value: 36.4965
+ - type: recall_at_5
+ value: 41.76258333333334
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackStatsRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 22.431
+ - type: map_at_10
+ value: 28.889
+ - type: map_at_100
+ value: 29.642000000000003
+ - type: map_at_1000
+ value: 29.742
+ - type: map_at_3
+ value: 26.998
+ - type: map_at_5
+ value: 28.172000000000004
+ - type: mrr_at_1
+ value: 25.307000000000002
+ - type: mrr_at_10
+ value: 31.763
+ - type: mrr_at_100
+ value: 32.443
+ - type: mrr_at_1000
+ value: 32.531
+ - type: mrr_at_3
+ value: 29.959000000000003
+ - type: mrr_at_5
+ value: 31.063000000000002
+ - type: ndcg_at_1
+ value: 25.307000000000002
+ - type: ndcg_at_10
+ value: 32.586999999999996
+ - type: ndcg_at_100
+ value: 36.5
+ - type: ndcg_at_1000
+ value: 39.133
+ - type: ndcg_at_3
+ value: 29.25
+ - type: ndcg_at_5
+ value: 31.023
+ - type: precision_at_1
+ value: 25.307000000000002
+ - type: precision_at_10
+ value: 4.954
+ - type: precision_at_100
+ value: 0.747
+ - type: precision_at_1000
+ value: 0.104
+ - type: precision_at_3
+ value: 12.577
+ - type: precision_at_5
+ value: 8.741999999999999
+ - type: recall_at_1
+ value: 22.431
+ - type: recall_at_10
+ value: 41.134
+ - type: recall_at_100
+ value: 59.28600000000001
+ - type: recall_at_1000
+ value: 78.857
+ - type: recall_at_3
+ value: 31.926
+ - type: recall_at_5
+ value: 36.335
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackTexRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 17.586
+ - type: map_at_10
+ value: 23.304
+ - type: map_at_100
+ value: 24.159
+ - type: map_at_1000
+ value: 24.281
+ - type: map_at_3
+ value: 21.316
+ - type: map_at_5
+ value: 22.383
+ - type: mrr_at_1
+ value: 21.645
+ - type: mrr_at_10
+ value: 27.365000000000002
+ - type: mrr_at_100
+ value: 28.108
+ - type: mrr_at_1000
+ value: 28.192
+ - type: mrr_at_3
+ value: 25.482
+ - type: mrr_at_5
+ value: 26.479999999999997
+ - type: ndcg_at_1
+ value: 21.645
+ - type: ndcg_at_10
+ value: 27.306
+ - type: ndcg_at_100
+ value: 31.496000000000002
+ - type: ndcg_at_1000
+ value: 34.53
+ - type: ndcg_at_3
+ value: 23.73
+ - type: ndcg_at_5
+ value: 25.294
+ - type: precision_at_1
+ value: 21.645
+ - type: precision_at_10
+ value: 4.797
+ - type: precision_at_100
+ value: 0.8059999999999999
+ - type: precision_at_1000
+ value: 0.121
+ - type: precision_at_3
+ value: 10.850999999999999
+ - type: precision_at_5
+ value: 7.736
+ - type: recall_at_1
+ value: 17.586
+ - type: recall_at_10
+ value: 35.481
+ - type: recall_at_100
+ value: 54.534000000000006
+ - type: recall_at_1000
+ value: 76.456
+ - type: recall_at_3
+ value: 25.335
+ - type: recall_at_5
+ value: 29.473
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackUnixRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 25.095
+ - type: map_at_10
+ value: 32.374
+ - type: map_at_100
+ value: 33.537
+ - type: map_at_1000
+ value: 33.634
+ - type: map_at_3
+ value: 30.089
+ - type: map_at_5
+ value: 31.433
+ - type: mrr_at_1
+ value: 29.198
+ - type: mrr_at_10
+ value: 36.01
+ - type: mrr_at_100
+ value: 37.022
+ - type: mrr_at_1000
+ value: 37.083
+ - type: mrr_at_3
+ value: 33.94
+ - type: mrr_at_5
+ value: 35.148
+ - type: ndcg_at_1
+ value: 29.198
+ - type: ndcg_at_10
+ value: 36.729
+ - type: ndcg_at_100
+ value: 42.114000000000004
+ - type: ndcg_at_1000
+ value: 44.592
+ - type: ndcg_at_3
+ value: 32.644
+ - type: ndcg_at_5
+ value: 34.652
+ - type: precision_at_1
+ value: 29.198
+ - type: precision_at_10
+ value: 5.970000000000001
+ - type: precision_at_100
+ value: 0.967
+ - type: precision_at_1000
+ value: 0.129
+ - type: precision_at_3
+ value: 14.396999999999998
+ - type: precision_at_5
+ value: 10.093
+ - type: recall_at_1
+ value: 25.095
+ - type: recall_at_10
+ value: 46.392
+ - type: recall_at_100
+ value: 69.706
+ - type: recall_at_1000
+ value: 87.738
+ - type: recall_at_3
+ value: 35.303000000000004
+ - type: recall_at_5
+ value: 40.441
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackWebmastersRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 26.857999999999997
+ - type: map_at_10
+ value: 34.066
+ - type: map_at_100
+ value: 35.671
+ - type: map_at_1000
+ value: 35.881
+ - type: map_at_3
+ value: 31.304
+ - type: map_at_5
+ value: 32.885
+ - type: mrr_at_1
+ value: 32.411
+ - type: mrr_at_10
+ value: 38.987
+ - type: mrr_at_100
+ value: 39.894
+ - type: mrr_at_1000
+ value: 39.959
+ - type: mrr_at_3
+ value: 36.626999999999995
+ - type: mrr_at_5
+ value: 38.011
+ - type: ndcg_at_1
+ value: 32.411
+ - type: ndcg_at_10
+ value: 39.208
+ - type: ndcg_at_100
+ value: 44.626
+ - type: ndcg_at_1000
+ value: 47.43
+ - type: ndcg_at_3
+ value: 35.091
+ - type: ndcg_at_5
+ value: 37.119
+ - type: precision_at_1
+ value: 32.411
+ - type: precision_at_10
+ value: 7.51
+ - type: precision_at_100
+ value: 1.486
+ - type: precision_at_1000
+ value: 0.234
+ - type: precision_at_3
+ value: 16.14
+ - type: precision_at_5
+ value: 11.976
+ - type: recall_at_1
+ value: 26.857999999999997
+ - type: recall_at_10
+ value: 47.407
+ - type: recall_at_100
+ value: 72.236
+ - type: recall_at_1000
+ value: 90.77
+ - type: recall_at_3
+ value: 35.125
+ - type: recall_at_5
+ value: 40.522999999999996
+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackWordpressRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 21.3
+ - type: map_at_10
+ value: 27.412999999999997
+ - type: map_at_100
+ value: 28.29
+ - type: map_at_1000
+ value: 28.398
+ - type: map_at_3
+ value: 25.169999999999998
+ - type: map_at_5
+ value: 26.496
+ - type: mrr_at_1
+ value: 23.29
+ - type: mrr_at_10
+ value: 29.215000000000003
+ - type: mrr_at_100
+ value: 30.073
+ - type: mrr_at_1000
+ value: 30.156
+ - type: mrr_at_3
+ value: 26.956000000000003
+ - type: mrr_at_5
+ value: 28.38
+ - type: ndcg_at_1
+ value: 23.29
+ - type: ndcg_at_10
+ value: 31.113000000000003
+ - type: ndcg_at_100
+ value: 35.701
+ - type: ndcg_at_1000
+ value: 38.505
+ - type: ndcg_at_3
+ value: 26.727
+ - type: ndcg_at_5
+ value: 29.037000000000003
+ - type: precision_at_1
+ value: 23.29
+ - type: precision_at_10
+ value: 4.787
+ - type: precision_at_100
+ value: 0.763
+ - type: precision_at_1000
+ value: 0.11100000000000002
+ - type: precision_at_3
+ value: 11.091
+ - type: precision_at_5
+ value: 7.985
