README.md

---
model-index:
- name: jasper_en_vision_language_v1
  results:
  - dataset:
      config: en-ext
      name: MTEB AmazonCounterfactualClassification (en-ext)
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      split: test
      type: mteb/amazon_counterfactual
    metrics:
    - type: accuracy
      value: 95.7271
    - type: f1
      value: 89.25450000000001
    - type: f1_weighted
      value: 95.8563
    - type: ap
      value: 67.1563
    - type: ap_weighted
      value: 67.1563
    - type: main_score
      value: 95.7271
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB AmazonCounterfactualClassification (en)
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      split: test
      type: mteb/amazon_counterfactual
    metrics:
    - type: accuracy
      value: 93.7761
    - type: f1
      value: 90.7582
    - type: f1_weighted
      value: 93.974
    - type: ap
      value: 74.88759999999999
    - type: ap_weighted
      value: 74.88759999999999
    - type: main_score
      value: 93.7761
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB AmazonPolarityClassification (default)
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
      split: test
      type: mteb/amazon_polarity
    metrics:
    - type: accuracy
      value: 97.5809
    - type: f1
      value: 97.5808
    - type: f1_weighted
      value: 97.5808
    - type: ap
      value: 96.3911
    - type: ap_weighted
      value: 96.3911
    - type: main_score
      value: 97.5809
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB AmazonReviewsClassification (en)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 62.918
    - type: f1
      value: 60.696099999999994
    - type: f1_weighted
      value: 60.696099999999994
    - type: main_score
      value: 62.918
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB ArguAna (default)
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
      split: test
      type: mteb/arguana
    metrics:
    - type: ndcg_at_1
      value: 41.323
    - type: ndcg_at_3
      value: 56.737
    - type: ndcg_at_5
      value: 61.254
    - type: ndcg_at_10
      value: 65.204
    - type: ndcg_at_20
      value: 66.75
    - type: ndcg_at_100
      value: 67.254
    - type: ndcg_at_1000
      value: 67.254
    - type: map_at_1
      value: 41.323
    - type: map_at_3
      value: 52.881
    - type: map_at_5
      value: 55.373000000000005
    - type: map_at_10
      value: 57.013999999999996
    - type: map_at_20
      value: 57.457
    - type: map_at_100
      value: 57.538
    - type: map_at_1000
      value: 57.538
    - type: recall_at_1
      value: 41.323
    - type: recall_at_3
      value: 67.923
    - type: recall_at_5
      value: 78.947
    - type: recall_at_10
      value: 91.11
    - type: recall_at_20
      value: 97.084
    - type: recall_at_100
      value: 99.644
    - type: recall_at_1000
      value: 99.644
    - type: precision_at_1
      value: 41.323
    - type: precision_at_3
      value: 22.641
    - type: precision_at_5
      value: 15.789
    - type: precision_at_10
      value: 9.110999999999999
    - type: precision_at_20
      value: 4.854
    - type: precision_at_100
      value: 0.996
    - type: precision_at_1000
      value: 0.1
    - type: mrr_at_1
      value: 41.6785
    - type: mrr_at_3
      value: 52.963499999999996
    - type: mrr_at_5
      value: 55.456399999999995
    - type: mrr_at_10
      value: 57.104299999999995
    - type: mrr_at_20
      value: 57.5402
    - type: mrr_at_100
      value: 57.6213
    - type: mrr_at_1000
      value: 57.6213
    - type: nauc_ndcg_at_1_max
      value: -12.633600000000001
    - type: nauc_ndcg_at_1_std
      value: -19.747700000000002
    - type: nauc_ndcg_at_1_diff1
      value: 25.820300000000003
    - type: nauc_ndcg_at_3_max
      value: -8.480799999999999
    - type: nauc_ndcg_at_3_std
      value: -18.928900000000002
    - type: nauc_ndcg_at_3_diff1
      value: 19.409499999999998
    - type: nauc_ndcg_at_5_max
      value: -7.9172
    - type: nauc_ndcg_at_5_std
      value: -19.2306
    - type: nauc_ndcg_at_5_diff1
      value: 18.5809
    - type: nauc_ndcg_at_10_max
      value: -9.7812
    - type: nauc_ndcg_at_10_std
      value: -19.9964
    - type: nauc_ndcg_at_10_diff1
      value: 18.0753
    - type: nauc_ndcg_at_20_max
      value: -8.6546
    - type: nauc_ndcg_at_20_std
      value: -19.3205
    - type: nauc_ndcg_at_20_diff1
      value: 20.1741
    - type: nauc_ndcg_at_100_max
      value: -9.376900000000001
    - type: nauc_ndcg_at_100_std
      value: -19.5093
    - type: nauc_ndcg_at_100_diff1
      value: 20.4997
    - type: nauc_ndcg_at_1000_max
      value: -9.376900000000001
    - type: nauc_ndcg_at_1000_std
      value: -19.5093
    - type: nauc_ndcg_at_1000_diff1
      value: 20.4997
    - type: nauc_map_at_1_max
      value: -12.633600000000001
    - type: nauc_map_at_1_std
      value: -19.747700000000002
    - type: nauc_map_at_1_diff1
      value: 25.820300000000003
    - type: nauc_map_at_3_max
      value: -9.5533
    - type: nauc_map_at_3_std
      value: -19.3235
    - type: nauc_map_at_3_diff1
      value: 20.9083
    - type: nauc_map_at_5_max
      value: -9.3126
    - type: nauc_map_at_5_std
      value: -19.4593
    - type: nauc_map_at_5_diff1
      value: 20.5718
    - type: nauc_map_at_10_max
      value: -10.0766
    - type: nauc_map_at_10_std
      value: -19.8322
    - type: nauc_map_at_10_diff1
      value: 20.484099999999998
    - type: nauc_map_at_20_max
      value: -9.7917
    - type: nauc_map_at_20_std
      value: -19.6759
    - type: nauc_map_at_20_diff1
      value: 21.0095
    - type: nauc_map_at_100_max
      value: -9.8837
    - type: nauc_map_at_100_std
      value: -19.741400000000002
    - type: nauc_map_at_100_diff1
      value: 21.067700000000002
    - type: nauc_map_at_1000_max
      value: -9.8837
    - type: nauc_map_at_1000_std
      value: -19.741400000000002
    - type: nauc_map_at_1000_diff1
      value: 21.067700000000002
    - type: nauc_recall_at_1_max
      value: -12.633600000000001
    - type: nauc_recall_at_1_std
      value: -19.747700000000002
    - type: nauc_recall_at_1_diff1
      value: 25.820300000000003
    - type: nauc_recall_at_3_max
      value: -4.7886999999999995
    - type: nauc_recall_at_3_std
      value: -17.4764
    - type: nauc_recall_at_3_diff1
      value: 14.3308
    - type: nauc_recall_at_5_max
      value: -1.4803
    - type: nauc_recall_at_5_std
      value: -18.2137
    - type: nauc_recall_at_5_diff1
      value: 9.4604
    - type: nauc_recall_at_10_max
      value: -8.8102
    - type: nauc_recall_at_10_std
      value: -21.8279
    - type: nauc_recall_at_10_diff1
      value: -5.5388
    - type: nauc_recall_at_20_max
      value: 25.202400000000004
    - type: nauc_recall_at_20_std
      value: -4.8613
    - type: nauc_recall_at_20_diff1
      value: 9.3917
    - type: nauc_recall_at_100_max
      value: 37.0551
    - type: nauc_recall_at_100_std
      value: 84.5472
    - type: nauc_recall_at_100_diff1
      value: 19.5116
    - type: nauc_recall_at_1000_max
      value: 37.0551
    - type: nauc_recall_at_1000_std
      value: 84.5472
    - type: nauc_recall_at_1000_diff1
      value: 19.5116
    - type: nauc_precision_at_1_max
      value: -12.633600000000001
    - type: nauc_precision_at_1_std
      value: -19.747700000000002
    - type: nauc_precision_at_1_diff1
      value: 25.820300000000003
    - type: nauc_precision_at_3_max
      value: -4.7886999999999995
    - type: nauc_precision_at_3_std
      value: -17.4764
    - type: nauc_precision_at_3_diff1
      value: 14.3308
    - type: nauc_precision_at_5_max
      value: -1.4803
    - type: nauc_precision_at_5_std
      value: -18.2137
    - type: nauc_precision_at_5_diff1
      value: 9.4604
    - type: nauc_precision_at_10_max
      value: -8.8102
    - type: nauc_precision_at_10_std
      value: -21.8279
    - type: nauc_precision_at_10_diff1
      value: -5.5388
    - type: nauc_precision_at_20_max
      value: 25.202400000000004
    - type: nauc_precision_at_20_std
      value: -4.8613
    - type: nauc_precision_at_20_diff1
      value: 9.3917
    - type: nauc_precision_at_100_max
      value: 37.0551
    - type: nauc_precision_at_100_std
      value: 84.5472
    - type: nauc_precision_at_100_diff1
      value: 19.5116
    - type: nauc_precision_at_1000_max
      value: 37.0551
    - type: nauc_precision_at_1000_std
      value: 84.5472
