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metadata
model-index:
  - name: gte_tiny
    results:
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_counterfactual
          name: MTEB AmazonCounterfactualClassification (en)
          config: en
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 71.76119402985076
          - type: ap
            value: 34.63659287952359
          - type: f1
            value: 65.88939512571113
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_polarity
          name: MTEB AmazonPolarityClassification
          config: default
          split: test
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
        metrics:
          - type: accuracy
            value: 86.61324999999998
          - type: ap
            value: 81.7476302802319
          - type: f1
            value: 86.5863470912001
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (en)
          config: en
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 42.61000000000001
          - type: f1
            value: 42.2217180000715
      - task:
          type: Retrieval
        dataset:
          type: arguana
          name: MTEB ArguAna
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 28.377999999999997
          - type: map_at_10
            value: 44.565
          - type: map_at_100
            value: 45.48
          - type: map_at_1000
            value: 45.487
          - type: map_at_3
            value: 39.841
          - type: map_at_5
            value: 42.284
          - type: mrr_at_1
            value: 29.445
          - type: mrr_at_10
            value: 44.956
          - type: mrr_at_100
            value: 45.877
          - type: mrr_at_1000
            value: 45.884
          - type: mrr_at_3
            value: 40.209
          - type: mrr_at_5
            value: 42.719
          - type: ndcg_at_1
            value: 28.377999999999997
          - type: ndcg_at_10
            value: 53.638
          - type: ndcg_at_100
            value: 57.354000000000006
          - type: ndcg_at_1000
            value: 57.513000000000005
          - type: ndcg_at_3
            value: 43.701
          - type: ndcg_at_5
            value: 48.114000000000004
          - type: precision_at_1
            value: 28.377999999999997
          - type: precision_at_10
            value: 8.272
          - type: precision_at_100
            value: 0.984
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 18.303
          - type: precision_at_5
            value: 13.129
          - type: recall_at_1
            value: 28.377999999999997
          - type: recall_at_10
            value: 82.717
          - type: recall_at_100
            value: 98.43499999999999
          - type: recall_at_1000
            value: 99.644
          - type: recall_at_3
            value: 54.908
          - type: recall_at_5
            value: 65.647
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-p2p
          name: MTEB ArxivClusteringP2P
          config: default
          split: test
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
        metrics:
          - type: v_measure
            value: 46.637318326729876
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-s2s
          name: MTEB ArxivClusteringS2S
          config: default
          split: test
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
        metrics:
          - type: v_measure
            value: 36.01134479855804
      - task:
          type: Reranking
        dataset:
          type: mteb/askubuntudupquestions-reranking
          name: MTEB AskUbuntuDupQuestions
          config: default
          split: test
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
        metrics:
          - type: map
            value: 59.82917555338909
          - type: mrr
            value: 74.7888361254012
      - task:
          type: STS
        dataset:
          type: mteb/biosses-sts
          name: MTEB BIOSSES
          config: default
          split: test
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
        metrics:
          - type: cos_sim_pearson
            value: 87.1657730995964
          - type: cos_sim_spearman
            value: 86.62787748941281
          - type: euclidean_pearson
            value: 85.48127914481798
          - type: euclidean_spearman
            value: 86.48148861167424
          - type: manhattan_pearson
            value: 85.07496934780823
          - type: manhattan_spearman
            value: 86.39473964708843
      - task:
          type: Classification
        dataset:
          type: mteb/banking77
          name: MTEB Banking77Classification
          config: default
          split: test
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
        metrics:
          - type: accuracy
            value: 81.73051948051948
          - type: f1
            value: 81.66368364988331
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-p2p
          name: MTEB BiorxivClusteringP2P
          config: default
          split: test
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
        metrics:
          - type: v_measure
            value: 39.18623707448217
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-s2s
          name: MTEB BiorxivClusteringS2S
          config: default
          split: test
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
        metrics:
          - type: v_measure
            value: 32.12697757150375
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackAndroidRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 29.160000000000004
          - type: map_at_10
            value: 40.474
          - type: map_at_100
            value: 41.905
          - type: map_at_1000
            value: 42.041000000000004
          - type: map_at_3
            value: 37.147000000000006
          - type: map_at_5
            value: 38.873999999999995
          - type: mrr_at_1
            value: 36.91
          - type: mrr_at_10
            value: 46.495999999999995
          - type: mrr_at_100
            value: 47.288000000000004
          - type: mrr_at_1000
            value: 47.339999999999996
          - type: mrr_at_3
            value: 43.777
          - type: mrr_at_5
            value: 45.257999999999996
          - type: ndcg_at_1
            value: 36.91
          - type: ndcg_at_10
            value: 46.722
          - type: ndcg_at_100
            value: 51.969
          - type: ndcg_at_1000
            value: 54.232
          - type: ndcg_at_3
            value: 41.783
          - type: ndcg_at_5
            value: 43.797000000000004
          - type: precision_at_1
            value: 36.91
          - type: precision_at_10
            value: 9.013
          - type: precision_at_100
            value: 1.455
          - type: precision_at_1000
            value: 0.193
          - type: precision_at_3
            value: 20.124
          - type: precision_at_5
            value: 14.363000000000001
          - type: recall_at_1
            value: 29.160000000000004
          - type: recall_at_10
            value: 58.521
          - type: recall_at_100
            value: 80.323
          - type: recall_at_1000
            value: 95.13000000000001
          - type: recall_at_3
            value: 44.205
          - type: recall_at_5
            value: 49.97
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackEnglishRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 27.750000000000004
          - type: map_at_10
            value: 36.39
          - type: map_at_100
            value: 37.5
          - type: map_at_1000
            value: 37.625
          - type: map_at_3
            value: 33.853
          - type: map_at_5
            value: 35.397
          - type: mrr_at_1
            value: 34.14
          - type: mrr_at_10
            value: 41.841
          - type: mrr_at_100
            value: 42.469
          - type: mrr_at_1000
            value: 42.521
          - type: mrr_at_3
            value: 39.724
          - type: mrr_at_5
            value: 40.955999999999996
          - type: ndcg_at_1
            value: 34.14
          - type: ndcg_at_10
            value: 41.409
          - type: ndcg_at_100
            value: 45.668
          - type: ndcg_at_1000
            value: 47.916
          - type: ndcg_at_3
            value: 37.836
          - type: ndcg_at_5
            value: 39.650999999999996
          - type: precision_at_1
            value: 34.14
          - type: precision_at_10
            value: 7.739
          - type: precision_at_100
            value: 1.2630000000000001
          - type: precision_at_1000
            value: 0.173
          - type: precision_at_3
            value: 18.217
          - type: precision_at_5
            value: 12.854
          - type: recall_at_1
            value: 27.750000000000004
          - type: recall_at_10
            value: 49.882
          - type: recall_at_100
            value: 68.556
          - type: recall_at_1000
            value: 83.186
          - type: recall_at_3
            value: 39.047
          - type: recall_at_5
            value: 44.458
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackGamingRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 36.879
          - type: map_at_10
            value: 48.878
          - type: map_at_100
            value: 49.918
          - type: map_at_1000
            value: 49.978
          - type: map_at_3
            value: 45.867999999999995
          - type: map_at_5
            value: 47.637
          - type: mrr_at_1
            value: 42.696
          - type: mrr_at_10
            value: 52.342
          - type: mrr_at_100
            value: 53.044000000000004
          - type: mrr_at_1000
            value: 53.077
          - type: mrr_at_3
            value: 50.01
          - type: mrr_at_5
            value: 51.437
          - type: ndcg_at_1
            value: 42.696
          - type: ndcg_at_10
            value: 54.469
          - type: ndcg_at_100
            value: 58.664
          - type: ndcg_at_1000
            value: 59.951
          - type: ndcg_at_3
            value: 49.419999999999995
          - type: ndcg_at_5