+ - type: recall_at_1
+ value: 21.3
+ - type: recall_at_10
+ value: 40.782000000000004
+ - type: recall_at_100
+ value: 62.13999999999999
+ - type: recall_at_1000
+ value: 83.012
+ - type: recall_at_3
+ value: 29.131
+ - type: recall_at_5
+ value: 34.624
+ - task:
+ type: Retrieval
+ dataset:
+ type: climate-fever
+ name: MTEB ClimateFEVER
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 9.631
+ - type: map_at_10
+ value: 16.634999999999998
+ - type: map_at_100
+ value: 18.23
+ - type: map_at_1000
+ value: 18.419
+ - type: map_at_3
+ value: 13.66
+ - type: map_at_5
+ value: 15.173
+ - type: mrr_at_1
+ value: 21.368000000000002
+ - type: mrr_at_10
+ value: 31.56
+ - type: mrr_at_100
+ value: 32.58
+ - type: mrr_at_1000
+ value: 32.633
+ - type: mrr_at_3
+ value: 28.241
+ - type: mrr_at_5
+ value: 30.225
+ - type: ndcg_at_1
+ value: 21.368000000000002
+ - type: ndcg_at_10
+ value: 23.855999999999998
+ - type: ndcg_at_100
+ value: 30.686999999999998
+ - type: ndcg_at_1000
+ value: 34.327000000000005
+ - type: ndcg_at_3
+ value: 18.781
+ - type: ndcg_at_5
+ value: 20.73
+ - type: precision_at_1
+ value: 21.368000000000002
+ - type: precision_at_10
+ value: 7.564
+ - type: precision_at_100
+ value: 1.496
+ - type: precision_at_1000
+ value: 0.217
+ - type: precision_at_3
+ value: 13.876
+ - type: precision_at_5
+ value: 11.062
+ - type: recall_at_1
+ value: 9.631
+ - type: recall_at_10
+ value: 29.517
+ - type: recall_at_100
+ value: 53.452
+ - type: recall_at_1000
+ value: 74.115
+ - type: recall_at_3
+ value: 17.605999999999998
+ - type: recall_at_5
+ value: 22.505
+ - task:
+ type: Retrieval
+ dataset:
+ type: dbpedia-entity
+ name: MTEB DBPedia
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 8.885
+ - type: map_at_10
+ value: 18.798000000000002
+ - type: map_at_100
+ value: 26.316
+ - type: map_at_1000
+ value: 27.869
+ - type: map_at_3
+ value: 13.719000000000001
+ - type: map_at_5
+ value: 15.716
+ - type: mrr_at_1
+ value: 66.0
+ - type: mrr_at_10
+ value: 74.263
+ - type: mrr_at_100
+ value: 74.519
+ - type: mrr_at_1000
+ value: 74.531
+ - type: mrr_at_3
+ value: 72.458
+ - type: mrr_at_5
+ value: 73.321
+ - type: ndcg_at_1
+ value: 53.87499999999999
+ - type: ndcg_at_10
+ value: 40.355999999999995
+ - type: ndcg_at_100
+ value: 44.366
+ - type: ndcg_at_1000
+ value: 51.771
+ - type: ndcg_at_3
+ value: 45.195
+ - type: ndcg_at_5
+ value: 42.187000000000005
+ - type: precision_at_1
+ value: 66.0
+ - type: precision_at_10
+ value: 31.75
+ - type: precision_at_100
+ value: 10.11
+ - type: precision_at_1000
+ value: 1.9800000000000002
+ - type: precision_at_3
+ value: 48.167
+ - type: precision_at_5
+ value: 40.050000000000004
+ - type: recall_at_1
+ value: 8.885
+ - type: recall_at_10
+ value: 24.471999999999998
+ - type: recall_at_100
+ value: 49.669000000000004
+ - type: recall_at_1000
+ value: 73.383
+ - type: recall_at_3
+ value: 14.872
+ - type: recall_at_5
+ value: 18.262999999999998
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/emotion
+ name: MTEB EmotionClassification
+ config: default
+ split: test
+ revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+ metrics:
+ - type: accuracy
+ value: 45.18
+ - type: f1
+ value: 40.26878691789978
+ - task:
+ type: Retrieval
+ dataset:
+ type: fever
+ name: MTEB FEVER
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 62.751999999999995
+ - type: map_at_10
+ value: 74.131
+ - type: map_at_100
+ value: 74.407
+ - type: map_at_1000
+ value: 74.423
+ - type: map_at_3
+ value: 72.329
+ - type: map_at_5
+ value: 73.555
+ - type: mrr_at_1
+ value: 67.282
+ - type: mrr_at_10
+ value: 78.292
+ - type: mrr_at_100
+ value: 78.455
+ - type: mrr_at_1000
+ value: 78.458
+ - type: mrr_at_3
+ value: 76.755
+ - type: mrr_at_5
+ value: 77.839
+ - type: ndcg_at_1
+ value: 67.282
+ - type: ndcg_at_10
+ value: 79.443
+ - type: ndcg_at_100
+ value: 80.529
+ - type: ndcg_at_1000
+ value: 80.812
+ - type: ndcg_at_3
+ value: 76.281
+ - type: ndcg_at_5
+ value: 78.235
+ - type: precision_at_1
+ value: 67.282
+ - type: precision_at_10
+ value: 10.078
+ - type: precision_at_100
+ value: 1.082
+ - type: precision_at_1000
+ value: 0.11199999999999999
+ - type: precision_at_3
+ value: 30.178
+ - type: precision_at_5
+ value: 19.232
+ - type: recall_at_1
+ value: 62.751999999999995
+ - type: recall_at_10
+ value: 91.521
+ - type: recall_at_100
+ value: 95.997
+ - type: recall_at_1000
+ value: 97.775
+ - type: recall_at_3
+ value: 83.131
+ - type: recall_at_5
+ value: 87.93299999999999
+ - task:
+ type: Retrieval
+ dataset:
+ type: fiqa
+ name: MTEB FiQA2018
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 18.861
+ - type: map_at_10
+ value: 30.252000000000002
+ - type: map_at_100
+ value: 32.082
+ - type: map_at_1000
+ value: 32.261
+ - type: map_at_3
+ value: 25.909
+ - type: map_at_5
+ value: 28.296
+ - type: mrr_at_1
+ value: 37.346000000000004
+ - type: mrr_at_10
+ value: 45.802
+ - type: mrr_at_100
+ value: 46.611999999999995
+ - type: mrr_at_1000
+ value: 46.659
+ - type: mrr_at_3
+ value: 43.056
+ - type: mrr_at_5
+ value: 44.637
+ - type: ndcg_at_1
+ value: 37.346000000000004
+ - type: ndcg_at_10
+ value: 38.169
+ - type: ndcg_at_100
+ value: 44.864
+ - type: ndcg_at_1000
+ value: 47.974
+ - type: ndcg_at_3
+ value: 33.619
+ - type: ndcg_at_5
+ value: 35.317
+ - type: precision_at_1
+ value: 37.346000000000004
+ - type: precision_at_10
+ value: 10.693999999999999
+ - type: precision_at_100
+ value: 1.775
+ - type: precision_at_1000
+ value: 0.231
+ - type: precision_at_3
+ value: 22.325
+ - type: precision_at_5
+ value: 16.852
+ - type: recall_at_1
+ value: 18.861
+ - type: recall_at_10
+ value: 45.672000000000004
+ - type: recall_at_100
+ value: 70.60499999999999
+ - type: recall_at_1000
+ value: 89.216
+ - type: recall_at_3
+ value: 30.361
+ - type: recall_at_5
+ value: 36.998999999999995
+ - task:
+ type: Retrieval
+ dataset:
+ type: hotpotqa
+ name: MTEB HotpotQA
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 37.852999999999994
+ - type: map_at_10
+ value: 59.961
+ - type: map_at_100
+ value: 60.78
+ - type: map_at_1000
+ value: 60.843
+ - type: map_at_3
+ value: 56.39999999999999
+ - type: map_at_5
+ value: 58.646
+ - type: mrr_at_1
+ value: 75.70599999999999
+ - type: mrr_at_10
+ value: 82.321
+ - type: mrr_at_100