    - type: nauc_precision_at_1000_diff1
      value: 19.5116
    - type: nauc_mrr_at_1_max
      value: -11.9728
    - type: nauc_mrr_at_1_std
      value: -19.4014
    - type: nauc_mrr_at_1_diff1
      value: 24.8653
    - type: nauc_mrr_at_3_max
      value: -9.6607
    - type: nauc_mrr_at_3_std
      value: -19.1819
    - type: nauc_mrr_at_3_diff1
      value: 20.0205
    - type: nauc_mrr_at_5_max
      value: -9.4261
    - type: nauc_mrr_at_5_std
      value: -19.3098
    - type: nauc_mrr_at_5_diff1
      value: 19.6347
    - type: nauc_mrr_at_10_max
      value: -10.1698
    - type: nauc_mrr_at_10_std
      value: -19.683
    - type: nauc_mrr_at_10_diff1
      value: 19.4823
    - type: nauc_mrr_at_20_max
      value: -9.913
    - type: nauc_mrr_at_20_std
      value: -19.517300000000002
    - type: nauc_mrr_at_20_diff1
      value: 20.0066
    - type: nauc_mrr_at_100_max
      value: -10.0053
    - type: nauc_mrr_at_100_std
      value: -19.5824
    - type: nauc_mrr_at_100_diff1
      value: 20.061899999999998
    - type: nauc_mrr_at_1000_max
      value: -10.0053
    - type: nauc_mrr_at_1000_std
      value: -19.5824
    - type: nauc_mrr_at_1000_diff1
      value: 20.061899999999998
    - type: main_score
      value: 65.204
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB ArxivClusteringP2P (default)
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
      split: test
      type: mteb/arxiv-clustering-p2p
    metrics:
    - type: v_measure
      value: 55.710300000000004
    - type: v_measure_std
      value: 14.551900000000002
    - type: main_score
      value: 55.710300000000004
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB ArxivClusteringS2S (default)
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
      split: test
      type: mteb/arxiv-clustering-s2s
    metrics:
    - type: v_measure
      value: 51.004599999999996
    - type: v_measure_std
      value: 14.868899999999998
    - type: main_score
      value: 51.004599999999996
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB AskUbuntuDupQuestions (default)
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
      split: test
      type: mteb/askubuntudupquestions-reranking
    metrics:
    - type: map
      value: 67.38119999999999
    - type: mrr
      value: 79.0692
    - type: nAUC_map_max
      value: 21.9757
    - type: nAUC_map_std
      value: 14.3545
    - type: nAUC_map_diff1
      value: 11.82
    - type: nAUC_mrr_max
      value: 40.3449
    - type: nAUC_mrr_std
      value: 18.2678
    - type: nAUC_mrr_diff1
      value: 21.1596
    - type: main_score
      value: 67.38119999999999
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB BIOSSES (default)
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
      split: test
      type: mteb/biosses-sts
    metrics:
    - type: pearson
      value: 87.4332
    - type: spearman
      value: 84.65979999999999
    - type: cosine_pearson
      value: 87.4332
    - type: cosine_spearman
      value: 84.65979999999999
    - type: manhattan_pearson
      value: 86.37270000000001
    - type: manhattan_spearman
      value: 85.20309999999999
    - type: euclidean_pearson
      value: 86.1672
    - type: euclidean_spearman
      value: 84.7453
    - type: main_score
      value: 84.65979999999999
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB Banking77Classification (default)
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
      split: test
      type: mteb/banking77
    metrics:
    - type: accuracy
      value: 87.224
    - type: f1
      value: 86.7235
    - type: f1_weighted
      value: 86.7235
    - type: main_score
      value: 87.224
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB BiorxivClusteringP2P (default)
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
      split: test
      type: mteb/biorxiv-clustering-p2p
    metrics:
    - type: v_measure
      value: 52.04990000000001
    - type: v_measure_std
      value: 0.7255
    - type: main_score
      value: 52.04990000000001
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB BiorxivClusteringS2S (default)
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
      split: test
      type: mteb/biorxiv-clustering-s2s
    metrics:
    - type: v_measure
      value: 47.5811
    - type: v_measure_std
      value: 0.8049000000000001
    - type: main_score
      value: 47.5811
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB CQADupstackAndroidRetrieval (default)
      revision: f46a197baaae43b4f621051089b82a364682dfeb
      split: test
      type: mteb/cqadupstack-android
    metrics:
    - type: ndcg_at_1
      value: 46.781
    - type: ndcg_at_3
      value: 52.111
    - type: ndcg_at_5
      value: 54.371
    - type: ndcg_at_10
      value: 57.247
    - type: ndcg_at_20
      value: 59.122
    - type: ndcg_at_100
      value: 62.071
    - type: ndcg_at_1000
      value: 63.32
    - type: map_at_1
      value: 37.2
    - type: map_at_3
      value: 46.005
    - type: map_at_5
      value: 48.32
    - type: map_at_10
      value: 50.181
    - type: map_at_20
      value: 51.062
    - type: map_at_100
      value: 51.735
    - type: map_at_1000
      value: 51.842
    - type: recall_at_1
      value: 37.2
    - type: recall_at_3
      value: 53.94
    - type: recall_at_5
      value: 60.88
    - type: recall_at_10
      value: 69.692
    - type: recall_at_20
      value: 76.711
    - type: recall_at_100
      value: 90.263
    - type: recall_at_1000
      value: 97.749
    - type: precision_at_1
      value: 46.781
    - type: precision_at_3
      value: 25.894000000000002
    - type: precision_at_5
      value: 18.541
    - type: precision_at_10
      value: 11.402
    - type: precision_at_20
      value: 6.567
    - type: precision_at_100
      value: 1.704
    - type: precision_at_1000
      value: 0.21
    - type: mrr_at_1
      value: 46.781099999999995
    - type: mrr_at_3
      value: 54.6257
    - type: mrr_at_5
      value: 56.0992
    - type: mrr_at_10
      value: 57.00769999999999
    - type: mrr_at_20
      value: 57.3576
    - type: mrr_at_100
      value: 57.6118
    - type: mrr_at_1000
      value: 57.6415
    - type: nauc_ndcg_at_1_max
      value: 41.3069
    - type: nauc_ndcg_at_1_std
      value: -3.9859999999999998
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      value: 56.355900000000005
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      value: 40.354299999999995
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      value: -1.4893
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      value: 51.473800000000004
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      value: 39.2091
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      value: -2.6139
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      value: 50.4382
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      value: 37.8136
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      value: -1.9053
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      value: 51.0321
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      value: 31.1237
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      value: -7.0686
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      value: 55.28189999999999
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      value: -4.502599999999999
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    - type: nauc_map_at_1000_diff1
      value: 51.807
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      value: -7.0686
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      value: 55.28189999999999
    - type: nauc_recall_at_3_max
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    - type: nauc_recall_at_3_std
      value: -2.1842
    - type: nauc_recall_at_3_diff1
      value: 46.806
    - type: nauc_recall_at_5_max
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    - type: nauc_recall_at_10_max
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    - type: nauc_recall_at_20_max
      value: 27.1235
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      value: 2.8238
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      value: 36.9813
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      type: Retrieval
  - dataset:
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      name: MTEB ImdbClassification (default)
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