            value: 52.007000000000005
          - type: precision_at_1
            value: 42.696
          - type: precision_at_10
            value: 8.734
          - type: precision_at_100
            value: 1.1769999999999998
          - type: precision_at_1000
            value: 0.133
          - type: precision_at_3
            value: 22.027
          - type: precision_at_5
            value: 15.135000000000002
          - type: recall_at_1
            value: 36.879
          - type: recall_at_10
            value: 67.669
          - type: recall_at_100
            value: 85.822
          - type: recall_at_1000
            value: 95.092
          - type: recall_at_3
            value: 54.157999999999994
          - type: recall_at_5
            value: 60.436
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackGisRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 22.942
          - type: map_at_10
            value: 31.741999999999997
          - type: map_at_100
            value: 32.721000000000004
          - type: map_at_1000
            value: 32.809
          - type: map_at_3
            value: 29.17
          - type: map_at_5
            value: 30.714000000000002
          - type: mrr_at_1
            value: 24.746000000000002
          - type: mrr_at_10
            value: 33.517
          - type: mrr_at_100
            value: 34.451
          - type: mrr_at_1000
            value: 34.522000000000006
          - type: mrr_at_3
            value: 31.148999999999997
          - type: mrr_at_5
            value: 32.606
          - type: ndcg_at_1
            value: 24.746000000000002
          - type: ndcg_at_10
            value: 36.553000000000004
          - type: ndcg_at_100
            value: 41.53
          - type: ndcg_at_1000
            value: 43.811
          - type: ndcg_at_3
            value: 31.674000000000003
          - type: ndcg_at_5
            value: 34.241
          - type: precision_at_1
            value: 24.746000000000002
          - type: precision_at_10
            value: 5.684
          - type: precision_at_100
            value: 0.859
          - type: precision_at_1000
            value: 0.109
          - type: precision_at_3
            value: 13.597000000000001
          - type: precision_at_5
            value: 9.672
          - type: recall_at_1
            value: 22.942
          - type: recall_at_10
            value: 49.58
          - type: recall_at_100
            value: 72.614
          - type: recall_at_1000
            value: 89.89200000000001
          - type: recall_at_3
            value: 36.552
          - type: recall_at_5
            value: 42.702
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackMathematicaRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 15.345
          - type: map_at_10
            value: 22.428
          - type: map_at_100
            value: 23.756
          - type: map_at_1000
            value: 23.872
          - type: map_at_3
            value: 20.212
          - type: map_at_5
            value: 21.291
          - type: mrr_at_1
            value: 19.279
          - type: mrr_at_10
            value: 27.1
          - type: mrr_at_100
            value: 28.211000000000002
          - type: mrr_at_1000
            value: 28.279
          - type: mrr_at_3
            value: 24.813
          - type: mrr_at_5
            value: 25.889
          - type: ndcg_at_1
            value: 19.279
          - type: ndcg_at_10
            value: 27.36
          - type: ndcg_at_100
            value: 33.499
          - type: ndcg_at_1000
            value: 36.452
          - type: ndcg_at_3
            value: 23.233999999999998
          - type: ndcg_at_5
            value: 24.806
          - type: precision_at_1
            value: 19.279
          - type: precision_at_10
            value: 5.149
          - type: precision_at_100
            value: 0.938
          - type: precision_at_1000
            value: 0.133
          - type: precision_at_3
            value: 11.360000000000001
          - type: precision_at_5
            value: 8.035
          - type: recall_at_1
            value: 15.345
          - type: recall_at_10
            value: 37.974999999999994
          - type: recall_at_100
            value: 64.472
          - type: recall_at_1000
            value: 85.97200000000001
          - type: recall_at_3
            value: 26.203
          - type: recall_at_5
            value: 30.485
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackPhysicsRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 26.362000000000002
          - type: map_at_10
            value: 36.406
          - type: map_at_100
            value: 37.726
          - type: map_at_1000
            value: 37.84
          - type: map_at_3
            value: 33.425
          - type: map_at_5
            value: 35.043
          - type: mrr_at_1
            value: 32.146
          - type: mrr_at_10
            value: 41.674
          - type: mrr_at_100
            value: 42.478
          - type: mrr_at_1000
            value: 42.524
          - type: mrr_at_3
            value: 38.948
          - type: mrr_at_5
            value: 40.415
          - type: ndcg_at_1
            value: 32.146
          - type: ndcg_at_10
            value: 42.374
          - type: ndcg_at_100
            value: 47.919
          - type: ndcg_at_1000
            value: 50.013
          - type: ndcg_at_3
            value: 37.29
          - type: ndcg_at_5
            value: 39.531
          - type: precision_at_1
            value: 32.146
          - type: precision_at_10
            value: 7.767
          - type: precision_at_100
            value: 1.236
          - type: precision_at_1000
            value: 0.16
          - type: precision_at_3
            value: 17.965999999999998
          - type: precision_at_5
            value: 12.742999999999999
          - type: recall_at_1
            value: 26.362000000000002
          - type: recall_at_10
            value: 54.98800000000001
          - type: recall_at_100
            value: 78.50200000000001
          - type: recall_at_1000
            value: 92.146
          - type: recall_at_3
            value: 40.486
          - type: recall_at_5
            value: 46.236
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackProgrammersRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 24.417
          - type: map_at_10
            value: 33.161
          - type: map_at_100
            value: 34.357
          - type: map_at_1000
            value: 34.473
          - type: map_at_3
            value: 30.245
          - type: map_at_5
            value: 31.541999999999998
          - type: mrr_at_1
            value: 29.909000000000002
          - type: mrr_at_10
            value: 38.211
          - type: mrr_at_100
            value: 39.056999999999995
          - type: mrr_at_1000
            value: 39.114
          - type: mrr_at_3
            value: 35.769
          - type: mrr_at_5
            value: 36.922
          - type: ndcg_at_1
            value: 29.909000000000002
          - type: ndcg_at_10
            value: 38.694
          - type: ndcg_at_100
            value: 44.057
          - type: ndcg_at_1000
            value: 46.6
          - type: ndcg_at_3
            value: 33.822
          - type: ndcg_at_5
            value: 35.454
          - type: precision_at_1
            value: 29.909000000000002
          - type: precision_at_10
            value: 7.180000000000001
          - type: precision_at_100
            value: 1.153
          - type: precision_at_1000
            value: 0.155
          - type: precision_at_3
            value: 16.134
          - type: precision_at_5
            value: 11.256
          - type: recall_at_1
            value: 24.417
          - type: recall_at_10
            value: 50.260000000000005
          - type: recall_at_100
            value: 73.55699999999999
          - type: recall_at_1000
            value: 91.216
          - type: recall_at_3
            value: 35.971
          - type: recall_at_5
            value: 40.793
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 24.266916666666663
          - type: map_at_10
            value: 32.75025
          - type: map_at_100
            value: 33.91341666666667
          - type: map_at_1000
            value: 34.031749999999995
          - type: map_at_3
            value: 30.166416666666674
          - type: map_at_5
            value: 31.577000000000005
          - type: mrr_at_1
            value: 28.828166666666664
          - type: mrr_at_10
            value: 36.80991666666667
          - type: mrr_at_100
            value: 37.67075
          - type: mrr_at_1000
            value: 37.733
          - type: mrr_at_3
            value: 34.513416666666664
          - type: mrr_at_5
            value: 35.788
          - type: ndcg_at_1
            value: 28.828166666666664
          - type: ndcg_at_10
            value: 37.796
          - type: ndcg_at_100
            value: 42.94783333333333
          - type: ndcg_at_1000
            value: 45.38908333333333
          - type: ndcg_at_3
            value: 33.374750000000006
          - type: ndcg_at_5
            value: 35.379666666666665
          - type: precision_at_1
            value: 28.828166666666664
          - type: precision_at_10
            value: 6.615749999999999
          - type: precision_at_100
            value: 1.0848333333333333
          - type: precision_at_1000
            value: 0.1484166666666667
          - type: precision_at_3
            value: 15.347833333333332
          - type: precision_at_5
            value: 10.848916666666666
          - type: recall_at_1
            value: 24.266916666666663
          - type: recall_at_10
            value: 48.73458333333333
          - type: recall_at_100
            value: 71.56341666666667
          - type: recall_at_1000
            value: 88.63091666666668
          - type: recall_at_3
            value: 36.31208333333333
          - type: recall_at_5
            value: 41.55633333333333
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackStatsRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 23.497