+ value: 82.516
+ - type: mrr_at_1000
+ value: 82.525
+ - type: mrr_at_3
+ value: 81.317
+ - type: mrr_at_5
+ value: 81.922
+ - type: ndcg_at_1
+ value: 75.70599999999999
+ - type: ndcg_at_10
+ value: 68.557
+ - type: ndcg_at_100
+ value: 71.485
+ - type: ndcg_at_1000
+ value: 72.71600000000001
+ - type: ndcg_at_3
+ value: 63.524
+ - type: ndcg_at_5
+ value: 66.338
+ - type: precision_at_1
+ value: 75.70599999999999
+ - type: precision_at_10
+ value: 14.463000000000001
+ - type: precision_at_100
+ value: 1.677
+ - type: precision_at_1000
+ value: 0.184
+ - type: precision_at_3
+ value: 40.806
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+ type: mteb/amazon_massive_scenario
+ name: MTEB MassiveScenarioClassification (zh-TW)
+ config: zh-TW
+ split: test
+ revision: 7d571f92784cd94a019292a1f45445077d0ef634
+ metrics:
+ - type: accuracy
+ value: 70.69266980497646
+ - type: f1
+ value: 70.94103167391192
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/medrxiv-clustering-p2p
+ name: MTEB MedrxivClusteringP2P
+ config: default
+ split: test
+ revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+ metrics:
+ - type: v_measure
+ value: 28.91697191169135
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/medrxiv-clustering-s2s
+ name: MTEB MedrxivClusteringS2S
+ config: default
+ split: test
+ revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+ metrics:
+ - type: v_measure
+ value: 28.434000079573313
+ - task:
+ type: Reranking
+ dataset:
+ type: mteb/mind_small
+ name: MTEB MindSmallReranking
+ config: default
+ split: test
+ revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+ metrics:
+ - type: map
+ value: 30.96683513343383
+ - type: mrr
+ value: 31.967364078714834
+ - task:
+ type: Retrieval
+ dataset:
+ type: nfcorpus
+ name: MTEB NFCorpus
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 5.5280000000000005
+ - type: map_at_10
+ value: 11.793
+ - type: map_at_100
+ value: 14.496999999999998
+ - type: map_at_1000
+ value: 15.783
+ - type: map_at_3
+ value: 8.838
+ - type: map_at_5
+ value: 10.07
+ - type: mrr_at_1
+ value: 43.653
+ - type: mrr_at_10
+ value: 51.531000000000006
+ - type: mrr_at_100
+ value: 52.205
+ - type: mrr_at_1000
+ value: 52.242999999999995
+ - type: mrr_at_3
+ value: 49.431999999999995
+ - type: mrr_at_5
+ value: 50.470000000000006
+ - type: ndcg_at_1
+ value: 42.415000000000006
+ - type: ndcg_at_10
+ value: 32.464999999999996
+ - type: ndcg_at_100
+ value: 28.927999999999997
+ - type: ndcg_at_1000
+ value: 37.629000000000005
+ - type: ndcg_at_3
+ value: 37.845
+ - type: ndcg_at_5
+ value: 35.147
+ - type: precision_at_1
+ value: 43.653
+ - type: precision_at_10
+ value: 23.932000000000002
+ - type: precision_at_100
+ value: 7.17
+ - type: precision_at_1000
+ value: 1.967
+ - type: precision_at_3
+ value: 35.397
+ - type: precision_at_5
+ value: 29.907
+ - type: recall_at_1
+ value: 5.5280000000000005
+ - type: recall_at_10
+ value: 15.568000000000001
+ - type: recall_at_100
+ value: 28.54
+ - type: recall_at_1000
+ value: 59.864
+ - type: recall_at_3
+ value: 9.822000000000001
+ - type: recall_at_5
+ value: 11.726
+ - task:
+ type: Retrieval
+ dataset:
+ type: nq
+ name: MTEB NQ
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 37.041000000000004
+ - type: map_at_10
+ value: 52.664
+ - type: map_at_100
+ value: 53.477
+ - type: map_at_1000
+ value: 53.505
+ - type: map_at_3
+ value: 48.510999999999996
+ - type: map_at_5
+ value: 51.036
+ - type: mrr_at_1
+ value: 41.338
+ - type: mrr_at_10
+ value: 55.071000000000005
+ - type: mrr_at_100
+ value: 55.672
+ - type: mrr_at_1000
+ value: 55.689
+ - type: mrr_at_3
+ value: 51.82
+ - type: mrr_at_5
+ value: 53.852
+ - type: ndcg_at_1
+ value: 41.338
+ - type: ndcg_at_10
+ value: 60.01800000000001
+ - type: ndcg_at_100
+ value: 63.409000000000006
+ - type: ndcg_at_1000
+ value: 64.017
+ - type: ndcg_at_3
+ value: 52.44799999999999
+ - type: ndcg_at_5
+ value: 56.571000000000005
+ - type: precision_at_1
+ value: 41.338
+ - type: precision_at_10
+ value: 9.531
+ - type: precision_at_100
+ value: 1.145
+ - type: precision_at_1000
+ value: 0.12
+ - type: precision_at_3
+ value: 23.416
+ - type: precision_at_5
+ value: 16.46
+ - type: recall_at_1
+ value: 37.041000000000004
+ - type: recall_at_10
+ value: 79.76299999999999
+ - type: recall_at_100
+ value: 94.39
+ - type: recall_at_1000
+ value: 98.851
+ - type: recall_at_3
+ value: 60.465
+ - type: recall_at_5
+ value: 69.906
+ - task:
+ type: Retrieval
+ dataset:
+ type: quora
+ name: MTEB QuoraRetrieval
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 69.952
+ - type: map_at_10
+ value: 83.758
+ - type: map_at_100
+ value: 84.406
+ - type: map_at_1000
+ value: 84.425
+ - type: map_at_3
+ value: 80.839
+ - type: map_at_5
+ value: 82.646
+ - type: mrr_at_1
+ value: 80.62
+ - type: mrr_at_10
+ value: 86.947
+ - type: mrr_at_100
+ value: 87.063
+ - type: mrr_at_1000
+ value: 87.064
+ - type: mrr_at_3
+ value: 85.96000000000001
+ - type: mrr_at_5
+ value: 86.619
+ - type: ndcg_at_1
+ value: 80.63
+ - type: ndcg_at_10
+ value: 87.64800000000001
+ - type: ndcg_at_100
+ value: 88.929
+ - type: ndcg_at_1000
+ value: 89.054
+ - type: ndcg_at_3
+ value: 84.765
+ - type: ndcg_at_5
+ value: 86.291
+ - type: precision_at_1
+ value: 80.63
+ - type: precision_at_10
+ value: 13.314
+ - type: precision_at_100
+ value: 1.525
+ - type: precision_at_1000
+ value: 0.157
+ - type: precision_at_3
+ value: 37.1
+ - type: precision_at_5
+ value: 24.372
+ - type: recall_at_1
+ value: 69.952
+ - type: recall_at_10
+ value: 94.955
+ - type: recall_at_100
+ value: 99.38
+ - type: recall_at_1000
+ value: 99.96000000000001
+ - type: recall_at_3
+ value: 86.60600000000001
+ - type: recall_at_5
+ value: 90.997
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/reddit-clustering
+ name: MTEB RedditClustering
+ config: default
+ split: test
+ revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+ metrics:
+ - type: v_measure
+ value: 42.41329517878427
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/reddit-clustering-p2p
+ name: MTEB RedditClusteringP2P
+ config: default
+ split: test
+ revision: 282350215ef01743dc01b456c7f5241fa8937f16
+ metrics:
+ - type: v_measure
+ value: 55.171278362748666
+ - task:
+ type: Retrieval
+ dataset:
+ type: scidocs
+ name: MTEB SCIDOCS