      split: test
      type: mteb/imdb
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    task:
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  - dataset:
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      revision: c5a29a104738b98a9e76336939199e264163d4a0
      split: test
      type: mteb/msmarco
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    task:
      type: Retrieval
  - dataset:
      config: en
      name: MTEB MTOPDomainClassification (en)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
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      value: 99.1712
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      value: 99.1701
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MTOPIntentClassification (en)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
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      value: 72.55080000000001
    - type: f1_weighted
      value: 91.72449999999999
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      value: 91.48429999999999
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MassiveIntentClassification (en)
      revision: 4672e20407010da34463acc759c162ca9734bca6
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 85.306
    - type: f1
      value: 83.1076
    - type: f1_weighted
      value: 84.4685
    - type: main_score
      value: 85.306
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MassiveScenarioClassification (en)
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
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      value: 90.15950000000001
    - type: f1_weighted
      value: 90.802
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      value: 91.17349999999999
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB MedrxivClusteringP2P (default)
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
      split: test
      type: mteb/medrxiv-clustering-p2p
    metrics:
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      value: 1.2241
    - type: main_score
      value: 46.7494
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MedrxivClusteringS2S (default)
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
      split: test
      type: mteb/medrxiv-clustering-s2s
    metrics:
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      value: 44.9016
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      value: 1.3978000000000002
    - type: main_score
      value: 44.9016
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MindSmallReranking (default)
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
      split: test
      type: mteb/mind_small
    metrics:
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      value: -21.0204
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      value: -5.1638
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      value: 10.4531
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      value: -15.85
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      value: -2.7011
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      value: 9.8352
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      value: 32.628099999999996
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB NFCorpus (default)
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
      split: test
      type: mteb/nfcorpus
    metrics:
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      value: 54.954
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      value: 49.876
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      value: 47.038999999999994
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      value: 43.313
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      value: 41.086
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      value: 40.849999999999994
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      value: 49.852000000000004
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      value: 7.412000000000001
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      value: 12.438
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      value: 14.448
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      value: 19.273
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      value: 22.494
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      value: 24.490000000000002
    - type: recall_at_1
      value: 7.412000000000001
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      value: 13.682
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      value: 16.595
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      value: 21.726
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      value: 26.895999999999997
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      value: 42.345
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      value: 74.752
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      value: 46.646
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      value: 40.619
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      value: 24.195
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      value: 77.9596
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      value: 25.3507
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    - type: nauc_recall_at_3_max
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    - type: nauc_recall_at_3_std
      value: -62.044399999999996
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    - type: nauc_recall_at_5_max
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      value: -68.6455
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    - type: nauc_recall_at_100_max
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      value: -2.321
    - type: nauc_precision_at_10_std
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    - type: nauc_precision_at_20_max
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    - type: nauc_precision_at_20_std
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    - type: nauc_precision_at_100_max
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      value: 40.402100000000004
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      value: -46.054
    - type: nauc_mrr_at_1_max
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      value: -42.5286
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      value: 79.3747
    - type: nauc_mrr_at_3_max
      value: 36.3166
    - type: nauc_mrr_at_3_std
      value: -45.0789
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      value: 78.3276
    - type: nauc_mrr_at_5_max
      value: 36.365700000000004
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      value: -45.1793
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      value: 78.5424
    - type: nauc_mrr_at_10_max
      value: 36.3128
    - type: nauc_mrr_at_10_std
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    - type: nauc_mrr_at_10_diff1
      value: 78.5756
    - type: nauc_mrr_at_20_max
      value: 36.327
    - type: nauc_mrr_at_20_std
      value: -44.853500000000004
    - type: nauc_mrr_at_20_diff1
      value: 78.57220000000001
    - type: nauc_mrr_at_100_max
      value: 36.3322
    - type: nauc_mrr_at_100_std
      value: -44.8025
    - type: nauc_mrr_at_100_diff1
      value: 78.57730000000001
    - type: nauc_mrr_at_1000_max
      value: 36.3314
    - type: nauc_mrr_at_1000_std
      value: -44.804100000000005
    - type: nauc_mrr_at_1000_diff1
      value: 78.5778
    - type: main_score
      value: 90.038
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB RedditClustering (default)
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
      split: test
      type: mteb/reddit-clustering
    metrics:
    - type: v_measure
      value: 73.0223
    - type: v_measure_std
      value: 2.5644
    - type: main_score
      value: 73.0223
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB RedditClusteringP2P (default)
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
      split: test
      type: mteb/reddit-clustering-p2p
    metrics:
    - type: v_measure
      value: 74.7154
    - type: v_measure_std
      value: 8.2851
    - type: main_score
      value: 74.7154
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB SCIDOCS (default)
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
      split: test
      type: mteb/scidocs
    metrics:
