Add model

README.md

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+---
+tags:
+- mteb
+model-index:
+- name: e5-small-v2
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 77.59701492537313
+    - type: ap
+      value: 41.67064885731708
+    - type: f1
+      value: 71.86465946398573
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 91.265875
+    - type: ap
+      value: 87.67633085349644
+    - type: f1
+      value: 91.24297521425744
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 45.882000000000005
+    - type: f1
+      value: 45.08058870381236
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 20.697
+    - type: map_at_10
+      value: 33.975
+    - type: map_at_100
+      value: 35.223
+    - type: map_at_1000
+      value: 35.260000000000005
+    - type: map_at_3
+      value: 29.776999999999997
+    - type: map_at_5
+      value: 32.035000000000004
+    - type: mrr_at_1
+      value: 20.982
+    - type: mrr_at_10
+      value: 34.094
+    - type: mrr_at_100
+      value: 35.343
+    - type: mrr_at_1000
+      value: 35.38
+    - type: mrr_at_3
+      value: 29.884
+    - type: mrr_at_5
+      value: 32.141999999999996
+    - type: ndcg_at_1
+      value: 20.697
+    - type: ndcg_at_10
+      value: 41.668
+    - type: ndcg_at_100
+      value: 47.397
+    - type: ndcg_at_1000
+      value: 48.305
+    - type: ndcg_at_3
+      value: 32.928000000000004
+    - type: ndcg_at_5
+      value: 36.998999999999995
+    - type: precision_at_1
+      value: 20.697
+    - type: precision_at_10
+      value: 6.636
+    - type: precision_at_100
+      value: 0.924
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 14.035
+    - type: precision_at_5
+      value: 10.398
+    - type: recall_at_1
+      value: 20.697
+    - type: recall_at_10
+      value: 66.35799999999999
+    - type: recall_at_100
+      value: 92.39
+    - type: recall_at_1000
+      value: 99.36
+    - type: recall_at_3
+      value: 42.105
+    - type: recall_at_5
+      value: 51.991
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 42.1169517447068
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 34.79553720107097
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 58.10811337308168
+    - type: mrr
+      value: 71.56410763751482
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 78.46834918248696
+    - type: cos_sim_spearman
+      value: 79.4289182755206
+    - type: euclidean_pearson
+      value: 76.26662973727008
+    - type: euclidean_spearman
+      value: 78.11744260952536
+    - type: manhattan_pearson
+      value: 76.08175262609434
+    - type: manhattan_spearman
+      value: 78.29395265552289
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 81.63636363636364
+    - type: f1
+      value: 81.55779952376953
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 35.88541137137571
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 30.05205685274407
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 30.293999999999997
+    - type: map_at_10
+      value: 39.876
+    - type: map_at_100
+      value: 41.315000000000005
+    - type: map_at_1000
+      value: 41.451
+    - type: map_at_3
+      value: 37.194
+    - type: map_at_5
+      value: 38.728
+    - type: mrr_at_1
+      value: 37.053000000000004
+    - type: mrr_at_10
+      value: 45.281
+    - type: mrr_at_100
+      value: 46.188
+    - type: mrr_at_1000
+      value: 46.245999999999995
+    - type: mrr_at_3
+      value: 43.228
+    - type: mrr_at_5
+      value: 44.366
+    - type: ndcg_at_1
+      value: 37.053000000000004
+    - type: ndcg_at_10
+      value: 45.086
+    - type: ndcg_at_100
+      value: 50.756
+    - type: ndcg_at_1000
+      value: 53.123
+    - type: ndcg_at_3
+      value: 41.416
+    - type: ndcg_at_5
+      value: 43.098
+    - type: precision_at_1
+      value: 37.053000000000004
+    - type: precision_at_10
+      value: 8.34
+    - type: precision_at_100
+      value: 1.346
+    - type: precision_at_1000
+      value: 0.186
+    - type: precision_at_3
+      value: 19.647000000000002
+    - type: precision_at_5
+      value: 13.877
+    - type: recall_at_1
+      value: 30.293999999999997
+    - type: recall_at_10
+      value: 54.309
+    - type: recall_at_100
+      value: 78.59
+    - type: recall_at_1000
+      value: 93.82300000000001
+    - type: recall_at_3
+      value: 43.168
+    - type: recall_at_5
+      value: 48.192
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.738000000000003
+    - type: map_at_10
+      value: 36.925999999999995
+    - type: map_at_100
+      value: 38.017
+    - type: map_at_1000
+      value: 38.144
+    - type: map_at_3
+      value: 34.446
+    - type: map_at_5
+      value: 35.704
+    - type: mrr_at_1
+      value: 35.478
+    - type: mrr_at_10
+      value: 42.786
+    - type: mrr_at_100
+      value: 43.458999999999996
+    - type: mrr_at_1000
+      value: 43.507
+    - type: mrr_at_3
+      value: 40.648
+    - type: mrr_at_5
+      value: 41.804
+    - type: ndcg_at_1
+      value: 35.478
+    - type: ndcg_at_10
+      value: 42.044
+    - type: ndcg_at_100
+      value: 46.249
+    - type: ndcg_at_1000
+      value: 48.44
+    - type: ndcg_at_3
+      value: 38.314
+    - type: ndcg_at_5
+      value: 39.798
+    - type: precision_at_1
+      value: 35.478
+    - type: precision_at_10
+      value: 7.764
+    - type: precision_at_100
+      value: 1.253
+    - type: precision_at_1000
+      value: 0.174
+    - type: precision_at_3
+      value: 18.047
+    - type: precision_at_5
+      value: 12.637
+    - type: recall_at_1
+      value: 28.738000000000003
+    - type: recall_at_10
+      value: 50.659
+    - type: recall_at_100
+      value: 68.76299999999999
+    - type: recall_at_1000
+      value: 82.811
+    - type: recall_at_3
+      value: 39.536
+    - type: recall_at_5
+      value: 43.763999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 38.565
+    - type: map_at_10
+      value: 50.168
+    - type: map_at_100
+      value: 51.11
+    - type: map_at_1000
+      value: 51.173
+    - type: map_at_3
+      value: 47.044000000000004
+    - type: map_at_5
+      value: 48.838
+    - type: mrr_at_1
+      value: 44.201
+    - type: mrr_at_10
+      value: 53.596999999999994
+    - type: mrr_at_100
+      value: 54.211
+    - type: mrr_at_1000
+      value: 54.247
+    - type: mrr_at_3
+      value: 51.202000000000005
+    - type: mrr_at_5
+      value: 52.608999999999995
+    - type: ndcg_at_1
+      value: 44.201
+    - type: ndcg_at_10
+      value: 55.694
+    - type: ndcg_at_100
+      value: 59.518
+    - type: ndcg_at_1000
+      value: 60.907
+    - type: ndcg_at_3
