sentence-transformers onnx safetensors bert feature-extraction sentence-similarity bge mteb dataset:Mihaiii/qa-assistant license:mit model-index autotrain_compatible text-embeddings-inference endpoints_compatible region:us
---
datasets:
- Mihaiii/qa-assistant
library_name: sentence-transformers
license: mit
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- bge
- mteb
model-index:
- name: Wartortle
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 70.40298507462687
    - type: ap
      value: 32.88973775597331
    - type: f1
      value: 64.3726772221329
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 82.0381
    - type: ap
      value: 77.15483149750918
    - type: f1
      value: 81.97695449378108
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 42.412
    - type: f1
      value: 41.039684315409595
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 16.003
    - type: map_at_10
      value: 28.448
    - type: map_at_100
      value: 29.781999999999996
    - type: map_at_1000
      value: 29.822
    - type: map_at_20
      value: 29.278
    - type: map_at_3
      value: 23.874000000000002
    - type: map_at_5
      value: 26.491
    - type: mrr_at_1
      value: 16.714000000000002
    - type: mrr_at_10
      value: 28.727999999999998
    - type: mrr_at_100
      value: 30.055
    - type: mrr_at_1000
      value: 30.095
    - type: mrr_at_20
      value: 29.558
    - type: mrr_at_3
      value: 24.194
    - type: mrr_at_5
      value: 26.778999999999996
    - type: ndcg_at_1
      value: 16.003
    - type: ndcg_at_10
      value: 35.865
    - type: ndcg_at_100
      value: 42.304
    - type: ndcg_at_1000
      value: 43.333
    - type: ndcg_at_20
      value: 38.876
    - type: ndcg_at_3
      value: 26.436999999999998
    - type: ndcg_at_5
      value: 31.139
    - type: precision_at_1
      value: 16.003
    - type: precision_at_10
      value: 5.982
    - type: precision_at_100
      value: 0.898
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_20
      value: 3.585
    - type: precision_at_3
      value: 11.285
    - type: precision_at_5
      value: 9.046999999999999
    - type: recall_at_1
      value: 16.003
    - type: recall_at_10
      value: 59.815
    - type: recall_at_100
      value: 89.75800000000001
    - type: recall_at_1000
      value: 97.795
    - type: recall_at_20
      value: 71.693
    - type: recall_at_3
      value: 33.855000000000004
    - type: recall_at_5
      value: 45.235
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 35.843668514122115
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  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.0887502643707
    - type: mrr
      value: 67.73864485775843
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 78.95194509739122
    - type: cos_sim_spearman
      value: 80.77894903688735
    - type: euclidean_pearson
      value: 79.39078717146849
    - type: euclidean_spearman
      value: 80.77894903688735
    - type: manhattan_pearson
      value: 78.71356224958951
    - type: manhattan_spearman
      value: 80.19520079602864
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 71.07467532467531
    - type: f1
      value: 70.01947223710656
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.35131737359483
    - type: v_measures
      value:
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  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
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      value: 24.05979515497522
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      - 0.234905158950128
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      - 0.24547781895496315
      - 0.2539173622848027
      - 0.24423605317277747
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      - 0.2375355178050442
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      - 0.22861139295656668
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      - 0.2452790973282123
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      - 0.2539173622848027
      - 0.24423605317277747
      - 0.2375355178050442
      - 0.24890298326625343
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      - 0.22861139295656668
      - 0.23279193251929806
      - 0.234905158950128
      - 0.2452790973282123
      - 0.24547781895496315
      - 0.2539173622848027
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 20.799
    - type: map_at_10
      value: 28.028
    - type: map_at_100
      value: 29.066
    - type: map_at_1000
      value: 29.205
    - type: map_at_20
      value: 28.541
    - type: map_at_3
      value: 25.741000000000003
    - type: map_at_5
      value: 26.962000000000003
    - type: mrr_at_1
      value: 27.039
    - type: mrr_at_10
      value: 34.028000000000006
    - type: mrr_at_100
      value: 34.823
    - type: mrr_at_1000
      value: 34.894
    - type: mrr_at_20
      value: 34.476
    - type: mrr_at_3
      value: 31.855
    - type: mrr_at_5
      value: 33.114
    - type: ndcg_at_1
      value: 27.039
    - type: ndcg_at_10
      value: 32.958999999999996
    - type: ndcg_at_100
      value: 37.778
    - type: ndcg_at_1000
      value: 40.703
    - type: ndcg_at_20
      value: 34.58
    - type: ndcg_at_3
      value: 29.443
    - type: ndcg_at_5
      value: 30.887999999999998
    - type: precision_at_1
      value: 27.039
    - type: precision_at_10
      value: 6.252000000000001
    - type: precision_at_100
      value: 1.0659999999999998
    - type: precision_at_1000
      value: 0.16199999999999998
    - type: precision_at_20
      value: 3.705
    - type: precision_at_3
      value: 14.402000000000001