          - type: map_at_10
            value: 30.249
          - type: map_at_100
            value: 30.947000000000003
          - type: map_at_1000
            value: 31.049
          - type: map_at_3
            value: 28.188000000000002
          - type: map_at_5
            value: 29.332
          - type: mrr_at_1
            value: 26.687
          - type: mrr_at_10
            value: 33.182
          - type: mrr_at_100
            value: 33.794999999999995
          - type: mrr_at_1000
            value: 33.873
          - type: mrr_at_3
            value: 31.263
          - type: mrr_at_5
            value: 32.428000000000004
          - type: ndcg_at_1
            value: 26.687
          - type: ndcg_at_10
            value: 34.252
          - type: ndcg_at_100
            value: 38.083
          - type: ndcg_at_1000
            value: 40.682
          - type: ndcg_at_3
            value: 30.464999999999996
          - type: ndcg_at_5
            value: 32.282
          - type: precision_at_1
            value: 26.687
          - type: precision_at_10
            value: 5.2909999999999995
          - type: precision_at_100
            value: 0.788
          - type: precision_at_1000
            value: 0.109
          - type: precision_at_3
            value: 13.037
          - type: precision_at_5
            value: 9.049
          - type: recall_at_1
            value: 23.497
          - type: recall_at_10
            value: 43.813
          - type: recall_at_100
            value: 61.88399999999999
          - type: recall_at_1000
            value: 80.926
          - type: recall_at_3
            value: 33.332
          - type: recall_at_5
            value: 37.862
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackTexRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 16.073
          - type: map_at_10
            value: 22.705000000000002
          - type: map_at_100
            value: 23.703
          - type: map_at_1000
            value: 23.833
          - type: map_at_3
            value: 20.593
          - type: map_at_5
            value: 21.7
          - type: mrr_at_1
            value: 19.683
          - type: mrr_at_10
            value: 26.39
          - type: mrr_at_100
            value: 27.264
          - type: mrr_at_1000
            value: 27.349
          - type: mrr_at_3
            value: 24.409
          - type: mrr_at_5
            value: 25.474000000000004
          - type: ndcg_at_1
            value: 19.683
          - type: ndcg_at_10
            value: 27.014
          - type: ndcg_at_100
            value: 31.948
          - type: ndcg_at_1000
            value: 35.125
          - type: ndcg_at_3
            value: 23.225
          - type: ndcg_at_5
            value: 24.866
          - type: precision_at_1
            value: 19.683
          - type: precision_at_10
            value: 4.948
          - type: precision_at_100
            value: 0.876
          - type: precision_at_1000
            value: 0.133
          - type: precision_at_3
            value: 10.943
          - type: precision_at_5
            value: 7.86
          - type: recall_at_1
            value: 16.073
          - type: recall_at_10
            value: 36.283
          - type: recall_at_100
            value: 58.745999999999995
          - type: recall_at_1000
            value: 81.711
          - type: recall_at_3
            value: 25.637
          - type: recall_at_5
            value: 29.919
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackUnixRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 25.776
          - type: map_at_10
            value: 33.317
          - type: map_at_100
            value: 34.437
          - type: map_at_1000
            value: 34.54
          - type: map_at_3
            value: 30.706
          - type: map_at_5
            value: 32.202999999999996
          - type: mrr_at_1
            value: 30.224
          - type: mrr_at_10
            value: 37.34
          - type: mrr_at_100
            value: 38.268
          - type: mrr_at_1000
            value: 38.335
          - type: mrr_at_3
            value: 35.075
          - type: mrr_at_5
            value: 36.348
          - type: ndcg_at_1
            value: 30.224
          - type: ndcg_at_10
            value: 38.083
          - type: ndcg_at_100
            value: 43.413000000000004
          - type: ndcg_at_1000
            value: 45.856
          - type: ndcg_at_3
            value: 33.437
          - type: ndcg_at_5
            value: 35.661
          - type: precision_at_1
            value: 30.224
          - type: precision_at_10
            value: 6.1850000000000005
          - type: precision_at_100
            value: 1.0030000000000001
          - type: precision_at_1000
            value: 0.132
          - type: precision_at_3
            value: 14.646
          - type: precision_at_5
            value: 10.428999999999998
          - type: recall_at_1
            value: 25.776
          - type: recall_at_10
            value: 48.787000000000006
          - type: recall_at_100
            value: 72.04899999999999
          - type: recall_at_1000
            value: 89.339
          - type: recall_at_3
            value: 36.192
          - type: recall_at_5
            value: 41.665
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackWebmastersRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 23.156
          - type: map_at_10
            value: 30.886000000000003
          - type: map_at_100
            value: 32.551
          - type: map_at_1000
            value: 32.769
          - type: map_at_3
            value: 28.584
          - type: map_at_5
            value: 29.959999999999997
          - type: mrr_at_1
            value: 28.260999999999996
          - type: mrr_at_10
            value: 35.555
          - type: mrr_at_100
            value: 36.687
          - type: mrr_at_1000
            value: 36.742999999999995
          - type: mrr_at_3
            value: 33.531
          - type: mrr_at_5
            value: 34.717
          - type: ndcg_at_1
            value: 28.260999999999996
          - type: ndcg_at_10
            value: 36.036
          - type: ndcg_at_100
            value: 42.675000000000004
          - type: ndcg_at_1000
            value: 45.303
          - type: ndcg_at_3
            value: 32.449
          - type: ndcg_at_5
            value: 34.293
          - type: precision_at_1
            value: 28.260999999999996
          - type: precision_at_10
            value: 6.837999999999999
          - type: precision_at_100
            value: 1.4569999999999999
          - type: precision_at_1000
            value: 0.23500000000000001
          - type: precision_at_3
            value: 15.217
          - type: precision_at_5
            value: 11.028
          - type: recall_at_1
            value: 23.156
          - type: recall_at_10
            value: 45.251999999999995
          - type: recall_at_100
            value: 75.339
          - type: recall_at_1000
            value: 91.56
          - type: recall_at_3
            value: 34.701
          - type: recall_at_5
            value: 39.922999999999995
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackWordpressRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 19.846
          - type: map_at_10
            value: 26.367
          - type: map_at_100
            value: 27.439999999999998
          - type: map_at_1000
            value: 27.552
          - type: map_at_3
            value: 24.006
          - type: map_at_5
            value: 25.230999999999998
          - type: mrr_at_1
            value: 21.257
          - type: mrr_at_10
            value: 28.071
          - type: mrr_at_100
            value: 29.037000000000003
          - type: mrr_at_1000
            value: 29.119
          - type: mrr_at_3
            value: 25.692999999999998
          - type: mrr_at_5
            value: 27.006000000000004
          - type: ndcg_at_1
            value: 21.257
          - type: ndcg_at_10
            value: 30.586000000000002
          - type: ndcg_at_100
            value: 35.949
          - type: ndcg_at_1000
            value: 38.728
          - type: ndcg_at_3
            value: 25.862000000000002
          - type: ndcg_at_5
            value: 27.967
          - type: precision_at_1
            value: 21.257
          - type: precision_at_10
            value: 4.861
          - type: precision_at_100
            value: 0.8130000000000001
          - type: precision_at_1000
            value: 0.116
          - type: precision_at_3
            value: 10.906
          - type: precision_at_5
            value: 7.763000000000001
          - type: recall_at_1
            value: 19.846
          - type: recall_at_10
            value: 41.805
          - type: recall_at_100
            value: 66.89699999999999
          - type: recall_at_1000
            value: 87.401
          - type: recall_at_3
            value: 29.261
          - type: recall_at_5
            value: 34.227000000000004
      - task:
          type: Retrieval
        dataset:
          type: climate-fever
          name: MTEB ClimateFEVER
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 10.333
          - type: map_at_10
            value: 17.14
          - type: map_at_100
            value: 18.878
          - type: map_at_1000
            value: 19.067
          - type: map_at_3
            value: 14.123
          - type: map_at_5
            value: 15.699
          - type: mrr_at_1
            value: 23.192
          - type: mrr_at_10
            value: 33.553
          - type: mrr_at_100
            value: 34.553
          - type: mrr_at_1000
            value: 34.603
          - type: mrr_at_3
            value: 29.848000000000003
          - type: mrr_at_5
            value: 32.18
          - type: ndcg_at_1
            value: 23.192
          - type: ndcg_at_10
            value: 24.707
          - type: ndcg_at_100
            value: 31.701
          - type: ndcg_at_1000
            value: 35.260999999999996
          - type: ndcg_at_3
            value: 19.492