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      value: 29.099999999999998
    - type: ndcg_at_3
      value: 22.891000000000002
    - type: ndcg_at_5
      value: 20.055
    - type: ndcg_at_10
      value: 24.637999999999998
    - type: ndcg_at_20
      value: 28.188999999999997
    - type: ndcg_at_100
      value: 34.589
    - type: ndcg_at_1000
      value: 39.93
    - type: map_at_1
      value: 5.903
    - type: map_at_3
      value: 10.375
    - type: map_at_5
      value: 12.503
    - type: map_at_10
      value: 14.997
    - type: map_at_20
      value: 16.383
    - type: map_at_100
      value: 17.769
    - type: map_at_1000
      value: 18.115000000000002
    - type: recall_at_1
      value: 5.903
    - type: recall_at_3
      value: 12.943
    - type: recall_at_5
      value: 17.818
    - type: recall_at_10
      value: 26.162999999999997
    - type: recall_at_20
      value: 34.46
    - type: recall_at_100
      value: 55.24
    - type: recall_at_1000
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    - type: precision_at_1
      value: 29.099999999999998
    - type: precision_at_3
      value: 21.3
    - type: precision_at_5
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    - type: precision_at_10
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    - type: precision_at_20
      value: 8.5
    - type: precision_at_100
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    - type: precision_at_1000
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    - type: mrr_at_1
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    - type: mrr_at_3
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    - type: mrr_at_5
      value: 38.9617
    - type: mrr_at_10
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    - type: mrr_at_20
      value: 41.3132
    - type: mrr_at_100
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    - type: mrr_at_1000
      value: 41.7584
    - type: nauc_ndcg_at_1_max
      value: 18.4908
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      value: 8.3766
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      value: 22.0483
    - type: nauc_ndcg_at_3_max
      value: 19.1712
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      value: 10.407399999999999
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    - type: nauc_ndcg_at_5_max
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      value: 11.8195
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      value: 16.4224
    - type: nauc_ndcg_at_10_max
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    - type: nauc_ndcg_at_20_max
      value: 21.5015
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      value: 17.292199999999998
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      value: 23.2308
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      value: 22.425800000000002
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      value: 22.764499999999998
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      value: 12.540000000000001
    - type: nauc_map_at_1_max
      value: 17.8236
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      value: 8.1625
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      value: 21.8362
    - type: nauc_map_at_3_max
      value: 19.1677
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      value: 16.2302
    - type: nauc_map_at_5_max
      value: 20.3156
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      value: 10.6218
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      value: 16.2404
    - type: nauc_map_at_10_max
      value: 20.2029
    - type: nauc_map_at_10_std
      value: 12.9342
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      value: 14.7992
    - type: nauc_map_at_20_max
      value: 20.7278
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      value: 16.746
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    - type: nauc_recall_at_1_max
      value: 17.8236
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      value: 21.8362
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      value: 18.5764
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    - type: nauc_recall_at_20_max
      value: 19.9903
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    - type: nauc_recall_at_1000_max
      value: 20.188
    - type: nauc_recall_at_1000_std
      value: 39.786
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      value: -4.0011
    - type: nauc_precision_at_1_max
      value: 18.4908
    - type: nauc_precision_at_1_std
      value: 8.3766
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      value: 22.0483
    - type: nauc_precision_at_3_max
      value: 19.178600000000003
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      value: 11.6744
    - type: nauc_precision_at_3_diff1
      value: 13.5931
    - type: nauc_precision_at_5_max
      value: 20.4581
    - type: nauc_precision_at_5_std
      value: 13.5076
    - type: nauc_precision_at_5_diff1
      value: 13.619600000000002
    - type: nauc_precision_at_10_max
      value: 19.437099999999997
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      value: 17.754900000000003
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      value: 10.6315
    - type: nauc_precision_at_20_max
      value: 20.9159
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      value: 21.9286
    - type: nauc_precision_at_20_diff1
      value: 8.251
    - type: nauc_precision_at_100_max
      value: 22.2412
    - type: nauc_precision_at_100_std
      value: 32.925900000000006
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      value: 1.5637999999999999
    - type: nauc_precision_at_1000_max
      value: 22.1
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      value: 37.227700000000006
    - type: nauc_precision_at_1000_diff1
      value: -2.3548
    - type: nauc_mrr_at_1_max
      value: 18.4908
    - type: nauc_mrr_at_1_std
      value: 8.3766
    - type: nauc_mrr_at_1_diff1
      value: 22.0483
    - type: nauc_mrr_at_3_max
      value: 18.3602
    - type: nauc_mrr_at_3_std
      value: 9.579600000000001
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      value: 18.7544
    - type: nauc_mrr_at_5_max
      value: 18.5224
    - type: nauc_mrr_at_5_std
      value: 9.747300000000001
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      value: 19.0625
    - type: nauc_mrr_at_10_max
      value: 19.067
    - type: nauc_mrr_at_10_std
      value: 10.7103
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      value: 19.444
    - type: nauc_mrr_at_20_max
      value: 19.118399999999998
    - type: nauc_mrr_at_20_std
      value: 10.6384
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      value: 19.5223
    - type: nauc_mrr_at_100_max
      value: 19.200300000000002
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      value: 10.6891
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      value: 19.4009
    - type: nauc_mrr_at_1000_max
      value: 19.1676
    - type: nauc_mrr_at_1000_std
      value: 10.649799999999999
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      value: 19.4127
    - type: main_score
      value: 24.637999999999998
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SICK-R (default)
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
      split: test
      type: mteb/sickr-sts
    metrics:
    - type: pearson
      value: 86.8981
    - type: spearman
      value: 82.234
    - type: cosine_pearson
      value: 86.8981
    - type: cosine_spearman
      value: 82.234
    - type: manhattan_pearson
      value: 84.1165
    - type: manhattan_spearman
      value: 82.063
    - type: euclidean_pearson
      value: 84.0688
    - type: euclidean_spearman
      value: 82.2329
    - type: main_score
      value: 82.234
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS12 (default)
      revision: a0d554a64d88156834ff5ae9920b964011b16384
      split: test
      type: mteb/sts12-sts
    metrics:
    - type: pearson
      value: 87.8269
    - type: spearman
      value: 80.2578
    - type: cosine_pearson
      value: 87.8269
    - type: cosine_spearman
      value: 80.2578
    - type: manhattan_pearson
      value: 85.09020000000001
    - type: manhattan_spearman
      value: 80.5777
    - type: euclidean_pearson
      value: 84.71990000000001
    - type: euclidean_spearman
      value: 80.2547
    - type: main_score