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 4.213
+ - type: map_at_10
+ value: 9.895
+ - type: map_at_100
+ value: 11.776
+ - type: map_at_1000
+ value: 12.084
+ - type: map_at_3
+ value: 7.2669999999999995
+ - type: map_at_5
+ value: 8.620999999999999
+ - type: mrr_at_1
+ value: 20.8
+ - type: mrr_at_10
+ value: 31.112000000000002
+ - type: mrr_at_100
+ value: 32.274
+ - type: mrr_at_1000
+ value: 32.35
+ - type: mrr_at_3
+ value: 28.133000000000003
+ - type: mrr_at_5
+ value: 29.892999999999997
+ - type: ndcg_at_1
+ value: 20.8
+ - type: ndcg_at_10
+ value: 17.163999999999998
+ - type: ndcg_at_100
+ value: 24.738
+ - type: ndcg_at_1000
+ value: 30.316
+ - type: ndcg_at_3
+ value: 16.665
+ - type: ndcg_at_5
+ value: 14.478
+ - type: precision_at_1
+ value: 20.8
+ - type: precision_at_10
+ value: 8.74
+ - type: precision_at_100
+ value: 1.963
+ - type: precision_at_1000
+ value: 0.33
+ - type: precision_at_3
+ value: 15.467
+ - type: precision_at_5
+ value: 12.6
+ - type: recall_at_1
+ value: 4.213
+ - type: recall_at_10
+ value: 17.698
+ - type: recall_at_100
+ value: 39.838
+ - type: recall_at_1000
+ value: 66.893
+ - type: recall_at_3
+ value: 9.418
+ - type: recall_at_5
+ value: 12.773000000000001
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sickr-sts
+ name: MTEB SICK-R
+ config: default
+ split: test
+ revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+ metrics:
+ - type: cos_sim_pearson
+ value: 82.90453315738294
+ - type: cos_sim_spearman
+ value: 78.51197850080254
+ - type: euclidean_pearson
+ value: 80.09647123597748
+ - type: euclidean_spearman
+ value: 78.63548011514061
+ - type: manhattan_pearson
+ value: 80.10645285675231
+ - type: manhattan_spearman
+ value: 78.57861806068901
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts12-sts
+ name: MTEB STS12
+ config: default
+ split: test
+ revision: a0d554a64d88156834ff5ae9920b964011b16384
+ metrics:
+ - type: cos_sim_pearson
+ value: 84.2616156846401
+ - type: cos_sim_spearman
+ value: 76.69713867850156
+ - type: euclidean_pearson
+ value: 77.97948563800394
+ - type: euclidean_spearman
+ value: 74.2371211567807
+ - type: manhattan_pearson
+ value: 77.69697879669705
+ - type: manhattan_spearman
+ value: 73.86529778022278
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts13-sts
+ name: MTEB STS13
+ config: default
+ split: test
+ revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+ metrics:
+ - type: cos_sim_pearson
+ value: 77.0293269315045
+ - type: cos_sim_spearman
+ value: 78.02555120584198
+ - type: euclidean_pearson
+ value: 78.25398100379078
+ - type: euclidean_spearman
+ value: 78.66963870599464
+ - type: manhattan_pearson
+ value: 78.14314682167348
+ - type: manhattan_spearman
+ value: 78.57692322969135
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts14-sts
+ name: MTEB STS14
+ config: default
+ split: test
+ revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+ metrics:
+ - type: cos_sim_pearson
+ value: 79.16989925136942
+ - type: cos_sim_spearman
+ value: 76.5996225327091
+ - type: euclidean_pearson
+ value: 77.8319003279786
+ - type: euclidean_spearman
+ value: 76.42824009468998
+ - type: manhattan_pearson
+ value: 77.69118862737736
+ - type: manhattan_spearman
+ value: 76.25568104762812
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts15-sts
+ name: MTEB STS15
+ config: default
+ split: test
+ revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+ metrics:
+ - type: cos_sim_pearson
+ value: 87.42012286935325
+ - type: cos_sim_spearman
+ value: 88.15654297884122
+ - type: euclidean_pearson
+ value: 87.34082819427852
+ - type: euclidean_spearman
+ value: 88.06333589547084
+ - type: manhattan_pearson
+ value: 87.25115596784842
+ - type: manhattan_spearman
+ value: 87.9559927695203
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts16-sts
+ name: MTEB STS16
+ config: default
+ split: test
+ revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+ metrics:
+ - type: cos_sim_pearson
+ value: 82.88222044996712
+ - type: cos_sim_spearman
+ value: 84.28476589061077
+ - type: euclidean_pearson
+ value: 83.17399758058309
+ - type: euclidean_spearman
+ value: 83.85497357244542
+ - type: manhattan_pearson
+ value: 83.0308397703786
+ - type: manhattan_spearman
+ value: 83.71554539935046
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (ko-ko)
+ config: ko-ko
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 80.20682986257339
+ - type: cos_sim_spearman
+ value: 79.94567120362092
+ - type: euclidean_pearson
+ value: 79.43122480368902
+ - type: euclidean_spearman
+ value: 79.94802077264987
+ - type: manhattan_pearson
+ value: 79.32653021527081
+ - type: manhattan_spearman
+ value: 79.80961146709178
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (ar-ar)
+ config: ar-ar
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 74.46578144394383
+ - type: cos_sim_spearman
+ value: 74.52496637472179
+ - type: euclidean_pearson
+ value: 72.2903807076809
+ - type: euclidean_spearman
+ value: 73.55549359771645
+ - type: manhattan_pearson
+ value: 72.09324837709393
+ - type: manhattan_spearman
+ value: 73.36743103606581
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (en-ar)
+ config: en-ar
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 71.37272335116
+ - type: cos_sim_spearman
+ value: 71.26702117766037
+ - type: euclidean_pearson
+ value: 67.114829954434
+ - type: euclidean_spearman
+ value: 66.37938893947761
+ - type: manhattan_pearson
+ value: 66.79688574095246
+ - type: manhattan_spearman
+ value: 66.17292828079667
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (en-de)
+ config: en-de
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 80.61016770129092
+ - type: cos_sim_spearman
+ value: 82.08515426632214
+ - type: euclidean_pearson
+ value: 80.557340361131
+ - type: euclidean_spearman
+ value: 80.37585812266175
+ - type: manhattan_pearson
+ value: 80.6782873404285
+ - type: manhattan_spearman
+ value: 80.6678073032024
+ - 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: 87.00150745350108
+ - type: cos_sim_spearman
+ value: 87.83441972211425
+ - type: euclidean_pearson
+ value: 87.94826702308792
+ - type: euclidean_spearman
+ value: 87.46143974860725
+ - type: manhattan_pearson
+ value: 87.97560344306105
+ - type: manhattan_spearman