          - type: ndcg_at_5
            value: 21.543
          - type: precision_at_1
            value: 23.192
          - type: precision_at_10
            value: 7.824000000000001
          - type: precision_at_100
            value: 1.52
          - type: precision_at_1000
            value: 0.218
          - type: precision_at_3
            value: 14.180000000000001
          - type: precision_at_5
            value: 11.530999999999999
          - type: recall_at_1
            value: 10.333
          - type: recall_at_10
            value: 30.142999999999997
          - type: recall_at_100
            value: 54.298
          - type: recall_at_1000
            value: 74.337
          - type: recall_at_3
            value: 17.602999999999998
          - type: recall_at_5
            value: 22.938
      - task:
          type: Retrieval
        dataset:
          type: dbpedia-entity
          name: MTEB DBPedia
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 8.03
          - type: map_at_10
            value: 17.345
          - type: map_at_100
            value: 23.462
          - type: map_at_1000
            value: 24.77
          - type: map_at_3
            value: 12.714
          - type: map_at_5
            value: 14.722
          - type: mrr_at_1
            value: 61
          - type: mrr_at_10
            value: 69.245
          - type: mrr_at_100
            value: 69.715
          - type: mrr_at_1000
            value: 69.719
          - type: mrr_at_3
            value: 67.583
          - type: mrr_at_5
            value: 68.521
          - type: ndcg_at_1
            value: 47.625
          - type: ndcg_at_10
            value: 35.973
          - type: ndcg_at_100
            value: 39.875
          - type: ndcg_at_1000
            value: 46.922000000000004
          - type: ndcg_at_3
            value: 40.574
          - type: ndcg_at_5
            value: 38.18
          - type: precision_at_1
            value: 61
          - type: precision_at_10
            value: 29.049999999999997
          - type: precision_at_100
            value: 8.828
          - type: precision_at_1000
            value: 1.8290000000000002
          - type: precision_at_3
            value: 45.333
          - type: precision_at_5
            value: 37.9
          - type: recall_at_1
            value: 8.03
          - type: recall_at_10
            value: 22.334
          - type: recall_at_100
            value: 45.919
          - type: recall_at_1000
            value: 68.822
          - type: recall_at_3
            value: 14.038999999999998
          - type: recall_at_5
            value: 17.118
      - task:
          type: Classification
        dataset:
          type: mteb/emotion
          name: MTEB EmotionClassification
          config: default
          split: test
          revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
        metrics:
          - type: accuracy
            value: 44.714999999999996
          - type: f1
            value: 39.83929362259356
      - task:
          type: Retrieval
        dataset:
          type: fever
          name: MTEB FEVER
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 52.242999999999995
          - type: map_at_10
            value: 64.087
          - type: map_at_100
            value: 64.549
          - type: map_at_1000
            value: 64.567
          - type: map_at_3
            value: 61.667
          - type: map_at_5
            value: 63.266
          - type: mrr_at_1
            value: 56.271
          - type: mrr_at_10
            value: 68.146
          - type: mrr_at_100
            value: 68.524
          - type: mrr_at_1000
            value: 68.53200000000001
          - type: mrr_at_3
            value: 65.869
          - type: mrr_at_5
            value: 67.37100000000001
          - type: ndcg_at_1
            value: 56.271
          - type: ndcg_at_10
            value: 70.109
          - type: ndcg_at_100
            value: 72.09
          - type: ndcg_at_1000
            value: 72.479
          - type: ndcg_at_3
            value: 65.559
          - type: ndcg_at_5
            value: 68.242
          - type: precision_at_1
            value: 56.271
          - type: precision_at_10
            value: 9.286999999999999
          - type: precision_at_100
            value: 1.039
          - type: precision_at_1000
            value: 0.109
          - type: precision_at_3
            value: 26.308
          - type: precision_at_5
            value: 17.291
          - type: recall_at_1
            value: 52.242999999999995
          - type: recall_at_10
            value: 84.71
          - type: recall_at_100
            value: 93.309
          - type: recall_at_1000
            value: 96.013
          - type: recall_at_3
            value: 72.554
          - type: recall_at_5
            value: 79.069
      - task:
          type: Retrieval
        dataset:
          type: fiqa
          name: MTEB FiQA2018
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 14.346
          - type: map_at_10
            value: 24.552
          - type: map_at_100
            value: 26.161
          - type: map_at_1000
            value: 26.345000000000002
          - type: map_at_3
            value: 21.208
          - type: map_at_5
            value: 22.959
          - type: mrr_at_1
            value: 29.166999999999998
          - type: mrr_at_10
            value: 38.182
          - type: mrr_at_100
            value: 39.22
          - type: mrr_at_1000
            value: 39.263
          - type: mrr_at_3
            value: 35.983
          - type: mrr_at_5
            value: 37.14
          - type: ndcg_at_1
            value: 29.166999999999998
          - type: ndcg_at_10
            value: 31.421
          - type: ndcg_at_100
            value: 38.129999999999995
          - type: ndcg_at_1000
            value: 41.569
          - type: ndcg_at_3
            value: 28.172000000000004
          - type: ndcg_at_5
            value: 29.029
          - type: precision_at_1
            value: 29.166999999999998
          - type: precision_at_10
            value: 8.997
          - type: precision_at_100
            value: 1.5709999999999997
          - type: precision_at_1000
            value: 0.22
          - type: precision_at_3
            value: 19.187
          - type: precision_at_5
            value: 13.980999999999998
          - type: recall_at_1
            value: 14.346
          - type: recall_at_10
            value: 37.963
          - type: recall_at_100
            value: 63.43299999999999
          - type: recall_at_1000
            value: 84.057
          - type: recall_at_3
            value: 26.119999999999997
          - type: recall_at_5
            value: 30.988
      - task:
          type: Retrieval
        dataset:
          type: hotpotqa
          name: MTEB HotpotQA
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 33.059
          - type: map_at_10
            value: 46.421
          - type: map_at_100
            value: 47.323
          - type: map_at_1000
            value: 47.403
          - type: map_at_3
            value: 43.553999999999995
          - type: map_at_5
            value: 45.283
          - type: mrr_at_1
            value: 66.117
          - type: mrr_at_10
            value: 73.10900000000001
          - type: mrr_at_100
            value: 73.444
          - type: mrr_at_1000
            value: 73.46000000000001
          - type: mrr_at_3
            value: 71.70400000000001
          - type: mrr_at_5
            value: 72.58099999999999
          - type: ndcg_at_1
            value: 66.117
          - type: ndcg_at_10
            value: 55.696999999999996
          - type: ndcg_at_100
            value: 59.167
          - type: ndcg_at_1000
            value: 60.809000000000005
          - type: ndcg_at_3
            value: 51.243
          - type: ndcg_at_5
            value: 53.627
          - type: precision_at_1
            value: 66.117
          - type: precision_at_10
            value: 11.538
          - type: precision_at_100
            value: 1.429
          - type: precision_at_1000
            value: 0.165
          - type: precision_at_3
            value: 31.861
          - type: precision_at_5
            value: 20.997
          - type: recall_at_1
            value: 33.059
          - type: recall_at_10
            value: 57.691
          - type: recall_at_100
            value: 71.458
          - type: recall_at_1000
            value: 82.35
          - type: recall_at_3
            value: 47.792
          - type: recall_at_5
            value: 52.492000000000004
      - task:
          type: Classification
        dataset:
          type: mteb/imdb
          name: MTEB ImdbClassification
          config: default
          split: test
          revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
        metrics:
          - type: accuracy
            value: 80.544
          - type: ap
            value: 74.69592367984956
          - type: f1
            value: 80.51138138449883
      - task:
          type: Retrieval
        dataset:
          type: msmarco
          name: MTEB MSMARCO
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 17.095
          - type: map_at_10
            value: 28.038999999999998
          - type: map_at_100
            value: 29.246
          - type: map_at_1000
            value: 29.311
          - type: map_at_3
            value: 24.253
          - type: map_at_5
            value: 26.442
          - type: mrr_at_1
            value: 17.535999999999998
          - type: mrr_at_10
            value: 28.53
          - type: mrr_at_100
            value: 29.697000000000003
          - type: mrr_at_1000
            value: 29.755
          - type: mrr_at_3
            value: 24.779999999999998
          - type: mrr_at_5
            value: 26.942
          - type: ndcg_at_1
            value: 17.549999999999997
          - type: ndcg_at_10
            value: 34.514
          - type: ndcg_at_100
            value: 40.497
          - type: ndcg_at_1000
            value: 42.17
          - type: ndcg_at_3
            value: 26.764