      value: 80.2578
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS13 (default)
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
      split: test
      type: mteb/sts13-sts
    metrics:
    - type: pearson
      value: 89.45769999999999
    - type: spearman
      value: 89.69200000000001
    - type: cosine_pearson
      value: 89.45769999999999
    - type: cosine_spearman
      value: 89.69200000000001
    - type: manhattan_pearson
      value: 89.1685
    - type: manhattan_spearman
      value: 89.8889
    - type: euclidean_pearson
      value: 89.07969999999999
    - type: euclidean_spearman
      value: 89.7003
    - type: main_score
      value: 89.69200000000001
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS14 (default)
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
      split: test
      type: mteb/sts14-sts
    metrics:
    - type: pearson
      value: 87.01989999999999
    - type: spearman
      value: 85.3155
    - type: cosine_pearson
      value: 87.01989999999999
    - type: cosine_spearman
      value: 85.3155
    - type: manhattan_pearson
      value: 86.24159999999999
    - type: manhattan_spearman
      value: 85.544
    - type: euclidean_pearson
      value: 86.1032
    - type: euclidean_spearman
      value: 85.31490000000001
    - type: main_score
      value: 85.3155
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS15 (default)
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
      split: test
      type: mteb/sts15-sts
    metrics:
    - type: pearson
      value: 89.593
    - type: spearman
      value: 90.1574
    - type: cosine_pearson
      value: 89.593
    - type: cosine_spearman
      value: 90.1574
    - type: manhattan_pearson
      value: 89.93910000000001
    - type: manhattan_spearman
      value: 90.4357
    - type: euclidean_pearson
      value: 89.76650000000001
    - type: euclidean_spearman
      value: 90.1554
    - type: main_score
      value: 90.1574
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS16 (default)
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
      split: test
      type: mteb/sts16-sts
    metrics:
    - type: pearson
      value: 85.03540000000001
    - type: spearman
      value: 86.4191
    - type: cosine_pearson
      value: 85.03540000000001
    - type: cosine_spearman
      value: 86.4191
    - type: manhattan_pearson
      value: 85.8992
    - type: manhattan_spearman
      value: 86.7274
    - type: euclidean_pearson
      value: 85.638
    - type: euclidean_spearman
      value: 86.42
    - type: main_score
      value: 86.4191
    task:
      type: STS
  - dataset:
      config: en-ar
      name: MTEB STS17 (en-ar)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: pearson
      value: 54.1098
    - type: spearman
      value: 52.721
    - type: cosine_pearson
      value: 54.1098
    - type: cosine_spearman
      value: 52.721
    - type: manhattan_pearson
      value: 54.890899999999995
    - type: manhattan_spearman
      value: 52.727900000000005
    - type: euclidean_pearson
      value: 54.65410000000001
    - type: euclidean_spearman
      value: 52.8582
    - type: main_score
      value: 52.721
    task:
      type: STS
  - dataset:
      config: fr-en
      name: MTEB STS17 (fr-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: pearson
      value: 84.3262
    - type: spearman
      value: 84.1421
    - type: cosine_pearson
      value: 84.3262
    - type: cosine_spearman
      value: 84.1421
    - type: manhattan_pearson
      value: 83.8999
    - type: manhattan_spearman
      value: 83.9987
    - type: euclidean_pearson
      value: 84.0174
    - type: euclidean_spearman
      value: 84.1711
    - type: main_score
      value: 84.1421
    task:
      type: STS
  - dataset:
      config: en-en
      name: MTEB STS17 (en-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: pearson
      value: 91.38969999999999
    - type: spearman
      value: 91.00789999999999
    - type: cosine_pearson
      value: 91.38969999999999
    - type: cosine_spearman
      value: 91.00789999999999
    - type: manhattan_pearson
      value: 90.8917
    - type: manhattan_spearman
      value: 90.7834
    - type: euclidean_pearson
      value: 91.0361
    - type: euclidean_spearman
      value: 91.011
    - type: main_score
      value: 91.00789999999999
    task:
      type: STS
  - dataset:
      config: nl-en
      name: MTEB STS17 (nl-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: pearson
      value: 84.636
    - type: spearman
      value: 84.1977
    - type: cosine_pearson
      value: 84.636
    - type: cosine_spearman
      value: 84.1977
    - type: manhattan_pearson
      value: 84.6895
    - type: manhattan_spearman
      value: 84.1849
    - type: euclidean_pearson
      value: 84.753
    - type: euclidean_spearman
      value: 84.2251
    - type: main_score
      value: 84.1977
    task:
      type: STS
  - dataset:
      config: es-en
      name: MTEB STS17 (es-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: pearson
      value: 85.8595
    - type: spearman
      value: 86.9965
    - type: cosine_pearson
      value: 85.8595
    - type: cosine_spearman
      value: 86.9965
    - type: manhattan_pearson
      value: 86.92450000000001
    - type: manhattan_spearman
      value: 87.39489999999999
    - type: euclidean_pearson
      value: 86.5575
    - type: euclidean_spearman
      value: 86.997
    - type: main_score
      value: 86.9965
    task:
      type: STS
  - dataset:
      config: it-en
      name: MTEB STS17 (it-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: pearson
      value: 85.959
    - type: spearman
      value: 86.3103
    - type: cosine_pearson
      value: 85.959
    - type: cosine_spearman
      value: 86.3103
    - type: manhattan_pearson
      value: 85.7486
    - type: manhattan_spearman
      value: 86.0977
    - type: euclidean_pearson
      value: 85.8361
    - type: euclidean_spearman
      value: 86.2741
    - type: main_score
      value: 86.3103
    task:
      type: STS
  - dataset:
      config: en-de
      name: MTEB STS17 (en-de)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: pearson
      value: 86.2629
    - type: spearman
      value: 85.8372
    - type: cosine_pearson
      value: 86.2629
    - type: cosine_spearman
      value: 85.8372
    - type: manhattan_pearson
      value: 86.2491
    - type: manhattan_spearman
      value: 85.4973
    - type: euclidean_pearson
      value: 86.5074
    - type: euclidean_spearman
      value: 85.83370000000001
    - type: main_score
      value: 85.8372
    task:
      type: STS
  - dataset:
      config: en-tr
      name: MTEB STS17 (en-tr)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: pearson
      value: 57.5675
    - type: spearman
      value: 55.564899999999994
    - type: cosine_pearson
      value: 57.5675
    - type: cosine_spearman
      value: 55.564899999999994
    - type: manhattan_pearson
      value: 57.4686
    - type: manhattan_spearman
      value: 55.3816
    - type: euclidean_pearson
      value: 57.635099999999994
    - type: euclidean_spearman
      value: 55.501900000000006
    - type: main_score
      value: 55.564899999999994
    task:
      type: STS
  - dataset:
      config: pl-en
      name: MTEB STS22 (pl-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: pearson
      value: 76.1237
    - type: spearman
      value: 76.4
    - type: cosine_pearson
      value: 76.1237
    - type: cosine_spearman
      value: 76.4
    - type: manhattan_pearson
      value: 78.6794
    - type: manhattan_spearman
      value: 77.2282
    - type: euclidean_pearson
      value: 77.1688
    - type: euclidean_spearman
      value: 76.4
    - type: main_score
      value: 76.4
    task:
      type: STS
  - dataset:
      config: es-en
      name: MTEB STS22 (es-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: pearson
      value: 73.89099999999999
    - type: spearman
      value: 77.8292
    - type: cosine_pearson
      value: 73.89099999999999
    - type: cosine_spearman
      value: 77.8292
    - type: manhattan_pearson
      value: 77.53229999999999
    - type: manhattan_spearman
      value: 78.3926
    - type: euclidean_pearson
      value: 76.6734
    - type: euclidean_spearman
      value: 77.8721
    - type: main_score
      value: 77.8292
    task:
      type: STS
  - dataset:
      config: en