+ value: 87.5267102829796
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (en-tr)
+ config: en-tr
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 64.76325252267235
+ - type: cos_sim_spearman
+ value: 63.32615095463905
+ - type: euclidean_pearson
+ value: 64.07920669155716
+ - type: euclidean_spearman
+ value: 61.21409893072176
+ - type: manhattan_pearson
+ value: 64.26308625680016
+ - type: manhattan_spearman
+ value: 61.2438185254079
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (es-en)
+ config: es-en
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 75.82644463022595
+ - type: cos_sim_spearman
+ value: 76.50381269945073
+ - type: euclidean_pearson
+ value: 75.1328548315934
+ - type: euclidean_spearman
+ value: 75.63761139408453
+ - type: manhattan_pearson
+ value: 75.18610101241407
+ - type: manhattan_spearman
+ value: 75.30669266354164
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (es-es)
+ config: es-es
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 87.49994164686832
+ - type: cos_sim_spearman
+ value: 86.73743986245549
+ - type: euclidean_pearson
+ value: 86.8272894387145
+ - type: euclidean_spearman
+ value: 85.97608491000507
+ - type: manhattan_pearson
+ value: 86.74960140396779
+ - type: manhattan_spearman
+ value: 85.79285984190273
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (fr-en)
+ config: fr-en
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 79.58172210788469
+ - type: cos_sim_spearman
+ value: 80.17516468334607
+ - type: euclidean_pearson
+ value: 77.56537843470504
+ - type: euclidean_spearman
+ value: 77.57264627395521
+ - type: manhattan_pearson
+ value: 78.09703521695943
+ - type: manhattan_spearman
+ value: 78.15942760916954
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (it-en)
+ config: it-en
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 79.7589932931751
+ - type: cos_sim_spearman
+ value: 80.15210089028162
+ - type: euclidean_pearson
+ value: 77.54135223516057
+ - type: euclidean_spearman
+ value: 77.52697996368764
+ - type: manhattan_pearson
+ value: 77.65734439572518
+ - type: manhattan_spearman
+ value: 77.77702992016121
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (nl-en)
+ config: nl-en
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 79.16682365511267
+ - type: cos_sim_spearman
+ value: 79.25311267628506
+ - type: euclidean_pearson
+ value: 77.54882036762244
+ - type: euclidean_spearman
+ value: 77.33212935194827
+ - type: manhattan_pearson
+ value: 77.98405516064015
+ - type: manhattan_spearman
+ value: 77.85075717865719
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts22-crosslingual-sts
+ name: MTEB STS22 (en)
+ config: en
+ split: test
+ revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+ metrics:
+ - type: cos_sim_pearson
+ value: 59.10473294775917
+ - type: cos_sim_spearman
+ value: 61.82780474476838
+ - type: euclidean_pearson
+ value: 45.885111672377256
+ - type: euclidean_spearman
+ value: 56.88306351932454
+ - type: manhattan_pearson
+ value: 46.101218127323186
+ - type: manhattan_spearman
+ value: 56.80953694186333
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts22-crosslingual-sts
+ name: MTEB STS22 (de)
+ config: de
+ split: test
+ revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+ metrics:
+ - type: cos_sim_pearson
+ value: 45.781923079584146
+ - type: cos_sim_spearman
+ value: 55.95098449691107
+ - type: euclidean_pearson
+ value: 25.4571031323205
+ - type: euclidean_spearman
+ value: 49.859978118078935
+ - type: manhattan_pearson
+ value: 25.624938455041384
+ - type: manhattan_spearman
+ value: 49.99546185049401
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts22-crosslingual-sts
+ name: MTEB STS22 (es)
+ config: es
+ split: test
+ revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+ metrics:
+ - type: cos_sim_pearson
+ value: 60.00618133997907
+ - type: cos_sim_spearman
+ value: 66.57896677718321
+ - type: euclidean_pearson
+ value: 42.60118466388821
+ - type: euclidean_spearman
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+ name: MTEB STS22 (es-it)
+ config: es-it
+ split: test
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+ - type: manhattan_pearson
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+ name: MTEB STS22 (de-fr)
+ config: de-fr
+ split: test
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+ - type: manhattan_pearson
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+ name: MTEB STS22 (de-pl)
+ config: de-pl
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+ metrics:
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+ - type: manhattan_pearson
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+ - type: manhattan_spearman
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+ - task:
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+ dataset:
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+ name: MTEB STS22 (fr-pl)
+ config: fr-pl
+ split: test
+ revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+ metrics:
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+ - type: euclidean_pearson
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+ - type: manhattan_pearson
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+ - type: manhattan_spearman
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+ - task:
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+ dataset:
+ type: mteb/stsbenchmark-sts
+ name: MTEB STSBenchmark
+ config: default
+ split: test
+ revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+ metrics:
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+ - type: euclidean_pearson
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+ - type: manhattan_pearson
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+ - type: manhattan_spearman
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+ - task:
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+ dataset:
+ type: mteb/scidocs-reranking
+ name: MTEB SciDocsRR
+ config: default
+ split: test
+ revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+ metrics:
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+ - type: mrr
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+ - task:
+ type: Retrieval
+ dataset:
+ type: scifact
+ name: MTEB SciFact
+ config: default
+ split: test
+ revision: None