          - type: ndcg_at_5
            value: 30.678
          - type: precision_at_1
            value: 17.549999999999997
          - type: precision_at_10
            value: 5.692
          - type: precision_at_100
            value: 0.8699999999999999
          - type: precision_at_1000
            value: 0.101
          - type: precision_at_3
            value: 11.562
          - type: precision_at_5
            value: 8.917
          - type: recall_at_1
            value: 17.095
          - type: recall_at_10
            value: 54.642
          - type: recall_at_100
            value: 82.652
          - type: recall_at_1000
            value: 95.555
          - type: recall_at_3
            value: 33.504
          - type: recall_at_5
            value: 42.925000000000004
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (en)
          config: en
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 91.75558595531236
          - type: f1
            value: 91.25979279648296
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (en)
          config: en
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 69.90424076607387
          - type: f1
            value: 52.067408707562244
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (en)
          config: en
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 70.13449899125757
          - type: f1
            value: 67.62456762910598
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (en)
          config: en
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 74.862138533961
          - type: f1
            value: 74.66457222091381
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-p2p
          name: MTEB MedrxivClusteringP2P
          config: default
          split: test
          revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
        metrics:
          - type: v_measure
            value: 34.10761942610792
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-s2s
          name: MTEB MedrxivClusteringS2S
          config: default
          split: test
          revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
        metrics:
          - type: v_measure
            value: 31.673172170578408
      - task:
          type: Reranking
        dataset:
          type: mteb/mind_small
          name: MTEB MindSmallReranking
          config: default
          split: test
          revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
        metrics:
          - type: map
            value: 32.058704977250315
          - type: mrr
            value: 33.24327760839221
      - task:
          type: Retrieval
        dataset:
          type: nfcorpus
          name: MTEB NFCorpus
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 5.163
          - type: map_at_10
            value: 11.652999999999999
          - type: map_at_100
            value: 14.849
          - type: map_at_1000
            value: 16.253999999999998
          - type: map_at_3
            value: 8.616999999999999
          - type: map_at_5
            value: 10.100000000000001
          - type: mrr_at_1
            value: 44.272
          - type: mrr_at_10
            value: 52.25
          - type: mrr_at_100
            value: 52.761
          - type: mrr_at_1000
            value: 52.811
          - type: mrr_at_3
            value: 50.31
          - type: mrr_at_5
            value: 51.347
          - type: ndcg_at_1
            value: 42.105
          - type: ndcg_at_10
            value: 32.044
          - type: ndcg_at_100
            value: 29.763
          - type: ndcg_at_1000
            value: 38.585
          - type: ndcg_at_3
            value: 36.868
          - type: ndcg_at_5
            value: 35.154999999999994
          - type: precision_at_1
            value: 43.653
          - type: precision_at_10
            value: 23.622
          - type: precision_at_100
            value: 7.7490000000000006
          - type: precision_at_1000
            value: 2.054
          - type: precision_at_3
            value: 34.262
          - type: precision_at_5
            value: 30.154999999999998
          - type: recall_at_1
            value: 5.163
          - type: recall_at_10
            value: 15.478
          - type: recall_at_100
            value: 30.424
          - type: recall_at_1000
            value: 62.67
          - type: recall_at_3
            value: 9.615
          - type: recall_at_5
            value: 12.369
      - task:
          type: Retrieval
        dataset:
          type: nq
          name: MTEB NQ
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 21.618000000000002
          - type: map_at_10
            value: 35.465
          - type: map_at_100
            value: 36.712
          - type: map_at_1000
            value: 36.757
          - type: map_at_3
            value: 31.189
          - type: map_at_5
            value: 33.537
          - type: mrr_at_1
            value: 24.305
          - type: mrr_at_10
            value: 37.653
          - type: mrr_at_100
            value: 38.662
          - type: mrr_at_1000
            value: 38.694
          - type: mrr_at_3
            value: 33.889
          - type: mrr_at_5
            value: 35.979
          - type: ndcg_at_1
            value: 24.305
          - type: ndcg_at_10
            value: 43.028
          - type: ndcg_at_100
            value: 48.653999999999996
          - type: ndcg_at_1000
            value: 49.733
          - type: ndcg_at_3
            value: 34.768
          - type: ndcg_at_5
            value: 38.753
          - type: precision_at_1
            value: 24.305
          - type: precision_at_10
            value: 7.59
          - type: precision_at_100
            value: 1.076
          - type: precision_at_1000
            value: 0.11800000000000001
          - type: precision_at_3
            value: 16.271
          - type: precision_at_5
            value: 12.068
          - type: recall_at_1
            value: 21.618000000000002
          - type: recall_at_10
            value: 63.977
          - type: recall_at_100
            value: 89.03999999999999
          - type: recall_at_1000
            value: 97.10600000000001
          - type: recall_at_3
            value: 42.422
          - type: recall_at_5
            value: 51.629000000000005
      - task:
          type: Retrieval
        dataset:
          type: quora
          name: MTEB QuoraRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 69.405
          - type: map_at_10
            value: 83.05
          - type: map_at_100
            value: 83.684
          - type: map_at_1000
            value: 83.70400000000001
          - type: map_at_3
            value: 80.08800000000001
          - type: map_at_5
            value: 81.937
          - type: mrr_at_1
            value: 79.85
          - type: mrr_at_10
            value: 86.369
          - type: mrr_at_100
            value: 86.48599999999999
          - type: mrr_at_1000
            value: 86.48700000000001
          - type: mrr_at_3
            value: 85.315
          - type: mrr_at_5
            value: 86.044
          - type: ndcg_at_1
            value: 79.86999999999999
          - type: ndcg_at_10
            value: 87.04499999999999
          - type: ndcg_at_100
            value: 88.373
          - type: ndcg_at_1000
            value: 88.531
          - type: ndcg_at_3
            value: 84.04
          - type: ndcg_at_5
            value: 85.684
          - type: precision_at_1
            value: 79.86999999999999
          - type: precision_at_10
            value: 13.183
          - type: precision_at_100
            value: 1.51
          - type: precision_at_1000
            value: 0.156
          - type: precision_at_3
            value: 36.67
          - type: precision_at_5
            value: 24.12
          - type: recall_at_1
            value: 69.405
          - type: recall_at_10
            value: 94.634
          - type: recall_at_100
            value: 99.214
          - type: recall_at_1000
            value: 99.958
          - type: recall_at_3
            value: 85.992
          - type: recall_at_5
            value: 90.656
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering
          name: MTEB RedditClustering
          config: default
          split: test
          revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
        metrics:
          - type: v_measure
            value: 50.191676323145465
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering-p2p
          name: MTEB RedditClusteringP2P
          config: default
          split: test
          revision: 282350215ef01743dc01b456c7f5241fa8937f16
        metrics:
          - type: v_measure
            value: 56.4874020363744
      - task:
          type: Retrieval
        dataset:
          type: scidocs
          name: MTEB SCIDOCS
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 4.228
          - type: map_at_10
            value: 11.245
          - type: map_at_100
            value: 13.353000000000002
          - type: map_at_1000
            value: 13.665
          - type: map_at_3
            value: 7.779999999999999
          - type: map_at_5
            value: 9.405
          - type: mrr_at_1
            value: 20.9
          - type: mrr_at_10
            value: 31.657999999999998
          - type: mrr_at_100
            value: 32.769999999999996
          - type: mrr_at_1000
            value: 32.833
          - type: mrr_at_3
            value: 28.333000000000002
          - type: mrr_at_5
            value: 30.043
          - type: ndcg_at_1
            value: 20.9
          - type: ndcg_at_10
            value: 19.073
          - type: ndcg_at_100
            value: 27.055
          - type: ndcg_at_1000
            value: 32.641
          - type: ndcg_at_3
            value: 17.483999999999998
          - type: ndcg_at_5
            value: 15.42
          - type: precision_at_1
            value: 20.9
          - type: precision_at_10
            value: 10.17
          - type: precision_at_100
            value: 2.162
          - type: precision_at_1000
            value: 0.35100000000000003