      name: MTEB STS22 (en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: pearson
      value: 68.31099999999999
    - type: spearman
      value: 68.0764
    - type: cosine_pearson
      value: 68.31099999999999
    - type: cosine_spearman
      value: 68.0764
    - type: manhattan_pearson
      value: 69.7423
    - type: manhattan_spearman
      value: 68.3212
    - type: euclidean_pearson
      value: 69.5701
    - type: euclidean_spearman
      value: 68.2299
    - type: main_score
      value: 68.0764
    task:
      type: STS
  - dataset:
      config: de-en
      name: MTEB STS22 (de-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: pearson
      value: 65.0636
    - type: spearman
      value: 59.4669
    - type: cosine_pearson
      value: 65.0636
    - type: cosine_spearman
      value: 59.4669
    - type: manhattan_pearson
      value: 69.723
    - type: manhattan_spearman
      value: 60.3823
    - type: euclidean_pearson
      value: 68.6454
    - type: euclidean_spearman
      value: 59.384899999999995
    - type: main_score
      value: 59.4669
    task:
      type: STS
  - dataset:
      config: zh-en
      name: MTEB STS22 (zh-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: pearson
      value: 73.7603
    - type: spearman
      value: 73.0799
    - type: cosine_pearson
      value: 73.7603
    - type: cosine_spearman
      value: 73.0799
    - type: manhattan_pearson
      value: 76.2351
    - type: manhattan_spearman
      value: 73.60719999999999
    - type: euclidean_pearson
      value: 75.61529999999999
    - type: euclidean_spearman
      value: 72.9809
    - type: main_score
      value: 73.0799
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STSBenchmark (default)
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
      split: test
      type: mteb/stsbenchmark-sts
    metrics:
    - type: pearson
      value: 88.1242
    - type: spearman
      value: 88.8456
    - type: cosine_pearson
      value: 88.1242
    - type: cosine_spearman
      value: 88.8456
    - type: manhattan_pearson
      value: 88.6122
    - type: manhattan_spearman
      value: 89.0198
    - type: euclidean_pearson
      value: 88.5314
    - type: euclidean_spearman
      value: 88.8432
    - type: main_score
      value: 88.8456
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB SciDocsRR (default)
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
      split: test
      type: mteb/scidocs-reranking
    metrics:
    - type: map
      value: 89.06920000000001
    - type: mrr
      value: 96.977
    - type: nAUC_map_max
      value: 49.1778
    - type: nAUC_map_std
      value: 62.091499999999996
    - type: nAUC_map_diff1
      value: -13.373899999999999
    - type: nAUC_mrr_max
      value: 86.7325
    - type: nAUC_mrr_std
      value: 74.958
    - type: nAUC_mrr_diff1
      value: 25.6955
    - type: main_score
      value: 89.06920000000001
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SciFact (default)
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
      split: test
      type: mteb/scifact
    metrics:
    - type: ndcg_at_1
      value: 67.333
    - type: ndcg_at_3
      value: 75.142
    - type: ndcg_at_5
      value: 78.873
    - type: ndcg_at_10
      value: 80.372
    - type: ndcg_at_20
      value: 80.914
    - type: ndcg_at_100
      value: 81.563
    - type: ndcg_at_1000
      value: 81.601
    - type: map_at_1
      value: 63.99399999999999
    - type: map_at_3
      value: 72.181
    - type: map_at_5
      value: 74.665
    - type: map_at_10
      value: 75.51299999999999
    - type: map_at_20
      value: 75.693
    - type: map_at_100
      value: 75.78
    - type: map_at_1000
      value: 75.78099999999999
    - type: recall_at_1
      value: 63.99399999999999
    - type: recall_at_3
      value: 80.63900000000001
    - type: recall_at_5
      value: 90.017
    - type: recall_at_10
      value: 94.167
    - type: recall_at_20
      value: 96.167
    - type: recall_at_100
      value: 99.667
    - type: recall_at_1000
      value: 100.0
    - type: precision_at_1
      value: 67.333
    - type: precision_at_3
      value: 29.444
    - type: precision_at_5
      value: 20.067
    - type: precision_at_10
      value: 10.667
    - type: precision_at_20
      value: 5.45
    - type: precision_at_100
      value: 1.127
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: mrr_at_1
      value: 67.3333
    - type: mrr_at_3
      value: 73.9444
    - type: mrr_at_5
      value: 76.0444
    - type: mrr_at_10
      value: 76.4517
    - type: mrr_at_20
      value: 76.5739
    - type: mrr_at_100
      value: 76.6556
    - type: mrr_at_1000
      value: 76.6563
    - type: nauc_ndcg_at_1_max
      value: 55.373099999999994
    - type: nauc_ndcg_at_1_std
      value: -11.362
    - type: nauc_ndcg_at_1_diff1
      value: 81.5232
    - type: nauc_ndcg_at_3_max
      value: 58.0376
    - type: nauc_ndcg_at_3_std
      value: -14.4854
    - type: nauc_ndcg_at_3_diff1
      value: 77.848
    - type: nauc_ndcg_at_5_max
      value: 55.789699999999996
    - type: nauc_ndcg_at_5_std
      value: -15.0412
    - type: nauc_ndcg_at_5_diff1
      value: 77.7873
    - type: nauc_ndcg_at_10_max
      value: 58.6243
    - type: nauc_ndcg_at_10_std
      value: -13.867799999999999
    - type: nauc_ndcg_at_10_diff1
      value: 78.071
    - type: nauc_ndcg_at_20_max
      value: 58.9032
    - type: nauc_ndcg_at_20_std
      value: -12.7998
    - type: nauc_ndcg_at_20_diff1
      value: 78.12010000000001
    - type: nauc_ndcg_at_100_max
      value: 58.0772
    - type: nauc_ndcg_at_100_std
      value: -12.4604
    - type: nauc_ndcg_at_100_diff1
      value: 78.7002
    - type: nauc_ndcg_at_1000_max
      value: 58.0835
    - type: nauc_ndcg_at_1000_std
      value: -12.662799999999999
    - type: nauc_ndcg_at_1000_diff1
      value: 78.7157
    - type: nauc_map_at_1_max
      value: 45.2711
    - type: nauc_map_at_1_std
      value: -21.685
    - type: nauc_map_at_1_diff1
      value: 80.8536
    - type: nauc_map_at_3_max
      value: 53.970600000000005
    - type: nauc_map_at_3_std
      value: -18.0178
    - type: nauc_map_at_3_diff1
      value: 78.95309999999999
    - type: nauc_map_at_5_max
      value: 54.7643
    - type: nauc_map_at_5_std
      value: -15.943999999999999
    - type: nauc_map_at_5_diff1
      value: 78.9665
    - type: nauc_map_at_10_max
      value: 56.737899999999996
    - type: nauc_map_at_10_std
      value: -14.355599999999999
    - type: nauc_map_at_10_diff1
      value: 79.095
    - type: nauc_map_at_20_max
      value: 56.804
    - type: nauc_map_at_20_std
      value: -14.033599999999998
    - type: nauc_map_at_20_diff1
      value: 79.0729
    - type: nauc_map_at_100_max
      value: 56.7168
    - type: nauc_map_at_100_std
      value: -14.000000000000002
    - type: nauc_map_at_100_diff1
      value: 79.1456
    - type: nauc_map_at_1000_max
      value: 56.7168
    - type: nauc_map_at_1000_std
      value: -14.003099999999998
    - type: nauc_map_at_1000_diff1
      value: 79.1458
    - type: nauc_recall_at_1_max
      value: 45.2711
    - type: nauc_recall_at_1_std
      value: -21.685
    - type: nauc_recall_at_1_diff1
      value: 80.8536
    - type: nauc_recall_at_3_max
      value: 55.911100000000005
    - type: nauc_recall_at_3_std
      value: -19.1603
    - type: nauc_recall_at_3_diff1
      value: 72.51689999999999
    - type: nauc_recall_at_5_max
      value: 50.6317
    - type: nauc_recall_at_5_std
      value: -21.4004
    - type: nauc_recall_at_5_diff1
      value: 68.3824
    - type: nauc_recall_at_10_max
      value: 67.3176
    - type: nauc_recall_at_10_std
      value: -23.6601
    - type: nauc_recall_at_10_diff1
      value: 67.20150000000001
    - type: nauc_recall_at_20_max
      value: 76.566
    - type: nauc_recall_at_20_std
      value: -12.4873
    - type: nauc_recall_at_20_diff1
      value: 63.6849
    - type: nauc_recall_at_100_max
      value: 55.415499999999994
    - type: nauc_recall_at_100_std
      value: 72.2222
    - type: nauc_recall_at_100_diff1
      value: 72.2222
    - type: nauc_recall_at_1000_max
      value: .nan
    - type: nauc_recall_at_1000_std
      value: .nan
    - type: nauc_recall_at_1000_diff1
      value: .nan
    - type: nauc_precision_at_1_max
      value: 55.373099999999994
    - type: nauc_precision_at_1_std
      value: -11.362
    - type: nauc_precision_at_1_diff1
      value: 81.5232
    - type: nauc_precision_at_3_max