+      value: 50.395999999999994
+    - type: ndcg_at_5
+      value: 53.022999999999996
+    - type: precision_at_1
+      value: 44.201
+    - type: precision_at_10
+      value: 8.84
+    - type: precision_at_100
+      value: 1.162
+    - type: precision_at_1000
+      value: 0.133
+    - type: precision_at_3
+      value: 22.153
+    - type: precision_at_5
+      value: 15.260000000000002
+    - type: recall_at_1
+      value: 38.565
+    - type: recall_at_10
+      value: 68.65
+    - type: recall_at_100
+      value: 85.37400000000001
+    - type: recall_at_1000
+      value: 95.37400000000001
+    - type: recall_at_3
+      value: 54.645999999999994
+    - type: recall_at_5
+      value: 60.958
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.945
+    - type: map_at_10
+      value: 30.641000000000002
+    - type: map_at_100
+      value: 31.599
+    - type: map_at_1000
+      value: 31.691000000000003
+    - type: map_at_3
+      value: 28.405
+    - type: map_at_5
+      value: 29.704000000000004
+    - type: mrr_at_1
+      value: 25.537
+    - type: mrr_at_10
+      value: 32.22
+    - type: mrr_at_100
+      value: 33.138
+    - type: mrr_at_1000
+      value: 33.214
+    - type: mrr_at_3
+      value: 30.151
+    - type: mrr_at_5
+      value: 31.298
+    - type: ndcg_at_1
+      value: 25.537
+    - type: ndcg_at_10
+      value: 34.638000000000005
+    - type: ndcg_at_100
+      value: 39.486
+    - type: ndcg_at_1000
+      value: 41.936
+    - type: ndcg_at_3
+      value: 30.333
+    - type: ndcg_at_5
+      value: 32.482
+    - type: precision_at_1
+      value: 25.537
+    - type: precision_at_10
+      value: 5.153
+    - type: precision_at_100
+      value: 0.7929999999999999
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 12.429
+    - type: precision_at_5
+      value: 8.723
+    - type: recall_at_1
+      value: 23.945
+    - type: recall_at_10
+      value: 45.412
+    - type: recall_at_100
+      value: 67.836
+    - type: recall_at_1000
+      value: 86.467
+    - type: recall_at_3
+      value: 34.031
+    - type: recall_at_5
+      value: 39.039
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 14.419
+    - type: map_at_10
+      value: 20.858999999999998
+    - type: map_at_100
+      value: 22.067999999999998
+    - type: map_at_1000
+      value: 22.192
+    - type: map_at_3
+      value: 18.673000000000002
+    - type: map_at_5
+      value: 19.968
+    - type: mrr_at_1
+      value: 17.785999999999998
+    - type: mrr_at_10
+      value: 24.878
+    - type: mrr_at_100
+      value: 26.021
+    - type: mrr_at_1000
+      value: 26.095000000000002
+    - type: mrr_at_3
+      value: 22.616
+    - type: mrr_at_5
+      value: 23.785
+    - type: ndcg_at_1
+      value: 17.785999999999998
+    - type: ndcg_at_10
+      value: 25.153
+    - type: ndcg_at_100
+      value: 31.05
+    - type: ndcg_at_1000
+      value: 34.052
+    - type: ndcg_at_3
+      value: 21.117
+    - type: ndcg_at_5
+      value: 23.048
+    - type: precision_at_1
+      value: 17.785999999999998
+    - type: precision_at_10
+      value: 4.590000000000001
+    - type: precision_at_100
+      value: 0.864
+    - type: precision_at_1000
+      value: 0.125
+    - type: precision_at_3
+      value: 9.908999999999999
+    - type: precision_at_5
+      value: 7.313
+    - type: recall_at_1
+      value: 14.419
+    - type: recall_at_10
+      value: 34.477999999999994
+    - type: recall_at_100
+      value: 60.02499999999999
+    - type: recall_at_1000
+      value: 81.646
+    - type: recall_at_3
+      value: 23.515
+    - type: recall_at_5
+      value: 28.266999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.268
+    - type: map_at_10
+      value: 35.114000000000004
+    - type: map_at_100
+      value: 36.212
+    - type: map_at_1000
+      value: 36.333
+    - type: map_at_3
+      value: 32.436
+    - type: map_at_5
+      value: 33.992
+    - type: mrr_at_1
+      value: 31.761
+    - type: mrr_at_10
+      value: 40.355999999999995
+    - type: mrr_at_100
+      value: 41.125
+    - type: mrr_at_1000
+      value: 41.186
+    - type: mrr_at_3
+      value: 37.937
+    - type: mrr_at_5
+      value: 39.463
+    - type: ndcg_at_1
+      value: 31.761
+    - type: ndcg_at_10
+      value: 40.422000000000004
+    - type: ndcg_at_100
+      value: 45.458999999999996
+    - type: ndcg_at_1000
+      value: 47.951
+    - type: ndcg_at_3
+      value: 35.972
+    - type: ndcg_at_5
+      value: 38.272
+    - type: precision_at_1
+      value: 31.761
+    - type: precision_at_10
+      value: 7.103
+    - type: precision_at_100
+      value: 1.133
+    - type: precision_at_1000
+      value: 0.152
+    - type: precision_at_3
+      value: 16.779
+    - type: precision_at_5
+      value: 11.877
+    - type: recall_at_1
+      value: 26.268
+    - type: recall_at_10
+      value: 51.053000000000004
+    - type: recall_at_100
+      value: 72.702
+    - type: recall_at_1000
+      value: 89.521
+    - type: recall_at_3
+      value: 38.619
+    - type: recall_at_5
+      value: 44.671
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.230999999999998
+    - type: map_at_10
+      value: 34.227000000000004
+    - type: map_at_100
+      value: 35.370000000000005
+    - type: map_at_1000
+      value: 35.488
+    - type: map_at_3
+      value: 31.496000000000002
+    - type: map_at_5
+      value: 33.034
+    - type: mrr_at_1
+      value: 30.822
+    - type: mrr_at_10
+      value: 39.045
+    - type: mrr_at_100
+      value: 39.809
+    - type: mrr_at_1000
+      value: 39.873
+    - type: mrr_at_3
+      value: 36.663000000000004
+    - type: mrr_at_5
+      value: 37.964
+    - type: ndcg_at_1
+      value: 30.822
+    - type: ndcg_at_10
+      value: 39.472
+    - type: ndcg_at_100
+      value: 44.574999999999996
+    - type: ndcg_at_1000
+      value: 47.162
+    - type: ndcg_at_3
+      value: 34.929
+    - type: ndcg_at_5
+      value: 37.002
+    - type: precision_at_1
+      value: 30.822
+    - type: precision_at_10
+      value: 7.055
+    - type: precision_at_100
+      value: 1.124
+    - type: precision_at_1000
+      value: 0.152
+    - type: precision_at_3
+      value: 16.591
+    - type: precision_at_5
+      value: 11.667
+    - type: recall_at_1
+      value: 25.230999999999998
+    - type: recall_at_10
+      value: 50.42100000000001
+    - type: recall_at_100
+      value: 72.685
+    - type: recall_at_1000
+      value: 90.469
+    - type: recall_at_3
+      value: 37.503
+    - type: recall_at_5
+      value: 43.123
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.604166666666664
+    - type: map_at_10
+      value: 32.427166666666665