+ metrics:
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+ - type: map_at_10
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - type: recall_at_1000
+ value: 99.333
+ - type: recall_at_3
+ value: 70.783
+ - type: recall_at_5
+ value: 75.978
+ - task:
+ type: PairClassification
+ dataset:
+ type: mteb/sprintduplicatequestions-pairclassification
+ name: MTEB SprintDuplicateQuestions
+ config: default
+ split: test
+ revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+ metrics:
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+ - type: cos_sim_ap
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+ - type: cos_sim_f1
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+ - type: cos_sim_precision
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+ - type: cos_sim_recall
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+ - type: dot_accuracy
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+ - type: dot_ap
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+ - type: dot_f1
+ value: 53.51351351351352
+ - type: dot_precision
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+ - type: dot_recall
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+ - type: euclidean_accuracy
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+ - type: euclidean_ap
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+ - type: euclidean_f1
+ value: 86.97838109602817
+ - type: euclidean_precision
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+ - type: euclidean_recall
+ value: 86.5
+ - type: manhattan_accuracy
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+ - type: manhattan_ap
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+ - type: manhattan_f1
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+ - type: manhattan_precision
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+ - type: manhattan_recall
+ value: 86.5
+ - type: max_accuracy
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+ - type: max_ap
+ value: 93.01476369929063
+ - type: max_f1
+ value: 86.97838109602817
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/stackexchange-clustering
+ name: MTEB StackExchangeClustering
+ config: default
+ split: test
+ revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+ metrics:
+ - type: v_measure
+ value: 55.2660514302523
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/stackexchange-clustering-p2p
+ name: MTEB StackExchangeClusteringP2P
+ config: default
+ split: test
+ revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+ metrics:
+ - type: v_measure
+ value: 30.4637783572547
+ - task:
+ type: Reranking
+ dataset:
+ type: mteb/stackoverflowdupquestions-reranking
+ name: MTEB StackOverflowDupQuestions
+ config: default
+ split: test
+ revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+ metrics:
+ - type: map
+ value: 49.41377758357637
+ - type: mrr
+ value: 50.138451213818854
+ - task:
+ type: Summarization
+ dataset:
+ type: mteb/summeval
+ name: MTEB SummEval
+ config: default
+ split: test
+ revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+ metrics:
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+ - type: cos_sim_spearman
+ value: 30.10823258355903
+ - type: dot_pearson
+ value: 12.888049550236385
+ - type: dot_spearman
+ value: 12.827495903098123
+ - task:
+ type: Retrieval
+ dataset:
+ type: trec-covid
+ name: MTEB TRECCOVID
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 0.21
+ - type: map_at_10
+ value: 1.667
+ - type: map_at_100
+ value: 9.15
+ - type: map_at_1000
+ value: 22.927
+ - type: map_at_3
+ value: 0.573
+ - type: map_at_5
+ value: 0.915
+ - type: mrr_at_1
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+ - type: mrr_at_10
+ value: 87.167
+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
+ value: 78.0
+ - type: recall_at_1
+ value: 0.21
+ - type: recall_at_10
+ value: 1.9189999999999998
+ - type: recall_at_100
+ value: 12.589
+ - type: recall_at_1000
+ value: 45.312000000000005
+ - type: recall_at_3
+ value: 0.61
+ - type: recall_at_5
+ value: 1.019
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (sqi-eng)
+ config: sqi-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 92.10000000000001
+ - type: f1
+ value: 90.06
+ - type: precision
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+ - type: recall
+ value: 92.10000000000001
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (fry-eng)
+ config: fry-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 56.06936416184971
+ - type: f1
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+ - type: precision
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+ - type: recall
+ value: 56.06936416184971
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (kur-eng)
+ config: kur-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 57.3170731707317
+ - type: f1
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+ - type: precision
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+ - type: recall
+ value: 57.3170731707317
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (tur-eng)
+ config: tur-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 94.3
+ - type: f1
+ value: 92.67333333333333
+ - type: precision
+ value: 91.90833333333333
+ - type: recall
+ value: 94.3
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (deu-eng)
+ config: deu-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 97.7
+ - type: f1
+ value: 97.07333333333332
+ - type: precision
+ value: 96.79500000000002
+ - type: recall
+ value: 97.7
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (nld-eng)
+ config: nld-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 94.69999999999999
+ - type: f1
+ value: 93.2
+ - type: precision
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+ - type: recall
+ value: 94.69999999999999
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (ron-eng)
+ config: ron-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 92.9
+ - type: f1
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+ - type: precision
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+ - type: recall
+ value: 92.9
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (ang-eng)
+ config: ang-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 34.32835820895522
+ - type: f1
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+ - type: precision