    - type: precision_at_5
      value: 10.157
    - type: recall_at_1
      value: 20.799
    - type: recall_at_10
      value: 41.819
    - type: recall_at_100
      value: 63.32299999999999
    - type: recall_at_1000
      value: 82.994
    - type: recall_at_20
      value: 48.024
    - type: recall_at_3
      value: 30.523
    - type: recall_at_5
      value: 35.214
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: mteb/cqadupstack-english
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 13.431999999999999
    - type: map_at_10
      value: 18.384
    - type: map_at_100
      value: 19.067999999999998
    - type: map_at_1000
      value: 19.178
    - type: map_at_20
      value: 18.732
    - type: map_at_3
      value: 16.834
    - type: map_at_5
      value: 17.758
    - type: mrr_at_1
      value: 16.624
    - type: mrr_at_10
      value: 21.467
    - type: mrr_at_100
      value: 22.126
    - type: mrr_at_1000
      value: 22.206
    - type: mrr_at_20
      value: 21.8
    - type: mrr_at_3
      value: 19.894000000000002
    - type: mrr_at_5
      value: 20.794999999999998
    - type: ndcg_at_1
      value: 16.624
    - type: ndcg_at_10
      value: 21.502
    - type: ndcg_at_100
      value: 25.006
    - type: ndcg_at_1000
      value: 27.842
    - type: ndcg_at_20
      value: 22.651
    - type: ndcg_at_3
      value: 18.857
    - type: ndcg_at_5
      value: 20.149
    - type: precision_at_1
      value: 16.624
    - type: precision_at_10
      value: 4.025
    - type: precision_at_100
      value: 0.705
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_20
      value: 2.408
    - type: precision_at_3
      value: 9.107999999999999
    - type: precision_at_5
      value: 6.561
    - type: recall_at_1
      value: 13.431999999999999
    - type: recall_at_10
      value: 27.648
    - type: recall_at_100
      value: 43.455
    - type: recall_at_1000
      value: 63.246
    - type: recall_at_20
      value: 31.896
    - type: recall_at_3
      value: 20.084
    - type: recall_at_5
      value: 23.593
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: mteb/cqadupstack-gaming
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 24.26
    - type: map_at_10
      value: 32.432
    - type: map_at_100
      value: 33.415
    - type: map_at_1000
      value: 33.512
    - type: map_at_20
      value: 32.949
    - type: map_at_3
      value: 29.938
    - type: map_at_5
      value: 31.328
    - type: mrr_at_1
      value: 27.900000000000002
    - type: mrr_at_10
      value: 35.449000000000005
    - type: mrr_at_100
      value: 36.293
    - type: mrr_at_1000
      value: 36.359
    - type: mrr_at_20
      value: 35.92
    - type: mrr_at_3
      value: 33.166000000000004
    - type: mrr_at_5
      value: 34.439
    - type: ndcg_at_1
      value: 27.900000000000002
    - type: ndcg_at_10
      value: 37.074
    - type: ndcg_at_100
      value: 41.786
    - type: ndcg_at_1000
      value: 44.01
    - type: ndcg_at_20
      value: 38.786
    - type: ndcg_at_3
      value: 32.440000000000005
    - type: ndcg_at_5
      value: 34.615
    - type: precision_at_1
      value: 27.900000000000002
    - type: precision_at_10
      value: 6.056
    - type: precision_at_100
      value: 0.924
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_20
      value: 3.4979999999999998
    - type: precision_at_3
      value: 14.274000000000001
    - type: precision_at_5
      value: 10.044
    - type: recall_at_1
      value: 24.26
    - type: recall_at_10
      value: 48.266
    - type: recall_at_100
      value: 69.433
    - type: recall_at_1000
      value: 85.419
    - type: recall_at_20
      value: 54.578
    - type: recall_at_3
      value: 35.776
    - type: recall_at_5
      value: 41.076
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: mteb/cqadupstack-gis
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 13.277
    - type: map_at_10
      value: 17.776
    - type: map_at_100
      value: 18.476
    - type: map_at_1000
      value: 18.572
    - type: map_at_20
      value: 18.102
    - type: map_at_3
      value: 16.072
    - type: map_at_5
      value: 17.085
    - type: mrr_at_1
      value: 14.237
    - type: mrr_at_10
      value: 19.051000000000002
    - type: mrr_at_100
      value: 19.728
    - type: mrr_at_1000
      value: 19.819
    - type: mrr_at_20
      value: 19.346
    - type: mrr_at_3
      value: 17.439
    - type: mrr_at_5
      value: 18.387999999999998
    - type: ndcg_at_1
      value: 14.237
    - type: ndcg_at_10
      value: 20.669999999999998
    - type: ndcg_at_100
      value: 24.58
    - type: ndcg_at_1000
      value: 27.557
    - type: ndcg_at_20
      value: 21.784
    - type: ndcg_at_3
      value: 17.369
    - type: ndcg_at_5
      value: 19.067999999999998
    - type: precision_at_1
      value: 14.237
    - type: precision_at_10
      value: 3.232
    - type: precision_at_100
      value: 0.5579999999999999
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_20
      value: 1.881
    - type: precision_at_3
      value: 7.3069999999999995
    - type: precision_at_5
      value: 5.333
    - type: recall_at_1
      value: 13.277
    - type: recall_at_10
      value: 28.496
    - type: recall_at_100
      value: 47.343
    - type: recall_at_1000
      value: 70.92699999999999
    - type: recall_at_20
      value: 32.646
    - type: recall_at_3
      value: 19.570999999999998
    - type: recall_at_5
      value: 23.624000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: mteb/cqadupstack-mathematica
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.329999999999999
    - type: map_at_10