+    - type: map_at_100
+      value: 33.51474999999999
+    - type: map_at_1000
+      value: 33.6345
+    - type: map_at_3
+      value: 30.02366666666667
+    - type: map_at_5
+      value: 31.382333333333328
+    - type: mrr_at_1
+      value: 29.001166666666666
+    - type: mrr_at_10
+      value: 36.3315
+    - type: mrr_at_100
+      value: 37.16683333333333
+    - type: mrr_at_1000
+      value: 37.23341666666668
+    - type: mrr_at_3
+      value: 34.19916666666667
+    - type: mrr_at_5
+      value: 35.40458333333334
+    - type: ndcg_at_1
+      value: 29.001166666666666
+    - type: ndcg_at_10
+      value: 37.06883333333334
+    - type: ndcg_at_100
+      value: 41.95816666666666
+    - type: ndcg_at_1000
+      value: 44.501583333333336
+    - type: ndcg_at_3
+      value: 32.973499999999994
+    - type: ndcg_at_5
+      value: 34.90833333333334
+    - type: precision_at_1
+      value: 29.001166666666666
+    - type: precision_at_10
+      value: 6.336
+    - type: precision_at_100
+      value: 1.0282499999999999
+    - type: precision_at_1000
+      value: 0.14391666666666664
+    - type: precision_at_3
+      value: 14.932499999999996
+    - type: precision_at_5
+      value: 10.50825
+    - type: recall_at_1
+      value: 24.604166666666664
+    - type: recall_at_10
+      value: 46.9525
+    - type: recall_at_100
+      value: 68.67816666666667
+    - type: recall_at_1000
+      value: 86.59783333333334
+    - type: recall_at_3
+      value: 35.49783333333333
+    - type: recall_at_5
+      value: 40.52525000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.559
+    - type: map_at_10
+      value: 29.023
+    - type: map_at_100
+      value: 29.818
+    - type: map_at_1000
+      value: 29.909000000000002
+    - type: map_at_3
+      value: 27.037
+    - type: map_at_5
+      value: 28.225
+    - type: mrr_at_1
+      value: 26.994
+    - type: mrr_at_10
+      value: 31.962000000000003
+    - type: mrr_at_100
+      value: 32.726
+    - type: mrr_at_1000
+      value: 32.800000000000004
+    - type: mrr_at_3
+      value: 30.266
+    - type: mrr_at_5
+      value: 31.208999999999996
+    - type: ndcg_at_1
+      value: 26.994
+    - type: ndcg_at_10
+      value: 32.53
+    - type: ndcg_at_100
+      value: 36.758
+    - type: ndcg_at_1000
+      value: 39.362
+    - type: ndcg_at_3
+      value: 28.985
+    - type: ndcg_at_5
+      value: 30.757
+    - type: precision_at_1
+      value: 26.994
+    - type: precision_at_10
+      value: 4.968999999999999
+    - type: precision_at_100
+      value: 0.759
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 12.219
+    - type: precision_at_5
+      value: 8.527999999999999
+    - type: recall_at_1
+      value: 23.559
+    - type: recall_at_10
+      value: 40.585
+    - type: recall_at_100
+      value: 60.306000000000004
+    - type: recall_at_1000
+      value: 80.11
+    - type: recall_at_3
+      value: 30.794
+    - type: recall_at_5
+      value: 35.186
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.384999999999998
+    - type: map_at_10
+      value: 22.142
+    - type: map_at_100
+      value: 23.057
+    - type: map_at_1000
+      value: 23.177
+    - type: map_at_3
+      value: 20.29
+    - type: map_at_5
+      value: 21.332
+    - type: mrr_at_1
+      value: 19.89
+    - type: mrr_at_10
+      value: 25.771
+    - type: mrr_at_100
+      value: 26.599
+    - type: mrr_at_1000
+      value: 26.680999999999997
+    - type: mrr_at_3
+      value: 23.962
+    - type: mrr_at_5
+      value: 24.934
+    - type: ndcg_at_1
+      value: 19.89
+    - type: ndcg_at_10
+      value: 25.97
+    - type: ndcg_at_100
+      value: 30.605
+    - type: ndcg_at_1000
+      value: 33.619
+    - type: ndcg_at_3
+      value: 22.704
+    - type: ndcg_at_5
+      value: 24.199
+    - type: precision_at_1
+      value: 19.89
+    - type: precision_at_10
+      value: 4.553
+    - type: precision_at_100
+      value: 0.8049999999999999
+    - type: precision_at_1000
+      value: 0.122
+    - type: precision_at_3
+      value: 10.541
+    - type: precision_at_5
+      value: 7.46
+    - type: recall_at_1
+      value: 16.384999999999998
+    - type: recall_at_10
+      value: 34.001
+    - type: recall_at_100
+      value: 55.17100000000001
+    - type: recall_at_1000
+      value: 77.125
+    - type: recall_at_3
+      value: 24.618000000000002
+    - type: recall_at_5
+      value: 28.695999999999998
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.726
+    - type: map_at_10
+      value: 31.227
+    - type: map_at_100
+      value: 32.311
+    - type: map_at_1000
+      value: 32.419
+    - type: map_at_3
+      value: 28.765
+    - type: map_at_5
+      value: 30.229
+    - type: mrr_at_1
+      value: 27.705000000000002
+    - type: mrr_at_10
+      value: 35.085
+    - type: mrr_at_100
+      value: 35.931000000000004
+    - type: mrr_at_1000
+      value: 36
+    - type: mrr_at_3
+      value: 32.603
+    - type: mrr_at_5
+      value: 34.117999999999995
+    - type: ndcg_at_1
+      value: 27.705000000000002
+    - type: ndcg_at_10
+      value: 35.968
+    - type: ndcg_at_100
+      value: 41.197
+    - type: ndcg_at_1000
+      value: 43.76
+    - type: ndcg_at_3
+      value: 31.304
+    - type: ndcg_at_5
+      value: 33.661
+    - type: precision_at_1
+      value: 27.705000000000002
+    - type: precision_at_10
+      value: 5.942
+    - type: precision_at_100
+      value: 0.964
+    - type: precision_at_1000
+      value: 0.13
+    - type: precision_at_3
+      value: 13.868
+    - type: precision_at_5
+      value: 9.944
+    - type: recall_at_1
+      value: 23.726
+    - type: recall_at_10
+      value: 46.786
+    - type: recall_at_100
+      value: 70.072
+    - type: recall_at_1000
+      value: 88.2
+    - type: recall_at_3
+      value: 33.981
+    - type: recall_at_5
+      value: 39.893
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.344
+    - type: map_at_10
+      value: 31.636999999999997
+    - type: map_at_100
+      value: 33.065
+    - type: map_at_1000
+      value: 33.300000000000004
+    - type: map_at_3
+      value: 29.351
+    - type: map_at_5
+      value: 30.432
+    - type: mrr_at_1
+      value: 27.866000000000003
+    - type: mrr_at_10
+      value: 35.587
+    - type: mrr_at_100
+      value: 36.52
+    - type: mrr_at_1000
+      value: 36.597
+    - type: mrr_at_3
+      value: 33.696
+    - type: mrr_at_5
+      value: 34.713
+    - type: ndcg_at_1
+      value: 27.866000000000003
+    - type: ndcg_at_10
+      value: 36.61
+    - type: ndcg_at_100
+      value: 41.88
+    - type: ndcg_at_1000
+      value: 45.105000000000004