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+ - type: recall
+ value: 34.32835820895522
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (ido-eng)
+ config: ido-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 78.5
+ - type: f1
+ value: 74.3945115995116
+ - type: precision
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+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (khm-eng)
+ config: khm-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 53.8781163434903
+ - type: f1
+ value: 47.25804051288816
+ - type: precision
+ value: 45.0603482390186
+ - type: recall
+ value: 53.8781163434903
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (ces-eng)
+ config: ces-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 91.10000000000001
+ - type: f1
+ value: 88.88
+ - type: precision
+ value: 87.96333333333334
+ - type: recall
+ value: 91.10000000000001
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (tzl-eng)
+ config: tzl-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 38.46153846153847
+ - type: f1
+ value: 34.43978243978244
+ - type: precision
+ value: 33.429487179487175
+ - type: recall
+ value: 38.46153846153847
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (urd-eng)
+ config: urd-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 88.9
+ - type: f1
+ value: 86.19888888888887
+ - type: precision
+ value: 85.07440476190476
+ - type: recall
+ value: 88.9
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (ara-eng)
+ config: ara-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 85.9
+ - type: f1
+ value: 82.58857142857143
+ - type: precision
+ value: 81.15666666666667
+ - type: recall
+ value: 85.9
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (kor-eng)
+ config: kor-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 86.8
+ - type: f1
+ value: 83.36999999999999
+ - type: precision
+ value: 81.86833333333333
+ - type: recall
+ value: 86.8
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (yid-eng)
+ config: yid-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 68.51415094339622
+ - type: f1
+ value: 63.195000099481234
+ - type: precision
+ value: 61.394033442972116
+ - type: recall
+ value: 68.51415094339622
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (fin-eng)
+ config: fin-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 88.5
+ - type: f1
+ value: 86.14603174603175
+ - type: precision
+ value: 85.1162037037037
+ - type: recall
+ value: 88.5
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (tha-eng)
+ config: tha-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 95.62043795620438
+ - type: f1
+ value: 94.40389294403892
+ - type: precision
+ value: 93.7956204379562
+ - type: recall
+ value: 95.62043795620438
+ - task:
+ type: BitextMining
+ dataset:
+ type: mteb/tatoeba-bitext-mining
+ name: MTEB Tatoeba (wuu-eng)
+ config: wuu-eng
+ split: test
+ revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
+ metrics:
+ - type: accuracy
+ value: 81.8
+ - type: f1
+ value: 78.6532178932179
+ - type: precision
+ value: 77.46348795840176
+ - type: recall
+ value: 81.8
+ - task:
+ type: Retrieval
+ dataset:
+ type: webis-touche2020
+ name: MTEB Touche2020
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 2.603
+ - type: map_at_10
+ value: 8.5
+ - type: map_at_100
+ value: 12.985
+ - type: map_at_1000
+ value: 14.466999999999999
+ - type: map_at_3
+ value: 4.859999999999999
+ - type: map_at_5
+ value: 5.817
+ - type: mrr_at_1
+ value: 28.571
+ - type: mrr_at_10
+ value: 42.331
+ - type: mrr_at_100
+ value: 43.592999999999996
+ - type: mrr_at_1000
+ value: 43.592999999999996
+ - type: mrr_at_3
+ value: 38.435
+ - type: mrr_at_5
+ value: 39.966
+ - type: ndcg_at_1
+ value: 26.531
+ - type: ndcg_at_10
+ value: 21.353
+ - type: ndcg_at_100
+ value: 31.087999999999997
+ - type: ndcg_at_1000
+ value: 43.163000000000004
+ - type: ndcg_at_3
+ value: 22.999
+ - type: ndcg_at_5
+ value: 21.451
+ - type: precision_at_1
+ value: 28.571
+ - type: precision_at_10
+ value: 19.387999999999998
+ - type: precision_at_100
+ value: 6.265
+ - type: precision_at_1000
+ value: 1.4160000000000001
+ - type: precision_at_3
+ value: 24.490000000000002
+ - type: precision_at_5
+ value: 21.224
+ - type: recall_at_1
+ value: 2.603
+ - type: recall_at_10
+ value: 14.474
+ - type: recall_at_100
+ value: 40.287
+ - type: recall_at_1000
+ value: 76.606
+ - type: recall_at_3
+ value: 5.978
+ - type: recall_at_5
+ value: 7.819
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/toxic_conversations_50k
+ name: MTEB ToxicConversationsClassification
+ config: default
+ split: test
+ revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+ metrics:
+ - type: accuracy
+ value: 69.7848
+ - type: ap
+ value: 13.661023167088224
+ - type: f1
+ value: 53.61686134460943
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/tweet_sentiment_extraction
+ name: MTEB TweetSentimentExtractionClassification
+ config: default
+ split: test
+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+ metrics:
+ - type: accuracy
+ value: 61.28183361629882
+ - type: f1
+ value: 61.55481034919965
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/twentynewsgroups-clustering
+ name: MTEB TwentyNewsgroupsClustering
+ config: default
+ split: test
+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+ metrics:
+ - type: v_measure
+ value: 35.972128420092396
+ - task:
+ type: PairClassification
+ dataset:
+ type: mteb/twittersemeval2015-pairclassification
+ name: MTEB TwitterSemEval2015
+ config: default
+ split: test
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+ metrics:
+ - type: cos_sim_accuracy
+ value: 85.59933241938367
+ - type: cos_sim_ap
+ value: 72.20760361208136
+ - type: cos_sim_f1
+ value: 66.4447731755424
+ - type: cos_sim_precision
+ value: 62.35539102267469
+ - type: cos_sim_recall
+ value: 71.10817941952506
+ - type: dot_accuracy
+ value: 78.98313166835548
+ - type: dot_ap
+ value: 44.492521645493795
+ - type: dot_f1
+ value: 45.814889336016094
+ - type: dot_precision
+ value: 37.02439024390244
+ - type: dot_recall
+ value: 60.07915567282321
+ - type: euclidean_accuracy
+ value: 85.3907134767837
+ - type: euclidean_ap
+ value: 71.53847289080343
+ - type: euclidean_f1
+ value: 65.95952206778834
+ - type: euclidean_precision