      value: 10.16
    - type: map_at_100
      value: 11.004
    - type: map_at_1000
      value: 11.136
    - type: map_at_20
      value: 10.546999999999999
    - type: map_at_3
      value: 8.491
    - type: map_at_5
      value: 9.383
    - type: mrr_at_1
      value: 7.587000000000001
    - type: mrr_at_10
      value: 12.434000000000001
    - type: mrr_at_100
      value: 13.279
    - type: mrr_at_1000
      value: 13.377
    - type: mrr_at_20
      value: 12.855
    - type: mrr_at_3
      value: 10.282
    - type: mrr_at_5
      value: 11.42
    - type: ndcg_at_1
      value: 7.587000000000001
    - type: ndcg_at_10
      value: 13.239999999999998
    - type: ndcg_at_100
      value: 17.727999999999998
    - type: ndcg_at_1000
      value: 21.346
    - type: ndcg_at_20
      value: 14.649000000000001
    - type: ndcg_at_3
      value: 9.687
    - type: ndcg_at_5
      value: 11.306
    - type: precision_at_1
      value: 7.587000000000001
    - type: precision_at_10
      value: 2.749
    - type: precision_at_100
      value: 0.583
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_20
      value: 1.76
    - type: precision_at_3
      value: 4.643
    - type: precision_at_5
      value: 3.881
    - type: recall_at_1
      value: 6.329999999999999
    - type: recall_at_10
      value: 20.596999999999998
    - type: recall_at_100
      value: 40.642
    - type: recall_at_1000
      value: 67.268
    - type: recall_at_20
      value: 25.615
    - type: recall_at_3
      value: 11.036
    - type: recall_at_5
      value: 14.909
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: mteb/cqadupstack-physics
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 16.558
    - type: map_at_10
      value: 22.551
    - type: map_at_100
      value: 23.669
    - type: map_at_1000
      value: 23.809
    - type: map_at_20
      value: 23.173
    - type: map_at_3
      value: 20.681
    - type: map_at_5
      value: 21.674
    - type: mrr_at_1
      value: 20.693
    - type: mrr_at_10
      value: 27.133000000000003
    - type: mrr_at_100
      value: 28.073999999999998
    - type: mrr_at_1000
      value: 28.16
    - type: mrr_at_20
      value: 27.693
    - type: mrr_at_3
      value: 25.201
    - type: mrr_at_5
      value: 26.407999999999998
    - type: ndcg_at_1
      value: 20.693
    - type: ndcg_at_10
      value: 26.701999999999998
    - type: ndcg_at_100
      value: 32.031
    - type: ndcg_at_1000
      value: 35.265
    - type: ndcg_at_20
      value: 28.814
    - type: ndcg_at_3
      value: 23.474
    - type: ndcg_at_5
      value: 24.924
    - type: precision_at_1
      value: 20.693
    - type: precision_at_10
      value: 4.986
    - type: precision_at_100
      value: 0.915
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_20
      value: 3.157
    - type: precision_at_3
      value: 11.132
    - type: precision_at_5
      value: 8.027
    - type: recall_at_1
      value: 16.558
    - type: recall_at_10
      value: 34.636
    - type: recall_at_100
      value: 57.745999999999995
    - type: recall_at_1000
      value: 80.438
    - type: recall_at_20
      value: 42.248000000000005
    - type: recall_at_3
      value: 25.419999999999998
    - type: recall_at_5
      value: 29.254
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: mteb/cqadupstack-programmers
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 10.231
    - type: map_at_10
      value: 14.352
    - type: map_at_100
      value: 15.174000000000001
    - type: map_at_1000
      value: 15.310000000000002
    - type: map_at_20
      value: 14.704
    - type: map_at_3
      value: 12.878
    - type: map_at_5
      value: 13.632
    - type: mrr_at_1
      value: 12.556999999999999
    - type: mrr_at_10
      value: 17.378
    - type: mrr_at_100
      value: 18.186
    - type: mrr_at_1000
      value: 18.287
    - type: mrr_at_20
      value: 17.752000000000002
    - type: mrr_at_3
      value: 15.772
    - type: mrr_at_5
      value: 16.6
    - type: ndcg_at_1
      value: 12.556999999999999
    - type: ndcg_at_10
      value: 17.501
    - type: ndcg_at_100
      value: 22.065
    - type: ndcg_at_1000
      value: 25.607999999999997
    - type: ndcg_at_20
      value: 18.756
    - type: ndcg_at_3
      value: 14.691
    - type: ndcg_at_5
      value: 15.842
    - type: precision_at_1
      value: 12.556999999999999
    - type: precision_at_10
      value: 3.322
    - type: precision_at_100
      value: 0.6709999999999999
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_20
      value: 2.0549999999999997
    - type: precision_at_3
      value: 6.963
    - type: precision_at_5
      value: 5.137
    - type: recall_at_1
      value: 10.231
    - type: recall_at_10
      value: 24.2
    - type: recall_at_100
      value: 45.051
    - type: recall_at_1000
      value: 70.372
    - type: recall_at_20
      value: 28.624
    - type: recall_at_3
      value: 16.209
    - type: recall_at_5
      value: 19.259999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 13.304916666666664
    - type: map_at_10
      value: 18.2725
    - type: map_at_100
      value: 19.125249999999998
    - type: map_at_1000
      value: 19.246166666666664
    - type: map_at_20
      value: 18.682916666666667
    - type: map_at_3
      value: 16.61425
    - type: map_at_5
      value: 17.508000000000003
    - type: mrr_at_1
      value: 16.06625
    - type: mrr_at_10
      value: 21.317583333333335
    - type: mrr_at_100
      value: 22.106583333333333
    - type: mrr_at_1000
      value: 22.195
    - type: mrr_at_20
      value: 21.716500000000003
    - type: mrr_at_3