+    - type: ndcg_at_3
+      value: 33.038000000000004
+    - type: ndcg_at_5
+      value: 34.331
+    - type: precision_at_1
+      value: 27.866000000000003
+    - type: precision_at_10
+      value: 6.917
+    - type: precision_at_100
+      value: 1.3599999999999999
+    - type: precision_at_1000
+      value: 0.233
+    - type: precision_at_3
+      value: 15.547
+    - type: precision_at_5
+      value: 10.791
+    - type: recall_at_1
+      value: 23.344
+    - type: recall_at_10
+      value: 45.782000000000004
+    - type: recall_at_100
+      value: 69.503
+    - type: recall_at_1000
+      value: 90.742
+    - type: recall_at_3
+      value: 35.160000000000004
+    - type: recall_at_5
+      value: 39.058
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 20.776
+    - type: map_at_10
+      value: 27.285999999999998
+    - type: map_at_100
+      value: 28.235
+    - type: map_at_1000
+      value: 28.337
+    - type: map_at_3
+      value: 25.147000000000002
+    - type: map_at_5
+      value: 26.401999999999997
+    - type: mrr_at_1
+      value: 22.921
+    - type: mrr_at_10
+      value: 29.409999999999997
+    - type: mrr_at_100
+      value: 30.275000000000002
+    - type: mrr_at_1000
+      value: 30.354999999999997
+    - type: mrr_at_3
+      value: 27.418
+    - type: mrr_at_5
+      value: 28.592000000000002
+    - type: ndcg_at_1
+      value: 22.921
+    - type: ndcg_at_10
+      value: 31.239
+    - type: ndcg_at_100
+      value: 35.965
+    - type: ndcg_at_1000
+      value: 38.602
+    - type: ndcg_at_3
+      value: 27.174
+    - type: ndcg_at_5
+      value: 29.229
+    - type: precision_at_1
+      value: 22.921
+    - type: precision_at_10
+      value: 4.806
+    - type: precision_at_100
+      value: 0.776
+    - type: precision_at_1000
+      value: 0.11
+    - type: precision_at_3
+      value: 11.459999999999999
+    - type: precision_at_5
+      value: 8.022
+    - type: recall_at_1
+      value: 20.776
+    - type: recall_at_10
+      value: 41.294
+    - type: recall_at_100
+      value: 63.111
+    - type: recall_at_1000
+      value: 82.88600000000001
+    - type: recall_at_3
+      value: 30.403000000000002
+    - type: recall_at_5
+      value: 35.455999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 9.376
+    - type: map_at_10
+      value: 15.926000000000002
+    - type: map_at_100
+      value: 17.585
+    - type: map_at_1000
+      value: 17.776
+    - type: map_at_3
+      value: 13.014000000000001
+    - type: map_at_5
+      value: 14.417
+    - type: mrr_at_1
+      value: 20.195
+    - type: mrr_at_10
+      value: 29.95
+    - type: mrr_at_100
+      value: 31.052000000000003
+    - type: mrr_at_1000
+      value: 31.108000000000004
+    - type: mrr_at_3
+      value: 26.667
+    - type: mrr_at_5
+      value: 28.458
+    - type: ndcg_at_1
+      value: 20.195
+    - type: ndcg_at_10
+      value: 22.871
+    - type: ndcg_at_100
+      value: 29.921999999999997
+    - type: ndcg_at_1000
+      value: 33.672999999999995
+    - type: ndcg_at_3
+      value: 17.782999999999998
+    - type: ndcg_at_5
+      value: 19.544
+    - type: precision_at_1
+      value: 20.195
+    - type: precision_at_10
+      value: 7.394
+    - type: precision_at_100
+      value: 1.493
+    - type: precision_at_1000
+      value: 0.218
+    - type: precision_at_3
+      value: 13.073
+    - type: precision_at_5
+      value: 10.436
+    - type: recall_at_1
+      value: 9.376
+    - type: recall_at_10
+      value: 28.544999999999998
+    - type: recall_at_100
+      value: 53.147999999999996
+    - type: recall_at_1000
+      value: 74.62
+    - type: recall_at_3
+      value: 16.464000000000002
+    - type: recall_at_5
+      value: 21.004
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 8.415000000000001
+    - type: map_at_10
+      value: 18.738
+    - type: map_at_100
+      value: 27.291999999999998
+    - type: map_at_1000
+      value: 28.992
+    - type: map_at_3
+      value: 13.196
+    - type: map_at_5
+      value: 15.539
+    - type: mrr_at_1
+      value: 66.5
+    - type: mrr_at_10
+      value: 74.518
+    - type: mrr_at_100
+      value: 74.86
+    - type: mrr_at_1000
+      value: 74.87
+    - type: mrr_at_3
+      value: 72.375
+    - type: mrr_at_5
+      value: 73.86200000000001
+    - type: ndcg_at_1
+      value: 54.37499999999999
+    - type: ndcg_at_10
+      value: 41.317
+    - type: ndcg_at_100
+      value: 45.845
+    - type: ndcg_at_1000
+      value: 52.92
+    - type: ndcg_at_3
+      value: 44.983000000000004
+    - type: ndcg_at_5
+      value: 42.989
+    - type: precision_at_1
+      value: 66.5
+    - type: precision_at_10
+      value: 33.6
+    - type: precision_at_100
+      value: 10.972999999999999
+    - type: precision_at_1000
+      value: 2.214
+    - type: precision_at_3
+      value: 48.583
+    - type: precision_at_5
+      value: 42.15
+    - type: recall_at_1
+      value: 8.415000000000001
+    - type: recall_at_10
+      value: 24.953
+    - type: recall_at_100
+      value: 52.48199999999999
+    - type: recall_at_1000
+      value: 75.093
+    - type: recall_at_3
+      value: 14.341000000000001
+    - type: recall_at_5
+      value: 18.468
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 47.06499999999999
+    - type: f1
+      value: 41.439327599975385
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 66.02
+    - type: map_at_10
+      value: 76.68599999999999
+    - type: map_at_100
+      value: 76.959
+    - type: map_at_1000
+      value: 76.972
+    - type: map_at_3
+      value: 75.024
+    - type: map_at_5
+      value: 76.153
+    - type: mrr_at_1
+      value: 71.197
+    - type: mrr_at_10
+      value: 81.105
+    - type: mrr_at_100
+      value: 81.232
+    - type: mrr_at_1000
+      value: 81.233
+    - type: mrr_at_3
+      value: 79.758
+    - type: mrr_at_5
+      value: 80.69
+    - type: ndcg_at_1
+      value: 71.197
+    - type: ndcg_at_10
+      value: 81.644
+    - type: ndcg_at_100
+      value: 82.645
+    - type: ndcg_at_1000
+      value: 82.879
+    - type: ndcg_at_3
+      value: 78.792
+    - type: ndcg_at_5
+      value: 80.528
+    - type: precision_at_1
+      value: 71.197
+    - type: precision_at_10
+      value: 10.206999999999999
+    - type: precision_at_100
+      value: 1.093
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 30.868000000000002
+    - type: precision_at_5
+      value: 19.559
+    - type: recall_at_1
+      value: 66.02
+    - type: recall_at_10
+      value: 92.50699999999999
+    - type: recall_at_100
+      value: 96.497
+    - type: recall_at_1000
+      value: 97.956
+    - type: recall_at_3