      value: 59.23969999999999
    - type: nauc_precision_at_3_std
      value: 17.3868
    - type: nauc_precision_at_3_diff1
      value: 37.0438
    - type: nauc_precision_at_5_max
      value: 51.358599999999996
    - type: nauc_precision_at_5_std
      value: 39.9722
    - type: nauc_precision_at_5_diff1
      value: 9.2927
    - type: nauc_precision_at_10_max
      value: 44.6166
    - type: nauc_precision_at_10_std
      value: 46.4231
    - type: nauc_precision_at_10_diff1
      value: -7.435700000000001
    - type: nauc_precision_at_20_max
      value: 41.1852
    - type: nauc_precision_at_20_std
      value: 51.89359999999999
    - type: nauc_precision_at_20_diff1
      value: -14.6318
    - type: nauc_precision_at_100_max
      value: 33.6188
    - type: nauc_precision_at_100_std
      value: 60.621700000000004
    - type: nauc_precision_at_100_diff1
      value: -26.376500000000004
    - type: nauc_precision_at_1000_max
      value: 33.2976
    - type: nauc_precision_at_1000_std
      value: 60.4508
    - type: nauc_precision_at_1000_diff1
      value: -27.829500000000003
    - type: nauc_mrr_at_1_max
      value: 55.373099999999994
    - type: nauc_mrr_at_1_std
      value: -11.362
    - type: nauc_mrr_at_1_diff1
      value: 81.5232
    - type: nauc_mrr_at_3_max
      value: 58.7918
    - type: nauc_mrr_at_3_std
      value: -11.580300000000001
    - type: nauc_mrr_at_3_diff1
      value: 78.79310000000001
    - type: nauc_mrr_at_5_max
      value: 58.13270000000001
    - type: nauc_mrr_at_5_std
      value: -11.2346
    - type: nauc_mrr_at_5_diff1
      value: 78.8896
    - type: nauc_mrr_at_10_max
      value: 58.4249
    - type: nauc_mrr_at_10_std
      value: -11.842600000000001
    - type: nauc_mrr_at_10_diff1
      value: 79.0629
    - type: nauc_mrr_at_20_max
      value: 58.4409
    - type: nauc_mrr_at_20_std
      value: -11.7012
    - type: nauc_mrr_at_20_diff1
      value: 79.1097
    - type: nauc_mrr_at_100_max
      value: 58.3685
    - type: nauc_mrr_at_100_std
      value: -11.6333
    - type: nauc_mrr_at_100_diff1
      value: 79.1871
    - type: nauc_mrr_at_1000_max
      value: 58.3686
    - type: nauc_mrr_at_1000_std
      value: -11.6365
    - type: nauc_mrr_at_1000_diff1
      value: 79.1874
    - type: main_score
      value: 80.372
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SprintDuplicateQuestions (default)
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
      split: test
      type: mteb/sprintduplicatequestions-pairclassification
    metrics:
    - type: similarity_accuracy
      value: 99.8317
    - type: similarity_accuracy_threshold
      value: 87.7015
    - type: similarity_f1
      value: 91.2821
    - type: similarity_f1_threshold
      value: 87.68599999999999
    - type: similarity_precision
      value: 93.68419999999999
    - type: similarity_recall
      value: 89.0
    - type: similarity_ap
      value: 96.249
    - type: cosine_accuracy
      value: 99.8317
    - type: cosine_accuracy_threshold
      value: 87.7015
    - type: cosine_f1
      value: 91.2821
    - type: cosine_f1_threshold
      value: 87.68599999999999
    - type: cosine_precision
      value: 93.68419999999999
    - type: cosine_recall
      value: 89.0
    - type: cosine_ap
      value: 96.249
    - type: manhattan_accuracy
      value: 99.83370000000001
    - type: manhattan_accuracy_threshold
      value: 4133.4675
    - type: manhattan_f1
      value: 91.52369999999999
    - type: manhattan_f1_threshold
      value: 4244.392400000001
    - type: manhattan_precision
      value: 92.3625
    - type: manhattan_recall
      value: 90.7
    - type: manhattan_ap
      value: 96.4021
    - type: euclidean_accuracy
      value: 99.83070000000001
    - type: euclidean_accuracy_threshold
      value: 49.684200000000004
    - type: euclidean_f1
      value: 91.24419999999999
    - type: euclidean_f1_threshold
      value: 49.7175
    - type: euclidean_precision
      value: 93.4942
    - type: euclidean_recall
      value: 89.1
    - type: euclidean_ap
      value: 96.24589999999999
    - type: dot_accuracy
      value: 99.8277
    - type: dot_accuracy_threshold
      value: 87.3743
    - type: dot_f1
      value: 91.1495
    - type: dot_f1_threshold
      value: 87.3743
    - type: dot_precision
      value: 92.7536
    - type: dot_recall
      value: 89.60000000000001
    - type: dot_ap
      value: 96.23509999999999
    - type: max_accuracy
      value: 99.83370000000001
    - type: max_f1
      value: 91.52369999999999
    - type: max_precision
      value: 93.68419999999999
    - type: max_recall
      value: 90.7
    - type: max_ap
      value: 96.4021
    - type: main_score
      value: 96.4021
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB StackExchangeClustering (default)
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
      split: test
      type: mteb/stackexchange-clustering
    metrics:
    - type: v_measure
      value: 80.19420000000001
    - type: v_measure_std
      value: 2.8956
    - type: main_score
      value: 80.19420000000001
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB StackExchangeClusteringP2P (default)
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
      split: test
      type: mteb/stackexchange-clustering-p2p
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      value: 49.416900000000005
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      value: 1.5938
    - type: main_score
      value: 49.416900000000005
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB StackOverflowDupQuestions (default)
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
      split: test
      type: mteb/stackoverflowdupquestions-reranking
    metrics:
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      value: 55.598800000000004
    - type: nAUC_map_max
      value: 9.1665
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      value: 7.8292
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      value: 38.831199999999995
    - type: nAUC_mrr_max
      value: 9.7435
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      value: 8.030800000000001
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      value: 39.2785
    - type: main_score
      value: 54.579
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SummEval (default)
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
      split: test
      type: mteb/summeval
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      value: 31.4212
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      value: 31.4212
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      value: 31.6006
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      value: 31.5459
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      value: 31.6412
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      value: 31.4212
    task:
      type: Summarization
  - dataset:
      config: default
      name: MTEB TRECCOVID (default)
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
      split: test
      type: mteb/trec-covid
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      value: 0.243
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      value: 0.703
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      value: 1.142
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      value: 0.243
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      value: 0.726
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      value: 97.0
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      value: 97.0
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      value: 53.2855
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      value: 26.559500000000003
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      value: 30.8674
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      value: 25.9597
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      value: 34.3742
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      value: 24.567
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      value: -1.028
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      value: 69.3433
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      value: 69.3433
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      value: 69.3433
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    - type: main_score
      value: 86.732