      value: 19.601666666666667
    - type: mrr_at_5
      value: 20.540333333333326
    - type: ndcg_at_1
      value: 16.06625
    - type: ndcg_at_10
      value: 21.690500000000004
    - type: ndcg_at_100
      value: 26.08625
    - type: ndcg_at_1000
      value: 29.223333333333336
    - type: ndcg_at_20
      value: 23.085083333333333
    - type: ndcg_at_3
      value: 18.621583333333337
    - type: ndcg_at_5
      value: 19.984999999999996
    - type: precision_at_1
      value: 16.06625
    - type: precision_at_10
      value: 3.9008333333333334
    - type: precision_at_100
      value: 0.7179166666666666
    - type: precision_at_1000
      value: 0.11541666666666667
    - type: precision_at_20
      value: 2.3684166666666666
    - type: precision_at_3
      value: 8.643
    - type: precision_at_5
      value: 6.230833333333333
    - type: recall_at_1
      value: 13.304916666666664
    - type: recall_at_10
      value: 29.081916666666665
    - type: recall_at_100
      value: 49.29125
    - type: recall_at_1000
      value: 72.18308333333331
    - type: recall_at_20
      value: 34.271499999999996
    - type: recall_at_3
      value: 20.34425
    - type: recall_at_5
      value: 23.923583333333333
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: mteb/cqadupstack-stats
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.539
    - type: map_at_10
      value: 14.783
    - type: map_at_100
      value: 15.542
    - type: map_at_1000
      value: 15.644
    - type: map_at_20
      value: 15.139
    - type: map_at_3
      value: 13.508999999999999
    - type: map_at_5
      value: 14.191
    - type: mrr_at_1
      value: 12.577
    - type: mrr_at_10
      value: 17.212
    - type: mrr_at_100
      value: 17.95
    - type: mrr_at_1000
      value: 18.043
    - type: mrr_at_20
      value: 17.563000000000002
    - type: mrr_at_3
      value: 15.951
    - type: mrr_at_5
      value: 16.587
    - type: ndcg_at_1
      value: 12.577
    - type: ndcg_at_10
      value: 17.683
    - type: ndcg_at_100
      value: 21.783
    - type: ndcg_at_1000
      value: 24.802
    - type: ndcg_at_20
      value: 18.944
    - type: ndcg_at_3
      value: 15.204999999999998
    - type: ndcg_at_5
      value: 16.274
    - type: precision_at_1
      value: 12.577
    - type: precision_at_10
      value: 2.991
    - type: precision_at_100
      value: 0.557
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_20
      value: 1.81
    - type: precision_at_3
      value: 6.952999999999999
    - type: precision_at_5
      value: 4.8469999999999995
    - type: recall_at_1
      value: 10.539
    - type: recall_at_10
      value: 24.541
    - type: recall_at_100
      value: 43.732
    - type: recall_at_1000
      value: 66.97800000000001
    - type: recall_at_20
      value: 29.331000000000003
    - type: recall_at_3
      value: 17.096
    - type: recall_at_5
      value: 20.080000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: mteb/cqadupstack-tex
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.954
    - type: map_at_10
      value: 11.091
    - type: map_at_100
      value: 11.828
    - type: map_at_1000
      value: 11.935
    - type: map_at_20
      value: 11.44
    - type: map_at_3
      value: 9.876
    - type: map_at_5
      value: 10.496
    - type: mrr_at_1
      value: 9.738
    - type: mrr_at_10
      value: 13.361
    - type: mrr_at_100
      value: 14.096
    - type: mrr_at_1000
      value: 14.184
    - type: mrr_at_20
      value: 13.721
    - type: mrr_at_3
      value: 12.004
    - type: mrr_at_5
      value: 12.658
    - type: ndcg_at_1
      value: 9.738
    - type: ndcg_at_10
      value: 13.592
    - type: ndcg_at_100
      value: 17.512
    - type: ndcg_at_1000
      value: 20.602999999999998
    - type: ndcg_at_20
      value: 14.789
    - type: ndcg_at_3
      value: 11.232000000000001
    - type: ndcg_at_5
      value: 12.191
    - type: precision_at_1
      value: 9.738
    - type: precision_at_10
      value: 2.598
    - type: precision_at_100
      value: 0.553
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_20
      value: 1.652
    - type: precision_at_3
      value: 5.311
    - type: precision_at_5
      value: 3.895
    - type: recall_at_1
      value: 7.954
    - type: recall_at_10
      value: 18.932
    - type: recall_at_100
      value: 37.082
    - type: recall_at_1000
      value: 60.114999999999995
    - type: recall_at_20
      value: 23.339
    - type: recall_at_3
      value: 12.318999999999999
    - type: recall_at_5
      value: 14.834
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: mteb/cqadupstack-unix
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 13.764999999999999
    - type: map_at_10
      value: 17.766000000000002
    - type: map_at_100
      value: 18.637999999999998
    - type: map_at_1000
      value: 18.755
    - type: map_at_20
      value: 18.242
    - type: map_at_3
      value: 16.502
    - type: map_at_5
      value: 17.155
    - type: mrr_at_1
      value: 16.604
    - type: mrr_at_10
      value: 21.071
    - type: mrr_at_100
      value: 21.906
    - type: mrr_at_1000
      value: 22.0
    - type: mrr_at_20
      value: 21.545
    - type: mrr_at_3
      value: 19.667
    - type: mrr_at_5
      value: 20.395
    - type: ndcg_at_1
      value: 16.604
    - type: ndcg_at_10
      value: 20.742
    - type: ndcg_at_100
      value: 25.363999999999997
    - type: ndcg_at_1000
      value: 28.607
    - type: ndcg_at_20
      value: 22.469
    - type: ndcg_at_3
      value: 18.276999999999997
    - type: ndcg_at_5
      value: 19.277
    - type: precision_at_1
      value: 16.604