+      value: 84.866
+    - type: recall_at_5
+      value: 89.16199999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.948
+    - type: map_at_10
+      value: 29.833
+    - type: map_at_100
+      value: 31.487
+    - type: map_at_1000
+      value: 31.674000000000003
+    - type: map_at_3
+      value: 26.029999999999998
+    - type: map_at_5
+      value: 28.038999999999998
+    - type: mrr_at_1
+      value: 34.721999999999994
+    - type: mrr_at_10
+      value: 44.214999999999996
+    - type: mrr_at_100
+      value: 44.994
+    - type: mrr_at_1000
+      value: 45.051
+    - type: mrr_at_3
+      value: 41.667
+    - type: mrr_at_5
+      value: 43.032
+    - type: ndcg_at_1
+      value: 34.721999999999994
+    - type: ndcg_at_10
+      value: 37.434
+    - type: ndcg_at_100
+      value: 43.702000000000005
+    - type: ndcg_at_1000
+      value: 46.993
+    - type: ndcg_at_3
+      value: 33.56
+    - type: ndcg_at_5
+      value: 34.687
+    - type: precision_at_1
+      value: 34.721999999999994
+    - type: precision_at_10
+      value: 10.401
+    - type: precision_at_100
+      value: 1.7049999999999998
+    - type: precision_at_1000
+      value: 0.22799999999999998
+    - type: precision_at_3
+      value: 22.531000000000002
+    - type: precision_at_5
+      value: 16.42
+    - type: recall_at_1
+      value: 17.948
+    - type: recall_at_10
+      value: 45.062999999999995
+    - type: recall_at_100
+      value: 68.191
+    - type: recall_at_1000
+      value: 87.954
+    - type: recall_at_3
+      value: 31.112000000000002
+    - type: recall_at_5
+      value: 36.823
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 36.644
+    - type: map_at_10
+      value: 57.658
+    - type: map_at_100
+      value: 58.562000000000005
+    - type: map_at_1000
+      value: 58.62500000000001
+    - type: map_at_3
+      value: 54.022999999999996
+    - type: map_at_5
+      value: 56.293000000000006
+    - type: mrr_at_1
+      value: 73.288
+    - type: mrr_at_10
+      value: 80.51700000000001
+    - type: mrr_at_100
+      value: 80.72
+    - type: mrr_at_1000
+      value: 80.728
+    - type: mrr_at_3
+      value: 79.33200000000001
+    - type: mrr_at_5
+      value: 80.085
+    - type: ndcg_at_1
+      value: 73.288
+    - type: ndcg_at_10
+      value: 66.61
+    - type: ndcg_at_100
+      value: 69.723
+    - type: ndcg_at_1000
+      value: 70.96000000000001
+    - type: ndcg_at_3
+      value: 61.358999999999995
+    - type: ndcg_at_5
+      value: 64.277
+    - type: precision_at_1
+      value: 73.288
+    - type: precision_at_10
+      value: 14.17
+    - type: precision_at_100
+      value: 1.659
+    - type: precision_at_1000
+      value: 0.182
+    - type: precision_at_3
+      value: 39.487
+    - type: precision_at_5
+      value: 25.999
+    - type: recall_at_1
+      value: 36.644
+    - type: recall_at_10
+      value: 70.851
+    - type: recall_at_100
+      value: 82.94399999999999
+    - type: recall_at_1000
+      value: 91.134
+    - type: recall_at_3
+      value: 59.230000000000004
+    - type: recall_at_5
+      value: 64.997
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 86.00280000000001
+    - type: ap
+      value: 80.46302061021223
+    - type: f1
+      value: 85.9592921596419
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.541
+    - type: map_at_10
+      value: 34.625
+    - type: map_at_100
+      value: 35.785
+    - type: map_at_1000
+      value: 35.831
+    - type: map_at_3
+      value: 30.823
+    - type: map_at_5
+      value: 32.967999999999996
+    - type: mrr_at_1
+      value: 23.180999999999997
+    - type: mrr_at_10
+      value: 35.207
+    - type: mrr_at_100
+      value: 36.315
+    - type: mrr_at_1000
+      value: 36.355
+    - type: mrr_at_3
+      value: 31.483
+    - type: mrr_at_5
+      value: 33.589999999999996
+    - type: ndcg_at_1
+      value: 23.195
+    - type: ndcg_at_10
+      value: 41.461
+    - type: ndcg_at_100
+      value: 47.032000000000004
+    - type: ndcg_at_1000
+      value: 48.199999999999996
+    - type: ndcg_at_3
+      value: 33.702
+    - type: ndcg_at_5
+      value: 37.522
+    - type: precision_at_1
+      value: 23.195
+    - type: precision_at_10
+      value: 6.526999999999999
+    - type: precision_at_100
+      value: 0.932
+    - type: precision_at_1000
+      value: 0.10300000000000001
+    - type: precision_at_3
+      value: 14.308000000000002
+    - type: precision_at_5
+      value: 10.507
+    - type: recall_at_1
+      value: 22.541
+    - type: recall_at_10
+      value: 62.524
+    - type: recall_at_100
+      value: 88.228
+    - type: recall_at_1000
+      value: 97.243
+    - type: recall_at_3
+      value: 41.38
+    - type: recall_at_5
+      value: 50.55
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 92.69949840401279
+    - type: f1
+      value: 92.54141471311786
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 72.56041951664386
+    - type: f1
+      value: 55.88499977508287
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 71.62071284465365
+    - type: f1
+      value: 69.36717546572152
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 76.35843981170142
+    - type: f1
+      value: 76.15496453538884
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 31.33664956793118
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 27.883839621715524
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 30.096874986740758
+    - type: mrr
+      value: 30.97300481932132
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.4
+    - type: map_at_10
+      value: 11.852
+    - type: map_at_100
+      value: 14.758
+    - type: map_at_1000
+      value: 16.134
+    - type: map_at_3
+      value: 8.558
+    - type: map_at_5
+      value: 10.087
+    - type: mrr_at_1
+      value: 44.272
+    - type: mrr_at_10
+      value: 52.05800000000001
+    - type: mrr_at_100
+      value: 52.689
+    - type: mrr_at_1000
+      value: 52.742999999999995
+    - type: mrr_at_3
+      value: 50.205999999999996
+    - type: mrr_at_5
+      value: 51.367
+    - type: ndcg_at_1
+      value: 42.57
+    - type: ndcg_at_10
+      value: 32.449
+    - type: ndcg_at_100
+      value: 29.596
+    - type: ndcg_at_1000
+      value: 38.351
+    - type: ndcg_at_3
+      value: 37.044
+    - type: ndcg_at_5
+      value: 35.275
+    - type: precision_at_1
+      value: 44.272
+    - type: precision_at_10
+      value: 23.87
+    - type: precision_at_100
+      value: 7.625
+    - type: precision_at_1000
+      value: 2.045
+    - type: precision_at_3
+      value: 34.365
+    - type: precision_at_5
+      value: 30.341
+    - type: recall_at_1