          - type: precision_at_3
            value: 16.467000000000002
          - type: precision_at_5
            value: 13.68
          - type: recall_at_1
            value: 4.228
          - type: recall_at_10
            value: 20.573
          - type: recall_at_100
            value: 43.887
          - type: recall_at_1000
            value: 71.22
          - type: recall_at_3
            value: 10.023
          - type: recall_at_5
            value: 13.873
      - task:
          type: STS
        dataset:
          type: mteb/sickr-sts
          name: MTEB SICK-R
          config: default
          split: test
          revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
        metrics:
          - type: cos_sim_pearson
            value: 82.77965135067481
          - type: cos_sim_spearman
            value: 75.85121335808076
          - type: euclidean_pearson
            value: 80.09115175262697
          - type: euclidean_spearman
            value: 75.72249155647123
          - type: manhattan_pearson
            value: 79.89723577351782
          - type: manhattan_spearman
            value: 75.49855259442387
      - task:
          type: STS
        dataset:
          type: mteb/sts12-sts
          name: MTEB STS12
          config: default
          split: test
          revision: a0d554a64d88156834ff5ae9920b964011b16384
        metrics:
          - type: cos_sim_pearson
            value: 80.46084116030949
          - type: cos_sim_spearman
            value: 72.57579204392951
          - type: euclidean_pearson
            value: 76.39020830763684
          - type: euclidean_spearman
            value: 72.3718627025895
          - type: manhattan_pearson
            value: 76.6148833027359
          - type: manhattan_spearman
            value: 72.57570008442319
      - task:
          type: STS
        dataset:
          type: mteb/sts13-sts
          name: MTEB STS13
          config: default
          split: test
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
        metrics:
          - type: cos_sim_pearson
            value: 80.43678068337017
          - type: cos_sim_spearman
            value: 82.38941154076062
          - type: euclidean_pearson
            value: 81.59260573633661
          - type: euclidean_spearman
            value: 82.31144262574114
          - type: manhattan_pearson
            value: 81.43266909137056
          - type: manhattan_spearman
            value: 82.14704293004861
      - task:
          type: STS
        dataset:
          type: mteb/sts14-sts
          name: MTEB STS14
          config: default
          split: test
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
        metrics:
          - type: cos_sim_pearson
            value: 80.73713431763163
          - type: cos_sim_spearman
            value: 77.97860512809388
          - type: euclidean_pearson
            value: 80.35755041527027
          - type: euclidean_spearman
            value: 78.021703511412
          - type: manhattan_pearson
            value: 80.24440317109162
          - type: manhattan_spearman
            value: 77.93165415697575
      - task:
          type: STS
        dataset:
          type: mteb/sts15-sts
          name: MTEB STS15
          config: default
          split: test
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
        metrics:
          - type: cos_sim_pearson
            value: 85.15111852351204
          - type: cos_sim_spearman
            value: 86.54032447238258
          - type: euclidean_pearson
            value: 86.14157021537433
          - type: euclidean_spearman
            value: 86.67537291929713
          - type: manhattan_pearson
            value: 86.081041854808
          - type: manhattan_spearman
            value: 86.61561701560558
      - task:
          type: STS
        dataset:
          type: mteb/sts16-sts
          name: MTEB STS16
          config: default
          split: test
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
        metrics:
          - type: cos_sim_pearson
            value: 81.34532445104026
          - type: cos_sim_spearman
            value: 83.31325001474116
          - type: euclidean_pearson
            value: 82.81892375201032
          - type: euclidean_spearman
            value: 83.4521695148055
          - type: manhattan_pearson
            value: 82.72503790526163
          - type: manhattan_spearman
            value: 83.37833652941349
      - 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: 87.25463453839801
          - type: cos_sim_spearman
            value: 88.27655263515948
          - type: euclidean_pearson
            value: 88.0248334411439
          - type: euclidean_spearman
            value: 88.18141448876868
          - type: manhattan_pearson
            value: 87.8080451127279
          - type: manhattan_spearman
            value: 88.01028114423058
      - 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: 63.57551045355218
          - type: cos_sim_spearman
            value: 66.67614095126629
          - type: euclidean_pearson
            value: 66.0787243112528
          - type: euclidean_spearman
            value: 66.83660560636939
          - type: manhattan_pearson
            value: 66.74684019662031
          - type: manhattan_spearman
            value: 67.11761598074368
      - task:
          type: STS
        dataset:
          type: mteb/stsbenchmark-sts
          name: MTEB STSBenchmark
          config: default
          split: test
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
        metrics:
          - type: cos_sim_pearson
            value: 83.70881496766829
          - type: cos_sim_spearman
            value: 84.37803542941634
          - type: euclidean_pearson
            value: 84.84501245857096
          - type: euclidean_spearman
            value: 84.47088079741476
          - type: manhattan_pearson
            value: 84.77244090794765
          - type: manhattan_spearman
            value: 84.43307343706205
      - task:
          type: Reranking
        dataset:
          type: mteb/scidocs-reranking
          name: MTEB SciDocsRR
          config: default
          split: test
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
        metrics:
          - type: map
            value: 81.53946254759089
          - type: mrr
            value: 94.68259953554072
      - task:
          type: Retrieval
        dataset:
          type: scifact
          name: MTEB SciFact
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 51.817
          - type: map_at_10
            value: 62.339999999999996
          - type: map_at_100
            value: 62.88
          - type: map_at_1000
            value: 62.909000000000006
          - type: map_at_3
            value: 59.004
          - type: map_at_5
            value: 60.906000000000006
          - type: mrr_at_1
            value: 54.333
          - type: mrr_at_10
            value: 63.649
          - type: mrr_at_100
            value: 64.01
          - type: mrr_at_1000
            value: 64.039
          - type: mrr_at_3
            value: 61.056
          - type: mrr_at_5
            value: 62.639
          - type: ndcg_at_1
            value: 54.333
          - type: ndcg_at_10
            value: 67.509
          - type: ndcg_at_100
            value: 69.69999999999999
          - type: ndcg_at_1000
            value: 70.613
          - type: ndcg_at_3
            value: 61.729
          - type: ndcg_at_5
            value: 64.696
          - type: precision_at_1
            value: 54.333
          - type: precision_at_10
            value: 9.2
          - type: precision_at_100
            value: 1.043
          - type: precision_at_1000
            value: 0.11199999999999999
          - type: precision_at_3
            value: 24
          - type: precision_at_5
            value: 16.2
          - type: recall_at_1
            value: 51.817
          - type: recall_at_10
            value: 82.056
          - type: recall_at_100
            value: 91.667
          - type: recall_at_1000
            value: 99
          - type: recall_at_3
            value: 66.717
          - type: recall_at_5
            value: 74.17200000000001
      - task:
          type: PairClassification
        dataset:
          type: mteb/sprintduplicatequestions-pairclassification
          name: MTEB SprintDuplicateQuestions
          config: default
          split: test
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
        metrics:
          - type: cos_sim_accuracy
            value: 99.82475247524752
          - type: cos_sim_ap
            value: 95.4781199603258
          - type: cos_sim_f1
            value: 91.16186693147964
          - type: cos_sim_precision
            value: 90.53254437869822
          - type: cos_sim_recall
            value: 91.8
          - type: dot_accuracy
            value: 99.75049504950495
          - type: dot_ap
            value: 93.05183539809457
          - type: dot_f1
            value: 87.31117824773412
          - type: dot_precision
            value: 87.93103448275862
          - type: dot_recall
            value: 86.7
          - type: euclidean_accuracy
            value: 99.82475247524752
          - type: euclidean_ap
            value: 95.38547978154382
          - type: euclidean_f1
            value: 91.16325511732403
          - type: euclidean_precision
            value: 91.02691924227318
          - type: euclidean_recall
            value: 91.3
          - type: manhattan_accuracy
            value: 99.82574257425742
          - type: manhattan_ap
            value: 95.47237521890308
          - type: manhattan_f1
            value: 91.27849355797821
          - type: manhattan_precision
            value: 90.47151277013754
          - type: manhattan_recall
            value: 92.10000000000001
          - type: max_accuracy
            value: 99.82574257425742
          - type: max_ap
            value: 95.4781199603258
          - type: max_f1
            value: 91.27849355797821
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering
          name: MTEB StackExchangeClustering