    - type: precision_at_10
      value: 3.47
    - type: precision_at_100
      value: 0.651
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_20
      value: 2.169
    - type: precision_at_3
      value: 8.209
    - type: precision_at_5
      value: 5.7090000000000005
    - type: recall_at_1
      value: 13.764999999999999
    - type: recall_at_10
      value: 26.752
    - type: recall_at_100
      value: 47.988
    - type: recall_at_1000
      value: 71.859
    - type: recall_at_20
      value: 33.25
    - type: recall_at_3
      value: 19.777
    - type: recall_at_5
      value: 22.39
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: mteb/cqadupstack-webmasters
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.435999999999998
    - type: map_at_10
      value: 19.517
    - type: map_at_100
      value: 20.380000000000003
    - type: map_at_1000
      value: 20.558
    - type: map_at_20
      value: 19.858
    - type: map_at_3
      value: 17.764
    - type: map_at_5
      value: 18.705
    - type: mrr_at_1
      value: 18.182000000000002
    - type: mrr_at_10
      value: 23.342
    - type: mrr_at_100
      value: 24.121000000000002
    - type: mrr_at_1000
      value: 24.226
    - type: mrr_at_20
      value: 23.71
    - type: mrr_at_3
      value: 21.573999999999998
    - type: mrr_at_5
      value: 22.572
    - type: ndcg_at_1
      value: 18.182000000000002
    - type: ndcg_at_10
      value: 23.322000000000003
    - type: ndcg_at_100
      value: 27.529999999999998
    - type: ndcg_at_1000
      value: 31.434
    - type: ndcg_at_20
      value: 24.274
    - type: ndcg_at_3
      value: 20.307
    - type: ndcg_at_5
      value: 21.681
    - type: precision_at_1
      value: 18.182000000000002
    - type: precision_at_10
      value: 4.486
    - type: precision_at_100
      value: 0.907
    - type: precision_at_1000
      value: 0.17500000000000002
    - type: precision_at_20
      value: 2.727
    - type: precision_at_3
      value: 9.684
    - type: precision_at_5
      value: 7.074999999999999
    - type: recall_at_1
      value: 14.435999999999998
    - type: recall_at_10
      value: 30.221999999999998
    - type: recall_at_100
      value: 50.657
    - type: recall_at_1000
      value: 77.803
    - type: recall_at_20
      value: 34.044999999999995
    - type: recall_at_3
      value: 21.394
    - type: recall_at_5
      value: 25.058000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: mteb/cqadupstack-wordpress
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.078000000000001
    - type: map_at_10
      value: 12.43
    - type: map_at_100
      value: 13.242999999999999
    - type: map_at_1000
      value: 13.34
    - type: map_at_20
      value: 12.767999999999999
    - type: map_at_3
      value: 11.085
    - type: map_at_5
      value: 11.727
    - type: mrr_at_1
      value: 9.057
    - type: mrr_at_10
      value: 13.885
    - type: mrr_at_100
      value: 14.697
    - type: mrr_at_1000
      value: 14.785
    - type: mrr_at_20
      value: 14.216999999999999
    - type: mrr_at_3
      value: 12.415
    - type: mrr_at_5
      value: 13.108
    - type: ndcg_at_1
      value: 9.057
    - type: ndcg_at_10
      value: 15.299
    - type: ndcg_at_100
      value: 19.872
    - type: ndcg_at_1000
      value: 22.903000000000002
    - type: ndcg_at_20
      value: 16.525000000000002
    - type: ndcg_at_3
      value: 12.477
    - type: ndcg_at_5
      value: 13.605
    - type: precision_at_1
      value: 9.057
    - type: precision_at_10
      value: 2.643
    - type: precision_at_100
      value: 0.525
    - type: precision_at_1000
      value: 0.084
    - type: precision_at_20
      value: 1.599
    - type: precision_at_3
      value: 5.7299999999999995
    - type: precision_at_5
      value: 4.104
    - type: recall_at_1
      value: 8.078000000000001
    - type: recall_at_10
      value: 22.874
    - type: recall_at_100
      value: 45.043
    - type: recall_at_1000
      value: 68.77799999999999
    - type: recall_at_20
      value: 27.662
    - type: recall_at_3
      value: 14.926
    - type: recall_at_5
      value: 17.791
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: mteb/climate-fever
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 4.460999999999999
    - type: map_at_10
      value: 8.625
    - type: map_at_100
      value: 9.772
    - type: map_at_1000
      value: 9.952
    - type: map_at_20
      value: 9.133
    - type: map_at_3
      value: 6.961
    - type: map_at_5
      value: 7.727
    - type: mrr_at_1
      value: 9.381
    - type: mrr_at_10
      value: 16.742
    - type: mrr_at_100
      value: 17.901
    - type: mrr_at_1000
      value: 17.983
    - type: mrr_at_20
      value: 17.368
    - type: mrr_at_3
      value: 14.126
    - type: mrr_at_5
      value: 15.504000000000001
    - type: ndcg_at_1
      value: 9.381
    - type: ndcg_at_10
      value: 13.111
    - type: ndcg_at_100
      value: 19.043
    - type: ndcg_at_1000
      value: 22.901
    - type: ndcg_at_20
      value: 14.909
    - type: ndcg_at_3
      value: 9.727
    - type: ndcg_at_5
      value: 10.91
    - type: precision_at_1
      value: 9.381
    - type: precision_at_10
      value: 4.391
    - type: precision_at_100
      value: 1.075
    - type: precision_at_1000
      value: 0.178
    - type: precision_at_20
      value: 2.9739999999999998
    - type: precision_at_3
      value: 7.448
    - type: precision_at_5
      value: 5.954000000000001
    - type: recall_at_1
      value: 4.460999999999999
    - type: recall_at_10
      value: 17.657999999999998
    - type: recall_at_100
      value: 39.201