+      value: 5.4
+    - type: recall_at_10
+      value: 15.943999999999999
+    - type: recall_at_100
+      value: 29.805
+    - type: recall_at_1000
+      value: 61.695
+    - type: recall_at_3
+      value: 9.539
+    - type: recall_at_5
+      value: 12.127
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 36.047000000000004
+    - type: map_at_10
+      value: 51.6
+    - type: map_at_100
+      value: 52.449999999999996
+    - type: map_at_1000
+      value: 52.476
+    - type: map_at_3
+      value: 47.452
+    - type: map_at_5
+      value: 49.964
+    - type: mrr_at_1
+      value: 40.382
+    - type: mrr_at_10
+      value: 54.273
+    - type: mrr_at_100
+      value: 54.859
+    - type: mrr_at_1000
+      value: 54.876000000000005
+    - type: mrr_at_3
+      value: 51.014
+    - type: mrr_at_5
+      value: 52.983999999999995
+    - type: ndcg_at_1
+      value: 40.353
+    - type: ndcg_at_10
+      value: 59.11300000000001
+    - type: ndcg_at_100
+      value: 62.604000000000006
+    - type: ndcg_at_1000
+      value: 63.187000000000005
+    - type: ndcg_at_3
+      value: 51.513
+    - type: ndcg_at_5
+      value: 55.576
+    - type: precision_at_1
+      value: 40.353
+    - type: precision_at_10
+      value: 9.418
+    - type: precision_at_100
+      value: 1.1440000000000001
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_3
+      value: 23.078000000000003
+    - type: precision_at_5
+      value: 16.250999999999998
+    - type: recall_at_1
+      value: 36.047000000000004
+    - type: recall_at_10
+      value: 79.22200000000001
+    - type: recall_at_100
+      value: 94.23
+    - type: recall_at_1000
+      value: 98.51100000000001
+    - type: recall_at_3
+      value: 59.678
+    - type: recall_at_5
+      value: 68.967
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 68.232
+    - type: map_at_10
+      value: 81.674
+    - type: map_at_100
+      value: 82.338
+    - type: map_at_1000
+      value: 82.36099999999999
+    - type: map_at_3
+      value: 78.833
+    - type: map_at_5
+      value: 80.58
+    - type: mrr_at_1
+      value: 78.64
+    - type: mrr_at_10
+      value: 85.164
+    - type: mrr_at_100
+      value: 85.317
+    - type: mrr_at_1000
+      value: 85.319
+    - type: mrr_at_3
+      value: 84.127
+    - type: mrr_at_5
+      value: 84.789
+    - type: ndcg_at_1
+      value: 78.63
+    - type: ndcg_at_10
+      value: 85.711
+    - type: ndcg_at_100
+      value: 87.238
+    - type: ndcg_at_1000
+      value: 87.444
+    - type: ndcg_at_3
+      value: 82.788
+    - type: ndcg_at_5
+      value: 84.313
+    - type: precision_at_1
+      value: 78.63
+    - type: precision_at_10
+      value: 12.977
+    - type: precision_at_100
+      value: 1.503
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 36.113
+    - type: precision_at_5
+      value: 23.71
+    - type: recall_at_1
+      value: 68.232
+    - type: recall_at_10
+      value: 93.30199999999999
+    - type: recall_at_100
+      value: 98.799
+    - type: recall_at_1000
+      value: 99.885
+    - type: recall_at_3
+      value: 84.827
+    - type: recall_at_5
+      value: 89.188
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 45.71879170816294
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 59.65866311751794
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.218
+    - type: map_at_10
+      value: 10.337
+    - type: map_at_100
+      value: 12.131
+    - type: map_at_1000
+      value: 12.411
+    - type: map_at_3
+      value: 7.4270000000000005
+    - type: map_at_5
+      value: 8.913
+    - type: mrr_at_1
+      value: 20.8
+    - type: mrr_at_10
+      value: 30.868000000000002
+    - type: mrr_at_100
+      value: 31.903
+    - type: mrr_at_1000
+      value: 31.972
+    - type: mrr_at_3
+      value: 27.367
+    - type: mrr_at_5
+      value: 29.372
+    - type: ndcg_at_1
+      value: 20.8
+    - type: ndcg_at_10
+      value: 17.765
+    - type: ndcg_at_100
+      value: 24.914
+    - type: ndcg_at_1000
+      value: 30.206
+    - type: ndcg_at_3
+      value: 16.64
+    - type: ndcg_at_5
+      value: 14.712
+    - type: precision_at_1
+      value: 20.8
+    - type: precision_at_10
+      value: 9.24
+    - type: precision_at_100
+      value: 1.9560000000000002
+    - type: precision_at_1000
+      value: 0.32299999999999995
+    - type: precision_at_3
+      value: 15.467
+    - type: precision_at_5
+      value: 12.94
+    - type: recall_at_1
+      value: 4.218
+    - type: recall_at_10
+      value: 18.752
+    - type: recall_at_100
+      value: 39.7
+    - type: recall_at_1000
+      value: 65.57300000000001
+    - type: recall_at_3
+      value: 9.428
+    - type: recall_at_5
+      value: 13.133000000000001
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.04338850207233
+    - type: cos_sim_spearman
+      value: 78.5054651430423
+    - type: euclidean_pearson
+      value: 80.30739451228612
+    - type: euclidean_spearman
+      value: 78.48377464299097
+    - type: manhattan_pearson
+      value: 80.40795049052781
+    - type: manhattan_spearman
+      value: 78.49506205443114
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.11596224442962
+    - type: cos_sim_spearman
+      value: 76.20997388935461
+    - type: euclidean_pearson
+      value: 80.56858451349109
+    - type: euclidean_spearman
+      value: 75.92659183871186
+    - type: manhattan_pearson
+      value: 80.60246102203844
+    - type: manhattan_spearman
+      value: 76.03018971432664
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.34691640755737
+    - type: cos_sim_spearman
+      value: 82.4018369631579
+    - type: euclidean_pearson
+      value: 81.87673092245366
+    - type: euclidean_spearman
+      value: 82.3671489960678
+    - type: manhattan_pearson
+      value: 81.88222387719948
+    - type: manhattan_spearman
+      value: 82.3816590344736
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.2836092579524
+    - type: cos_sim_spearman
+      value: 78.99982781772064
+    - type: euclidean_pearson
+      value: 80.5184271010527
+    - type: euclidean_spearman
+      value: 78.89777392101904
+    - type: manhattan_pearson
+      value: 80.53585705018664
+    - type: manhattan_spearman
+      value: 78.92898405472994
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.7349907750784
+    - type: cos_sim_spearman
+      value: 87.7611234446225
+    - type: euclidean_pearson
+      value: 86.98759326731624
+    - type: euclidean_spearman
+      value: 87.58321319424618
+    - type: manhattan_pearson
+      value: 87.03483090370842
+    - type: manhattan_spearman
+      value: 87.63278333060288