+ value: 61.31006346328196
+ - type: euclidean_recall
+ value: 71.37203166226914
+ - type: manhattan_accuracy
+ value: 85.40859510043511
+ - type: manhattan_ap
+ value: 71.49664104395515
+ - type: manhattan_f1
+ value: 65.98569969356485
+ - type: manhattan_precision
+ value: 63.928748144482924
+ - type: manhattan_recall
+ value: 68.17941952506597
+ - type: max_accuracy
+ value: 85.59933241938367
+ - type: max_ap
+ value: 72.20760361208136
+ - type: max_f1
+ value: 66.4447731755424
+ - task:
+ type: PairClassification
+ dataset:
+ type: mteb/twitterurlcorpus-pairclassification
+ name: MTEB TwitterURLCorpus
+ config: default
+ split: test
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+ metrics:
+ - type: cos_sim_accuracy
+ value: 88.83261536073273
+ - type: cos_sim_ap
+ value: 85.48178133644264
+ - type: cos_sim_f1
+ value: 77.87816307403935
+ - type: cos_sim_precision
+ value: 75.88953021114926
+ - type: cos_sim_recall
+ value: 79.97382198952879
+ - type: dot_accuracy
+ value: 79.76287499514883
+ - type: dot_ap
+ value: 59.17438838475084
+ - type: dot_f1
+ value: 56.34566667855996
+ - type: dot_precision
+ value: 52.50349092359864
+ - type: dot_recall
+ value: 60.794579611949494
+ - type: euclidean_accuracy
+ value: 88.76857996662397
+ - type: euclidean_ap
+ value: 85.22764834359887
+ - type: euclidean_f1
+ value: 77.65379751543554
+ - type: euclidean_precision
+ value: 75.11152683839401
+ - type: euclidean_recall
+ value: 80.37419156144134
+ - type: manhattan_accuracy
+ value: 88.6987231730508
+ - type: manhattan_ap
+ value: 85.18907981724007
+ - type: manhattan_f1
+ value: 77.51967028849757
+ - type: manhattan_precision
+ value: 75.49992701795358
+ - type: manhattan_recall
+ value: 79.65044656606098
+ - type: max_accuracy
+ value: 88.83261536073273
+ - type: max_ap
+ value: 85.48178133644264
+ - type: max_f1
+ value: 77.87816307403935
+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
+---
+
+## Multilingual-E5-base
+
+[Text Embeddings by Weakly-Supervised Contrastive Pre-training](https://arxiv.org/pdf/2212.03533.pdf).
+Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022
+
+This model has 12 layers and the embedding size is 768.
+
+## 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-base')
+model = AutoModel.from_pretrained('intfloat/multilingual-e5-base')
+
+# Tokenize the input texts
+batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')
+
+outputs = model(**batch_dict)
+embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask'])
+
+# (Optionally) normalize embeddings
+embeddings = F.normalize(embeddings, p=2, dim=1)
+scores = (embeddings[:2] @ embeddings[2:].T) * 100
+print(scores.tolist())
+```
+
+## Supported Languages
+
+This model is initialized from [xlm-roberta-base](https://huggingface.co/xlm-roberta-base)
+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
+
+Please refer to our paper at [https://arxiv.org/pdf/2212.03533.pdf](https://arxiv.org/pdf/2212.03533.pdf).
+
+## Benchmark Evaluation
+
+Check out [unilm/e5](https://github.com/microsoft/unilm/tree/master/e5) to reproduce evaluation results
+on the [BEIR](https://arxiv.org/abs/2104.08663) and [MTEB benchmark](https://arxiv.org/abs/2210.07316).
+
+## Citation
+
+If you find our paper or models helpful, please consider cite as follows:
+
+```
+@article{wang2022text,
+ title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
+ author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
+ journal={arXiv preprint arXiv:2212.03533},
+ year={2022}
+}
+```
+
+## Limitations
+
+Long texts will be truncated to at most 512 tokens.
+
diff --git a/config.json b/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..2b827c7eb80b3765ec6f465ab7cbfe173388c9dc
--- /dev/null
+++ b/config.json
@@ -0,0 +1,28 @@
+{
+ "_name_or_path": "tmp/",
+ "architectures": [
+ "XLMRobertaModel"
+ ],
+ "attention_probs_dropout_prob": 0.1,
+ "bos_token_id": 0,
+ "classifier_dropout": null,
+ "eos_token_id": 2,
+ "hidden_act": "gelu",
+ "hidden_dropout_prob": 0.1,
+ "hidden_size": 768,
+ "initializer_range": 0.02,
+ "intermediate_size": 3072,
+ "layer_norm_eps": 1e-05,
+ "max_position_embeddings": 514,
+ "model_type": "xlm-roberta",
+ "num_attention_heads": 12,
+ "num_hidden_layers": 12,
+ "output_past": true,
+ "pad_token_id": 1,
+ "position_embedding_type": "absolute",
+ "torch_dtype": "float32",
+ "transformers_version": "4.29.0.dev0",
+ "type_vocab_size": 1,
+ "use_cache": true,
+ "vocab_size": 250002
+}
diff --git a/pytorch_model.bin b/pytorch_model.bin
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+version https://git-lfs.github.com/spec/v1
+oid sha256:f061cb7641880f52895cbacab7c4ab39b0844e2e6b73794f2798de460d9fa418
+size 1112242989
diff --git a/sentencepiece.bpe.model b/sentencepiece.bpe.model
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index 0000000000000000000000000000000000000000..7a3f40a75f870bc1f21700cd414dc2acc431583c
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+version https://git-lfs.github.com/spec/v1
+oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
+size 5069051
diff --git a/special_tokens_map.json b/special_tokens_map.json
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index 0000000000000000000000000000000000000000..d5698132694f4f1bcff08fa7d937b1701812598e
--- /dev/null
+++ b/special_tokens_map.json
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+{
+ "bos_token": "",
+ "cls_token": "",
+ "eos_token": "",
+ "mask_token": {
+ "content": "",
+ "lstrip": true,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ },
+ "pad_token": "",
+ "sep_token": "",
+ "unk_token": ""
+}
diff --git a/tokenizer_config.json b/tokenizer_config.json
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index 0000000000000000000000000000000000000000..6de1940d16d38be9877bf7cc228c9377841b311f
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+++ b/tokenizer_config.json
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+{
+ "bos_token": "",
+ "clean_up_tokenization_spaces": true,
+ "cls_token": "",
+ "eos_token": "",
+ "mask_token": {
+ "__type": "AddedToken",
+ "content": "",
+ "lstrip": true,
+ "normalized": true,
+ "rstrip": false,
+ "single_word": false
+ },
+ "model_max_length": 512,
+ "pad_token": "",
+ "sep_token": "",
+ "tokenizer_class": "XLMRobertaTokenizer",
+ "unk_token": ""
+}