    - type: recall_at_1000
      value: 61.229
    - type: recall_at_20
      value: 22.758
    - type: recall_at_3
      value: 9.724
    - type: recall_at_5
      value: 12.651000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: mteb/dbpedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 5.849
    - type: map_at_10
      value: 12.828999999999999
    - type: map_at_100
      value: 17.204
    - type: map_at_1000
      value: 18.314
    - type: map_at_20
      value: 14.607000000000001
    - type: map_at_3
      value: 9.442
    - type: map_at_5
      value: 10.808
    - type: mrr_at_1
      value: 48.75
    - type: mrr_at_10
      value: 59.82300000000001
    - type: mrr_at_100
      value: 60.293
    - type: mrr_at_1000
      value: 60.307
    - type: mrr_at_20
      value: 60.131
    - type: mrr_at_3
      value: 57.208000000000006
    - type: mrr_at_5
      value: 58.583
    - type: ndcg_at_1
      value: 36.875
    - type: ndcg_at_10
      value: 29.328
    - type: ndcg_at_100
      value: 32.2
    - type: ndcg_at_1000
      value: 39.125
    - type: ndcg_at_20
      value: 28.674
    - type: ndcg_at_3
      value: 32.469
    - type: ndcg_at_5
      value: 30.613
    - type: precision_at_1
      value: 48.75
    - type: precision_at_10
      value: 24.099999999999998
    - type: precision_at_100
      value: 7.292999999999999
    - type: precision_at_1000
      value: 1.486
    - type: precision_at_20
      value: 17.812
    - type: precision_at_3
      value: 37.167
    - type: precision_at_5
      value: 31.1
    - type: recall_at_1
      value: 5.849
    - type: recall_at_10
      value: 18.473
    - type: recall_at_100
      value: 37.602000000000004
    - type: recall_at_1000
      value: 60.68599999999999
    - type: recall_at_20
      value: 23.552
    - type: recall_at_3
      value: 11.077
    - type: recall_at_5
      value: 13.511999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 46.78
    - type: f1
      value: 40.027922341568576
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: mteb/fever
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 21.675
    - type: map_at_10
      value: 30.4
    - type: map_at_100
      value: 31.285
    - type: map_at_1000
      value: 31.351000000000003
    - type: map_at_20
      value: 30.917
    - type: map_at_3
      value: 27.748
    - type: map_at_5
      value: 29.265
    - type: mrr_at_1
      value: 23.327
    - type: mrr_at_10
      value: 32.363
    - type: mrr_at_100
      value: 33.237
    - type: mrr_at_1000
      value: 33.298
    - type: mrr_at_20
      value: 32.883
    - type: mrr_at_3
      value: 29.665000000000003
    - type: mrr_at_5
      value: 31.230999999999998
    - type: ndcg_at_1
      value: 23.327
    - type: ndcg_at_10
      value: 35.576
    - type: ndcg_at_100
      value: 40.071
    - type: ndcg_at_1000
      value: 41.884
    - type: ndcg_at_20
      value: 37.431
    - type: ndcg_at_3
      value: 30.173
    - type: ndcg_at_5
      value: 32.883
    - type: precision_at_1
      value: 23.327
    - type: precision_at_10
      value: 5.438
    - type: precision_at_100
      value: 0.784
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_20
      value: 3.121
    - type: precision_at_3
      value: 12.741
    - type: precision_at_5
      value: 9.078999999999999
    - type: recall_at_1
      value: 21.675
    - type: recall_at_10
      value: 49.952999999999996
    - type: recall_at_100
      value: 70.953
    - type: recall_at_1000
      value: 84.902
    - type: recall_at_20
      value: 57.081
    - type: recall_at_3
      value: 35.301
    - type: recall_at_5
      value: 41.805
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: mteb/fiqa
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 3.096
    - type: map_at_10
      value: 5.4879999999999995
    - type: map_at_100
      value: 6.199000000000001
    - type: map_at_1000
      value: 6.348
    - type: map_at_20
      value: 5.826
    - type: map_at_3
      value: 4.43
    - type: map_at_5
      value: 4.899
    - type: mrr_at_1
      value: 6.481000000000001
    - type: mrr_at_10
      value: 10.059999999999999
    - type: mrr_at_100
      value: 10.905
    - type: mrr_at_1000
      value: 11.019
    - type: mrr_at_20
      value: 10.513
    - type: mrr_at_3
      value: 8.436
    - type: mrr_at_5
      value: 9.168999999999999
    - type: ndcg_at_1
      value: 6.481000000000001
    - type: ndcg_at_10
      value: 8.097999999999999
    - type: ndcg_at_100
      value: 12.092
    - type: ndcg_at_1000
      value: 16.5
    - type: ndcg_at_20
      value: 9.353
    - type: ndcg_at_3
      value: 6.148
    - type: ndcg_at_5
      value: 6.714
    - type: precision_at_1
      value: 6.481000000000001
    - type: precision_at_10
      value: 2.5309999999999997
    - type: precision_at_100
      value: 0.6479999999999999
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_20
      value: 1.752
    - type: precision_at_3
      value: 4.064
    - type: precision_at_5
      value: 3.272
    - type: recall_at_1
      value: 3.096
    - type: recall_at_10
      value: 11.575000000000001
    - type: recall_at_100
      value: 27.560000000000002
    - type: recall_at_1000
      value: 56.391999999999996
    - type: recall_at_20
      value: 15.611
    - type: recall_at_3
      value: 5.821
    - type: recall_at_5
      value: 7.6259999999999994
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: mteb/hotpotqa
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 27.481
    - type: map_at_10
      value: 38.229
    - type: map_at_100
      value: 39.186
    - type: map_at_1000