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.75873694924825
+    - type: cos_sim_spearman
+      value: 83.80237999094724
+    - type: euclidean_pearson
+      value: 83.55023725861537
+    - type: euclidean_spearman
+      value: 84.12744338577744
+    - type: manhattan_pearson
+      value: 83.58816983036232
+    - type: manhattan_spearman
+      value: 84.18520748676501
+  - 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: 87.21630882940174
+    - type: cos_sim_spearman
+      value: 87.72382883437031
+    - type: euclidean_pearson
+      value: 88.69933350930333
+    - type: euclidean_spearman
+      value: 88.24660814383081
+    - type: manhattan_pearson
+      value: 88.77331018833499
+    - type: manhattan_spearman
+      value: 88.26109989380632
+  - 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: 61.11854063060489
+    - type: cos_sim_spearman
+      value: 63.14678634195072
+    - type: euclidean_pearson
+      value: 61.679090067000864
+    - type: euclidean_spearman
+      value: 62.28876589509653
+    - type: manhattan_pearson
+      value: 62.082324165511004
+    - type: manhattan_spearman
+      value: 62.56030932816679
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.00319882832645
+    - type: cos_sim_spearman
+      value: 85.94529772647257
+    - type: euclidean_pearson
+      value: 85.6661390122756
+    - type: euclidean_spearman
+      value: 85.97747815545827
+    - type: manhattan_pearson
+      value: 85.58422770541893
+    - type: manhattan_spearman
+      value: 85.9237139181532
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 79.16198731863916
+    - type: mrr
+      value: 94.25202702163487
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 54.761
+    - type: map_at_10
+      value: 64.396
+    - type: map_at_100
+      value: 65.07
+    - type: map_at_1000
+      value: 65.09899999999999
+    - type: map_at_3
+      value: 61.846000000000004
+    - type: map_at_5
+      value: 63.284
+    - type: mrr_at_1
+      value: 57.667
+    - type: mrr_at_10
+      value: 65.83099999999999
+    - type: mrr_at_100
+      value: 66.36800000000001
+    - type: mrr_at_1000
+      value: 66.39399999999999
+    - type: mrr_at_3
+      value: 64.056
+    - type: mrr_at_5
+      value: 65.206
+    - type: ndcg_at_1
+      value: 57.667
+    - type: ndcg_at_10
+      value: 68.854
+    - type: ndcg_at_100
+      value: 71.59100000000001
+    - type: ndcg_at_1000
+      value: 72.383
+    - type: ndcg_at_3
+      value: 64.671
+    - type: ndcg_at_5
+      value: 66.796
+    - type: precision_at_1
+      value: 57.667
+    - type: precision_at_10
+      value: 9.167
+    - type: precision_at_100
+      value: 1.053
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 25.444
+    - type: precision_at_5
+      value: 16.667
+    - type: recall_at_1
+      value: 54.761
+    - type: recall_at_10
+      value: 80.9
+    - type: recall_at_100
+      value: 92.767
+    - type: recall_at_1000
+      value: 99
+    - type: recall_at_3
+      value: 69.672
+    - type: recall_at_5
+      value: 75.083
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.8079207920792
+    - type: cos_sim_ap
+      value: 94.88470927617445
+    - type: cos_sim_f1
+      value: 90.08179959100204
+    - type: cos_sim_precision
+      value: 92.15481171548117
+    - type: cos_sim_recall
+      value: 88.1
+    - type: dot_accuracy
+      value: 99.58613861386138
+    - type: dot_ap
+      value: 82.94822578881316
+    - type: dot_f1
+      value: 77.33333333333333
+    - type: dot_precision
+      value: 79.36842105263158
+    - type: dot_recall
+      value: 75.4
+    - type: euclidean_accuracy
+      value: 99.8069306930693
+    - type: euclidean_ap
+      value: 94.81367858031837
+    - type: euclidean_f1
+      value: 90.01009081735621
+    - type: euclidean_precision
+      value: 90.83503054989816
+    - type: euclidean_recall
+      value: 89.2
+    - type: manhattan_accuracy
+      value: 99.81188118811882
+    - type: manhattan_ap
+      value: 94.91405337220161
+    - type: manhattan_f1
+      value: 90.2763561924258
+    - type: manhattan_precision
+      value: 92.45283018867924
+    - type: manhattan_recall
+      value: 88.2
+    - type: max_accuracy
+      value: 99.81188118811882
+    - type: max_ap
+      value: 94.91405337220161
+    - type: max_f1
+      value: 90.2763561924258
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 58.511599500053094
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 31.984728147814707
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 49.93428193939015
+    - type: mrr
+      value: 50.916557911043206
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.562500894537145
+    - type: cos_sim_spearman
+      value: 31.162587976726307
+    - type: dot_pearson
+      value: 22.633662187735762
+    - type: dot_spearman
+      value: 22.723000282378962
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.219
+    - type: map_at_10
+      value: 1.871
+    - type: map_at_100
+      value: 10.487
+    - type: map_at_1000
+      value: 25.122
+    - type: map_at_3
+      value: 0.657
+    - type: map_at_5
+      value: 1.0699999999999998
+    - type: mrr_at_1
+      value: 84
+    - type: mrr_at_10
+      value: 89.567
+    - type: mrr_at_100
+      value: 89.748
+    - type: mrr_at_1000
+      value: 89.748
+    - type: mrr_at_3
+      value: 88.667
+    - type: mrr_at_5
+      value: 89.567
+    - type: ndcg_at_1
+      value: 80
+    - type: ndcg_at_10
+      value: 74.533
+    - type: ndcg_at_100
+      value: 55.839000000000006
+    - type: ndcg_at_1000
+      value: 49.748
+    - type: ndcg_at_3
+      value: 79.53099999999999
+    - type: ndcg_at_5
+      value: 78.245
+    - type: precision_at_1
+      value: 84
+    - type: precision_at_10
+      value: 78.4
+    - type: precision_at_100
+      value: 56.99999999999999
+    - type: precision_at_1000
+      value: 21.98
+    - type: precision_at_3
+      value: 85.333
+    - type: precision_at_5
+      value: 84.8
+    - type: recall_at_1
+      value: 0.219
+    - type: recall_at_10
+      value: 2.02
+    - type: recall_at_100
+      value: 13.555
+    - type: recall_at_1000
+      value: 46.739999999999995
+    - type: recall_at_3
+      value: 0.685
+    - type: recall_at_5
+      value: 1.13
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 3.5029999999999997
+    - type: map_at_10
+      value: 11.042
+    - type: map_at_100
+      value: 16.326999999999998
+    - type: map_at_1000
+      value: 17.836
+    - type: map_at_3
+      value: 6.174
+    - type: map_at_5
+      value: 7.979
+    - type: mrr_at_1
+      value: 42.857
+    - type: mrr_at_10