          config: default
          split: test
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
        metrics:
          - type: v_measure
            value: 57.542169376331245
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering-p2p
          name: MTEB StackExchangeClusteringP2P
          config: default
          split: test
          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
        metrics:
          - type: v_measure
            value: 35.74399302634387
      - task:
          type: Reranking
        dataset:
          type: mteb/stackoverflowdupquestions-reranking
          name: MTEB StackOverflowDupQuestions
          config: default
          split: test
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
        metrics:
          - type: map
            value: 49.65076347632749
          - type: mrr
            value: 50.418099057804945
      - task:
          type: Summarization
        dataset:
          type: mteb/summeval
          name: MTEB SummEval
          config: default
          split: test
          revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
        metrics:
          - type: cos_sim_pearson
            value: 29.73997756592847
          - type: cos_sim_spearman
            value: 29.465208011593308
          - type: dot_pearson
            value: 24.83735342474541
          - type: dot_spearman
            value: 26.005180528584855
      - task:
          type: Retrieval
        dataset:
          type: trec-covid
          name: MTEB TRECCOVID
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 0.208
          - type: map_at_10
            value: 1.434
          - type: map_at_100
            value: 7.829
          - type: map_at_1000
            value: 19.807
          - type: map_at_3
            value: 0.549
          - type: map_at_5
            value: 0.8330000000000001
          - type: mrr_at_1
            value: 78
          - type: mrr_at_10
            value: 85.35199999999999
          - type: mrr_at_100
            value: 85.673
          - type: mrr_at_1000
            value: 85.673
          - type: mrr_at_3
            value: 84.667
          - type: mrr_at_5
            value: 85.06700000000001
          - type: ndcg_at_1
            value: 72
          - type: ndcg_at_10
            value: 59.214999999999996
          - type: ndcg_at_100
            value: 44.681
          - type: ndcg_at_1000
            value: 43.035000000000004
          - type: ndcg_at_3
            value: 66.53099999999999
          - type: ndcg_at_5
            value: 63.23
          - type: precision_at_1
            value: 78
          - type: precision_at_10
            value: 62.4
          - type: precision_at_100
            value: 45.76
          - type: precision_at_1000
            value: 19.05
          - type: precision_at_3
            value: 71.333
          - type: precision_at_5
            value: 67.2
          - type: recall_at_1
            value: 0.208
          - type: recall_at_10
            value: 1.6580000000000001
          - type: recall_at_100
            value: 11.324
          - type: recall_at_1000
            value: 41.537
          - type: recall_at_3
            value: 0.579
          - type: recall_at_5
            value: 0.8959999999999999
      - task:
          type: Retrieval
        dataset:
          type: webis-touche2020
          name: MTEB Touche2020
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 2.442
          - type: map_at_10
            value: 8.863
          - type: map_at_100
            value: 14.606
          - type: map_at_1000
            value: 16.258
          - type: map_at_3
            value: 4.396
          - type: map_at_5
            value: 6.199000000000001
          - type: mrr_at_1
            value: 30.612000000000002
          - type: mrr_at_10
            value: 43.492
          - type: mrr_at_100
            value: 44.557
          - type: mrr_at_1000
            value: 44.557
          - type: mrr_at_3
            value: 40.816
          - type: mrr_at_5
            value: 42.143
          - type: ndcg_at_1
            value: 25.509999999999998
          - type: ndcg_at_10
            value: 22.076
          - type: ndcg_at_100
            value: 34.098
          - type: ndcg_at_1000
            value: 46.265
          - type: ndcg_at_3
            value: 24.19
          - type: ndcg_at_5
            value: 23.474
          - type: precision_at_1
            value: 30.612000000000002
          - type: precision_at_10
            value: 19.796
          - type: precision_at_100
            value: 7.286
          - type: precision_at_1000
            value: 1.5310000000000001
          - type: precision_at_3
            value: 25.85
          - type: precision_at_5
            value: 24.490000000000002
          - type: recall_at_1
            value: 2.442
          - type: recall_at_10
            value: 15.012
          - type: recall_at_100
            value: 45.865
          - type: recall_at_1000
            value: 82.958
          - type: recall_at_3
            value: 5.731
          - type: recall_at_5
            value: 9.301
      - task:
          type: Classification
        dataset:
          type: mteb/toxic_conversations_50k
          name: MTEB ToxicConversationsClassification
          config: default
          split: test
          revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
        metrics:
          - type: accuracy
            value: 70.974
          - type: ap
            value: 14.534996211286682
          - type: f1
            value: 54.785946183399005
      - task:
          type: Classification
        dataset:
          type: mteb/tweet_sentiment_extraction
          name: MTEB TweetSentimentExtractionClassification
          config: default
          split: test
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
        metrics:
          - type: accuracy
            value: 58.56819468024901
          - type: f1
            value: 58.92391487111204
      - task:
          type: Clustering
        dataset:
          type: mteb/twentynewsgroups-clustering
          name: MTEB TwentyNewsgroupsClustering
          config: default
          split: test
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
        metrics:
          - type: v_measure
            value: 43.273202335218194
      - task:
          type: PairClassification
        dataset:
          type: mteb/twittersemeval2015-pairclassification
          name: MTEB TwitterSemEval2015
          config: default
          split: test
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
        metrics:
          - type: cos_sim_accuracy
            value: 84.37742146986946
          - type: cos_sim_ap
            value: 68.1684129575579
          - type: cos_sim_f1
            value: 64.93475108748189
          - type: cos_sim_precision
            value: 59.89745876058849
          - type: cos_sim_recall
            value: 70.89709762532982
          - type: dot_accuracy
            value: 80.49710913750968
          - type: dot_ap
            value: 54.699790073944186
          - type: dot_f1
            value: 54.45130013221684
          - type: dot_precision
            value: 46.74612183125236
          - type: dot_recall
            value: 65.19788918205805
          - type: euclidean_accuracy
            value: 84.5085533766466
          - type: euclidean_ap
            value: 68.38835695236224
          - type: euclidean_f1
            value: 65.3391121002694
          - type: euclidean_precision
            value: 58.75289656625237
          - type: euclidean_recall
            value: 73.58839050131925
          - type: manhattan_accuracy
            value: 84.40126363473803
          - type: manhattan_ap
            value: 68.09539181555348
          - type: manhattan_f1
            value: 64.99028182701653
          - type: manhattan_precision
            value: 60.22062134173795
          - type: manhattan_recall
            value: 70.58047493403694
          - type: max_accuracy
            value: 84.5085533766466
          - type: max_ap
            value: 68.38835695236224
          - type: max_f1
            value: 65.3391121002694
      - task:
          type: PairClassification
        dataset:
          type: mteb/twitterurlcorpus-pairclassification
          name: MTEB TwitterURLCorpus
          config: default
          split: test
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
        metrics:
          - type: cos_sim_accuracy
            value: 88.34167733923235
          - type: cos_sim_ap
            value: 84.84136381147736
          - type: cos_sim_f1
            value: 77.01434980904001
          - type: cos_sim_precision
            value: 74.27937915742794
          - type: cos_sim_recall
            value: 79.95842315983985
          - type: dot_accuracy
            value: 85.06422944075756
          - type: dot_ap
            value: 76.49446747522325
          - type: dot_f1
            value: 71.11606520830432
          - type: dot_precision
            value: 64.93638676844785
          - type: dot_recall
            value: 78.59562673236834
          - type: euclidean_accuracy
            value: 88.45810532852097
          - type: euclidean_ap
            value: 84.91526721863501
          - type: euclidean_f1
            value: 77.04399001750662
          - type: euclidean_precision
            value: 74.62298867162133
          - type: euclidean_recall
            value: 79.62734832152756
          - type: manhattan_accuracy
            value: 88.46004579500912
          - type: manhattan_ap
            value: 84.81590026238194
          - type: manhattan_f1
            value: 76.97804626491822
          - type: manhattan_precision
            value: 73.79237288135593
          - type: manhattan_recall
            value: 80.45118570988605
          - type: max_accuracy
            value: 88.46004579500912
          - type: max_ap
            value: 84.91526721863501
          - type: max_f1
            value: 77.04399001750662
pipeline_tag: sentence-similarity
tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
  - transformers
  - mteb