      value: 39.283
    - type: map_at_20
      value: 38.763999999999996
    - type: map_at_3
      value: 35.652
    - type: map_at_5
      value: 37.18
    - type: mrr_at_1
      value: 54.962999999999994
    - type: mrr_at_10
      value: 62.651999999999994
    - type: mrr_at_100
      value: 63.158
    - type: mrr_at_1000
      value: 63.18899999999999
    - type: mrr_at_20
      value: 62.965
    - type: mrr_at_3
      value: 61.013
    - type: mrr_at_5
      value: 62.004999999999995
    - type: ndcg_at_1
      value: 54.962999999999994
    - type: ndcg_at_10
      value: 47.03
    - type: ndcg_at_100
      value: 50.938
    - type: ndcg_at_1000
      value: 53.028
    - type: ndcg_at_20
      value: 48.571999999999996
    - type: ndcg_at_3
      value: 42.751
    - type: ndcg_at_5
      value: 44.981
    - type: precision_at_1
      value: 54.962999999999994
    - type: precision_at_10
      value: 9.919
    - type: precision_at_100
      value: 1.302
    - type: precision_at_1000
      value: 0.158
    - type: precision_at_20
      value: 5.4559999999999995
    - type: precision_at_3
      value: 26.671
    - type: precision_at_5
      value: 17.764
    - type: recall_at_1
      value: 27.481
    - type: recall_at_10
      value: 49.595
    - type: recall_at_100
      value: 65.078
    - type: recall_at_1000
      value: 79.001
    - type: recall_at_20
      value: 54.564
    - type: recall_at_3
      value: 40.007
    - type: recall_at_5
      value: 44.409
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 74.5976
    - type: ap
      value: 68.90030024726627
    - type: f1
      value: 74.44139933523756
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 9.392
    - type: map_at_10
      value: 15.858
    - type: map_at_100
      value: 16.821
    - type: map_at_1000
      value: 16.916999999999998
    - type: map_at_20
      value: 16.378
    - type: map_at_3
      value: 13.627
    - type: map_at_5
      value: 14.837
    - type: mrr_at_1
      value: 9.642000000000001
    - type: mrr_at_10
      value: 16.189999999999998
    - type: mrr_at_100
      value: 17.149
    - type: mrr_at_1000
      value: 17.241
    - type: mrr_at_20
      value: 16.712
    - type: mrr_at_3
      value: 13.94
    - type: mrr_at_5
      value: 15.173
    - type: ndcg_at_1
      value: 9.642000000000001
    - type: ndcg_at_10
      value: 19.798
    - type: ndcg_at_100
      value: 24.93
    - type: ndcg_at_1000
      value: 27.723
    - type: ndcg_at_20
      value: 21.676000000000002
    - type: ndcg_at_3
      value: 15.135000000000002
    - type: ndcg_at_5
      value: 17.323
    - type: precision_at_1
      value: 9.642000000000001
    - type: precision_at_10
      value: 3.335
    - type: precision_at_100
      value: 0.597
    - type: precision_at_1000
      value: 0.084
    - type: precision_at_20
      value: 2.052
    - type: precision_at_3
      value: 6.585000000000001
    - type: precision_at_5
      value: 5.0569999999999995
    - type: recall_at_1
      value: 9.392
    - type: recall_at_10
      value: 32.074000000000005
    - type: recall_at_100
      value: 56.816
    - type: recall_at_1000
      value: 79.107
    - type: recall_at_20
      value: 39.404
    - type: recall_at_3
      value: 19.211
    - type: recall_at_5
      value: 24.476
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.23529411764707
    - type: f1
      value: 87.7087794539205
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 54.9361605107159
    - type: f1
      value: 37.32757786855856
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 62.269670477471415
    - type: f1
      value: 59.31689853710541
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.21788836583724
    - type: f1
      value: 67.10588384512401
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
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      value: 28.23811395981688
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  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
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      value: 25.338025048309298
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  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.27968813284564
    - type: mrr
      value: 31.192897822243165
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 2.8930000000000002
    - type: map_at_10
      value: 5.63
    - type: map_at_100
      value: 6.981999999999999
    - type: map_at_1000
      value: 7.99
    - type: map_at_20
      value: 6.165
    - type: map_at_3
      value: 4.466
    - type: map_at_5
      value: 4.885
    - type: mrr_at_1
      value: 27.245
    - type: mrr_at_10
      value: 34.952
    - type: mrr_at_100
      value: 35.83
    - type: mrr_at_1000
      value: 35.892
    - type: mrr_at_20
      value: 35.464
    - type: mrr_at_3
      value: 32.611000000000004
    - type: mrr_at_5
      value: 33.725
    - type: ndcg_at_1
      value: 25.697
    - type: ndcg_at_10
      value: 18.746
    - type: ndcg_at_100
      value: 17.613
    - type: ndcg_at_1000
      value: 26.698
    - type: ndcg_at_20
      value: 17.607
    - type: ndcg_at_3
      value: 22.163
    - type: ndcg_at_5
      value: 20.497
    - type: precision_at_1
      value: 26.625
    - type: precision_at_10
      value: 13.437
    - type: precision_at_100
      value: 4.805000000000001
    - type: precision_at_1000
      value: 1.733
    - type: precision_at_20
      value: 10.17
    - type: precision_at_3
      value: 20.433
    - type: precision_at_5
      value: 17.214
    - type: recall_at_1
      value: 2.8930000000000002
    - type: recall_at_10