+      value: 52.617000000000004
+    - type: mrr_at_100
+      value: 53.351000000000006
+    - type: mrr_at_1000
+      value: 53.351000000000006
+    - type: mrr_at_3
+      value: 46.939
+    - type: mrr_at_5
+      value: 50.714000000000006
+    - type: ndcg_at_1
+      value: 38.775999999999996
+    - type: ndcg_at_10
+      value: 27.125
+    - type: ndcg_at_100
+      value: 35.845
+    - type: ndcg_at_1000
+      value: 47.377
+    - type: ndcg_at_3
+      value: 29.633
+    - type: ndcg_at_5
+      value: 28.378999999999998
+    - type: precision_at_1
+      value: 42.857
+    - type: precision_at_10
+      value: 24.082
+    - type: precision_at_100
+      value: 6.877999999999999
+    - type: precision_at_1000
+      value: 1.463
+    - type: precision_at_3
+      value: 29.932
+    - type: precision_at_5
+      value: 28.571
+    - type: recall_at_1
+      value: 3.5029999999999997
+    - type: recall_at_10
+      value: 17.068
+    - type: recall_at_100
+      value: 43.361
+    - type: recall_at_1000
+      value: 78.835
+    - type: recall_at_3
+      value: 6.821000000000001
+    - type: recall_at_5
+      value: 10.357
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 71.0954
+    - type: ap
+      value: 14.216844153511959
+    - type: f1
+      value: 54.63687418565117
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 61.46293152235427
+    - type: f1
+      value: 61.744177921638645
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 41.12708617788644
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 85.75430649102938
+    - type: cos_sim_ap
+      value: 73.34252536948081
+    - type: cos_sim_f1
+      value: 67.53758935173774
+    - type: cos_sim_precision
+      value: 63.3672525439408
+    - type: cos_sim_recall
+      value: 72.29551451187335
+    - type: dot_accuracy
+      value: 81.71305954580676
+    - type: dot_ap
+      value: 59.5532209082386
+    - type: dot_f1
+      value: 56.18466898954705
+    - type: dot_precision
+      value: 47.830923248053395
+    - type: dot_recall
+      value: 68.07387862796834
+    - type: euclidean_accuracy
+      value: 85.81987244441795
+    - type: euclidean_ap
+      value: 73.34325409809446
+    - type: euclidean_f1
+      value: 67.83451360417443
+    - type: euclidean_precision
+      value: 64.09955388588871
+    - type: euclidean_recall
+      value: 72.0316622691293
+    - type: manhattan_accuracy
+      value: 85.68277999642368
+    - type: manhattan_ap
+      value: 73.1535450121903
+    - type: manhattan_f1
+      value: 67.928237896289
+    - type: manhattan_precision
+      value: 63.56945722171113
+    - type: manhattan_recall
+      value: 72.9287598944591
+    - type: max_accuracy
+      value: 85.81987244441795
+    - type: max_ap
+      value: 73.34325409809446
+    - type: max_f1
+      value: 67.928237896289
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.90441262079403
+    - type: cos_sim_ap
+      value: 85.79331880741438
+    - type: cos_sim_f1
+      value: 78.31563529842548
+    - type: cos_sim_precision
+      value: 74.6683424102779
+    - type: cos_sim_recall
+      value: 82.33754234678165
+    - type: dot_accuracy
+      value: 84.89928978926534
+    - type: dot_ap
+      value: 75.25819218316
+    - type: dot_f1
+      value: 69.88730119720536
+    - type: dot_precision
+      value: 64.23362374959665
+    - type: dot_recall
+      value: 76.63227594702803
+    - type: euclidean_accuracy
+      value: 89.01695967710637
+    - type: euclidean_ap
+      value: 85.98986606038852
+    - type: euclidean_f1
+      value: 78.5277880014722
+    - type: euclidean_precision
+      value: 75.22211253701876
+    - type: euclidean_recall
+      value: 82.13735756082538
+    - type: manhattan_accuracy
+      value: 88.99561454573679
+    - type: manhattan_ap
+      value: 85.92262421793953
+    - type: manhattan_f1
+      value: 78.38866094740769
+    - type: manhattan_precision
+      value: 76.02373028505282
+    - type: manhattan_recall
+      value: 80.9054511857099
+    - type: max_accuracy
+      value: 89.01695967710637
+    - type: max_ap
+      value: 85.98986606038852
+    - type: max_f1
+      value: 78.5277880014722
+language:
+- en
+license: mit
+---
+
+# E5-small-v2
+
+[Text Embeddings by Weakly-Supervised Contrastive Pre-training](https://arxiv.org/pdf/2212.03533.pdf).
+Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022
+
+This model has 12 layers and the embedding size is 384.
+
+## Usage
+
+Below is an example to encode queries and passages from the MS-MARCO passage ranking dataset.
+
+```python
+import torch.nn.functional as F
+
+from torch import Tensor
+from transformers import AutoTokenizer, AutoModel
+
+
+def average_pool(last_hidden_states: Tensor,
+                 attention_mask: Tensor) -> Tensor:
+    last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0)
+    return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None]
+
+
+# Each input text should start with "query: " or "passage: ".
+# For tasks other than retrieval, you can simply use the "query: " prefix.
+input_texts = ['query: how much protein should a female eat',
+               'query: summit define',
+               "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: Definition of summit for English Language Learners. : 1  the highest point of a mountain : the top of a mountain. : 2  the highest level. : 3  a meeting or series of meetings between the leaders of two or more governments."]
+
+tokenizer = AutoTokenizer.from_pretrained('intfloat/e5-small-v2')
+model = AutoModel.from_pretrained('intfloat/e5-small-v2')
+
+# 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())
+```
+
+## 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
+
+This model only works for English texts. Long texts will be truncated to at most 512 tokens.
+
+## Sentence Transformers
+
+Below is an example for usage with sentence_transformers. `pip install sentence_transformers~=2.2.2`
+This is community contributed, and results may vary up to numerical precision.
+```python
+from sentence_transformers import SentenceTransformer
+model = SentenceTransformer('intfloat/e5-small-v2')
+embeddings = model.encode(input_texts, normalize_embeddings=True)
+```

config.json

@@ -0,0 +1,6 @@
+{
+  "bos_token": "<s>",
+  "eos_token": "</s>",
+  "layer_norm_epsilon": 1e-12,
+  "unk_token": "[UNK]"
+}

model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5e879493b1a8969c853c56602b6f4233207663263a83b1a881cc0b35646df17a
+size 34433870

special_tokens_map.json

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

tokenizer_config.json

@@ -0,0 +1,15 @@
+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}