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB Touche2020 (default)
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
      split: test
      type: mteb/touche2020
    metrics:
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      value: 37.185
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      value: 32.564
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      value: 31.395
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      value: 30.494
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      value: 42.617
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      value: 53.324000000000005
    - type: map_at_1
      value: 2.7640000000000002
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      value: 6.970999999999999
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      value: 8.518
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      value: 11.919
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      value: 14.389
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      value: 18.799
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    - type: recall_at_1
      value: 2.7640000000000002
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      value: 8.323
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      value: 11.259
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      value: 19.088
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      value: 26.488
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      value: 53.437
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      value: 86.385
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      value: 31.429000000000002
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      value: 1.6119999999999999
    - type: mrr_at_1
      value: 38.7755
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      value: 52.7211
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      value: 55.9864
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      value: 57.2554
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      value: -20.4965
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    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB ToxicConversationsClassification (default)
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
      split: test
      type: mteb/toxic_conversations_50k
    metrics:
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    - type: main_score
      value: 91.3135
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TweetSentimentExtractionClassification (default)
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
      split: test
      type: mteb/tweet_sentiment_extraction
    metrics:
    - type: accuracy
      value: 77.24109999999999
    - type: f1
      value: 77.4964
    - type: f1_weighted
      value: 77.0248
    - type: main_score
      value: 77.24109999999999
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TwentyNewsgroupsClustering (default)
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
      split: test
      type: mteb/twentynewsgroups-clustering
    metrics:
    - type: v_measure
      value: 63.132200000000005
    - type: v_measure_std
      value: 0.7163
    - type: main_score
      value: 63.132200000000005
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB TwitterSemEval2015 (default)
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
      split: test
      type: mteb/twittersemeval2015-pairclassification
    metrics:
    - type: similarity_accuracy
      value: 88.061
    - type: similarity_accuracy_threshold
      value: 85.9546
    - type: similarity_f1
      value: 73.36240000000001
    - type: similarity_f1_threshold
      value: 84.0127
    - type: similarity_precision
      value: 71.47149999999999
    - type: similarity_recall
      value: 75.3562
    - type: similarity_ap
      value: 80.2787
    - type: cosine_accuracy
      value: 88.061
    - type: cosine_accuracy_threshold
      value: 85.9546
    - type: cosine_f1
      value: 73.36240000000001
    - type: cosine_f1_threshold
      value: 84.0127
    - type: cosine_precision
      value: 71.47149999999999
    - type: cosine_recall
      value: 75.3562
    - type: cosine_ap
      value: 80.2787
    - type: manhattan_accuracy
      value: 87.8941
    - type: manhattan_accuracy_threshold
      value: 4374.3263
    - type: manhattan_f1
      value: 72.929
    - type: manhattan_f1_threshold
      value: 4637.7289
    - type: manhattan_precision
      value: 71.3636
    - type: manhattan_recall
      value: 74.5646
    - type: manhattan_ap
      value: 79.98140000000001
    - type: euclidean_accuracy
      value: 88.0789
    - type: euclidean_accuracy_threshold
      value: 52.9742
    - type: euclidean_f1
      value: 73.3591
    - type: euclidean_f1_threshold
      value: 56.4815
    - type: euclidean_precision
      value: 71.608
    - type: euclidean_recall
      value: 75.19789999999999
    - type: euclidean_ap
      value: 80.2656
    - type: dot_accuracy
      value: 88.0789
    - type: dot_accuracy_threshold
      value: 85.8034
    - type: dot_f1
      value: 73.40379999999999
    - type: dot_f1_threshold
      value: 84.3213
    - type: dot_precision
      value: 72.6544
    - type: dot_recall
      value: 74.16890000000001
    - type: dot_ap
      value: 80.32010000000001
    - type: max_accuracy
      value: 88.0789
    - type: max_f1
      value: 73.40379999999999
    - type: max_precision
      value: 72.6544
    - type: max_recall
      value: 75.3562
    - type: max_ap
      value: 80.32010000000001
    - type: main_score
      value: 80.32010000000001
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB TwitterURLCorpus (default)
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
      split: test
      type: mteb/twitterurlcorpus-pairclassification
    metrics:
    - type: similarity_accuracy
      value: 89.93090000000001
    - type: similarity_accuracy_threshold
      value: 82.1349
    - type: similarity_f1
      value: 80.1377
    - type: similarity_f1_threshold
      value: 80.5047
    - type: similarity_precision
      value: 77.1539
    - type: similarity_recall
      value: 83.3616
    - type: similarity_ap
      value: 87.6917
    - type: cosine_accuracy
      value: 89.93090000000001
    - type: cosine_accuracy_threshold
      value: 82.1349
    - type: cosine_f1
      value: 80.1377
    - type: cosine_f1_threshold
      value: 80.5047
    - type: cosine_precision
      value: 77.1539
    - type: cosine_recall
      value: 83.3616
    - type: cosine_ap
      value: 87.6917
    - type: manhattan_accuracy
      value: 89.86880000000001
    - type: manhattan_accuracy_threshold
      value: 4882.7347
    - type: manhattan_f1
      value: 80.2323
    - type: manhattan_f1_threshold
      value: 5185.1944
    - type: manhattan_precision
      value: 76.74889999999999
    - type: manhattan_recall
      value: 84.0468
    - type: manhattan_ap
      value: 87.70750000000001
    - type: euclidean_accuracy
      value: 89.94640000000001
    - type: euclidean_accuracy_threshold
      value: 59.9149
    - type: euclidean_f1
      value: 80.1527
    - type: euclidean_f1_threshold
      value: 62.3611
    - type: euclidean_precision
      value: 77.2744
    - type: euclidean_recall
      value: 83.2538
    - type: euclidean_ap
      value: 87.6922
    - type: dot_accuracy
      value: 89.9038
    - type: dot_accuracy_threshold
      value: 82.53049999999999
    - type: dot_f1
      value: 80.0969
    - type: dot_f1_threshold
      value: 80.7285
    - type: dot_precision
      value: 77.5853
    - type: dot_recall
      value: 82.77640000000001
    - type: dot_ap
      value: 87.668
    - type: max_accuracy
      value: 89.94640000000001
    - type: max_f1
      value: 80.2323
    - type: max_precision
      value: 77.5853
    - type: max_recall
      value: 84.0468
    - type: max_ap
      value: 87.70750000000001
    - type: main_score
      value: 87.70750000000001
    task:
      type: PairClassification
datasets:
- BAAI/Infinity-MM
- HuggingFaceFW/fineweb-edu
language:
- en
base_model:
- dunzhang/stella_en_1.5B_v5
- google/siglip-so400m-patch14-384
tags:
- mteb
---


## Introduction 

Based on dunzhang/stella_en_1.5B_v5 and google/siglip-so400m-patch14-384.

It can encode both text and image.

Details is coming soon.

## License
**This model should not be used for any commercial purpose!**