{gte-tiny}

This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. It is distilled from thenlper/gte-small, with comparable (slightly worse) performance at around half the size.

Usage (Sentence-Transformers)

Using this model becomes easy when you have sentence-transformers installed:

pip install -U sentence-transformers

Then you can use the model like this:

from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('{MODEL_NAME}')
embeddings = model.encode(sentences)
print(embeddings)

Usage (HuggingFace Transformers)

Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.

from transformers import AutoTokenizer, AutoModel
import torch


#Mean Pooling - Take attention mask into account for correct averaging
def mean_pooling(model_output, attention_mask):
    token_embeddings = model_output[0] #First element of model_output contains all token embeddings
    input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
    return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)


# Sentences we want sentence embeddings for
sentences = ['This is an example sentence', 'Each sentence is converted']

# Load model from HuggingFace Hub
tokenizer = AutoTokenizer.from_pretrained('{MODEL_NAME}')
model = AutoModel.from_pretrained('{MODEL_NAME}')

# Tokenize sentences
encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')

# Compute token embeddings
with torch.no_grad():
    model_output = model(**encoded_input)

# Perform pooling. In this case, mean pooling.
sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask'])

print("Sentence embeddings:")
print(sentence_embeddings)

Evaluation Results

For an automated evaluation of this model, see the Sentence Embeddings Benchmark: https://seb.sbert.net

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
)

Citing & Authors