      value: 8.731
    - type: recall_at_100
      value: 19.236
    - type: recall_at_1000
      value: 50.632
    - type: recall_at_20
      value: 11.402
    - type: recall_at_3
      value: 5.207
    - type: recall_at_5
      value: 6.021
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 10.116999999999999
    - type: map_at_10
      value: 18.062
    - type: map_at_100
      value: 19.276
    - type: map_at_1000
      value: 19.366
    - type: map_at_20
      value: 18.719
    - type: map_at_3
      value: 15.018999999999998
    - type: map_at_5
      value: 16.659
    - type: mrr_at_1
      value: 11.587
    - type: mrr_at_10
      value: 19.75
    - type: mrr_at_100
      value: 20.855
    - type: mrr_at_1000
      value: 20.929000000000002
    - type: mrr_at_20
      value: 20.377000000000002
    - type: mrr_at_3
      value: 16.733999999999998
    - type: mrr_at_5
      value: 18.422
    - type: ndcg_at_1
      value: 11.559
    - type: ndcg_at_10
      value: 23.25
    - type: ndcg_at_100
      value: 29.364
    - type: ndcg_at_1000
      value: 31.775
    - type: ndcg_at_20
      value: 25.56
    - type: ndcg_at_3
      value: 17.052
    - type: ndcg_at_5
      value: 19.98
    - type: precision_at_1
      value: 11.559
    - type: precision_at_10
      value: 4.447
    - type: precision_at_100
      value: 0.796
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_20
      value: 2.762
    - type: precision_at_3
      value: 8.14
    - type: precision_at_5
      value: 6.524000000000001
    - type: recall_at_1
      value: 10.116999999999999
    - type: recall_at_10
      value: 37.736999999999995
    - type: recall_at_100
      value: 65.998
    - type: recall_at_1000
      value: 84.533
    - type: recall_at_20
      value: 46.43
    - type: recall_at_3
      value: 21.282
    - type: recall_at_5
      value: 28.1
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 64.706
    - type: map_at_10
      value: 77.777
    - type: map_at_100
      value: 78.509
    - type: map_at_1000
      value: 78.537
    - type: map_at_20
      value: 78.237
    - type: map_at_3
      value: 74.802
    - type: map_at_5
      value: 76.655
    - type: mrr_at_1
      value: 74.62
    - type: mrr_at_10
      value: 81.817
    - type: mrr_at_100
      value: 82.021
    - type: mrr_at_1000
      value: 82.025
    - type: mrr_at_20
      value: 81.962
    - type: mrr_at_3
      value: 80.452
    - type: mrr_at_5
      value: 81.352
    - type: ndcg_at_1
      value: 74.64
    - type: ndcg_at_10
      value: 82.30499999999999
    - type: ndcg_at_100
      value: 84.21
    - type: ndcg_at_1000
      value: 84.505
    - type: ndcg_at_20
      value: 83.255
    - type: ndcg_at_3
      value: 78.851
    - type: ndcg_at_5
      value: 80.72200000000001
    - type: precision_at_1
      value: 74.64
    - type: precision_at_10
      value: 12.457
    - type: precision_at_100
      value: 1.473
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_20
      value: 6.677
    - type: precision_at_3
      value: 34.29
    - type: precision_at_5
      value: 22.7
    - type: recall_at_1
      value: 64.706
    - type: recall_at_10
      value: 91.01
    - type: recall_at_100
      value: 98.039
    - type: recall_at_1000
      value: 99.66000000000001
    - type: recall_at_20
      value: 94.184
    - type: recall_at_3
      value: 81.12700000000001
    - type: recall_at_5
      value: 86.319
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 35.92118583596968
    - type: v_measures
      value:
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      - 0.5064461714989106
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      - 0.43921575409868097
      - 0.3495794570559578
      - 0.30573013564346774
      - 0.32165840125624
      - 0.3272115833286129
      - 0.48520494325401664
      - 0.33563783213490467
      - 0.31385131638717517
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      - 0.41972047648086824
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  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
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      value: 46.08479450077311
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  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 2.823
    - type: map_at_10
      value: 6.162999999999999
    - type: map_at_100
      value: 7.462000000000001
    - type: map_at_1000
      value: 7.707
    - type: map_at_20
      value: 6.7989999999999995
    - type: map_at_3
      value: 4.614
    - type: map_at_5
      value: 5.221
    - type: mrr_at_1
      value: 13.8
    - type: mrr_at_10
      value: 20.317
    - type: mrr_at_100
      value: 21.495
    - type: mrr_at_1000
      value: 21.609
    - type: mrr_at_20
      value: 21.038999999999998
    - type: mrr_at_3
      value: 17.916999999999998
    - type: mrr_at_5
      value: 19.047
    - type: ndcg_at_1
      value: 13.8
    - type: ndcg_at_10
      value: 11.124
    - type: ndcg_at_100
      value: 17.058
    - type: ndcg_at_1000
      value: 22.584
    - type: ndcg_at_20
      value: 13.165
    - type: ndcg_at_3
      value: 10.453999999999999
    - type: ndcg_at_5
      value: 8.844000000000001
    - type: precision_at_1
      value: 13.8
    - type: precision_at_10
      value: 5.800000000000001
    - type: precision_at_100
      value: 1.443
    - type: precision_at_1000
      value: 0.27899999999999997
    - type: precision_at_20
      value: 4.08
    - type: precision_at_3
      value: 9.5
    - type: precision_at_5
      value: 7.42
    - type: recall_at_1
      value: 2.823
    - type: recall_at_10
      value: 11.790000000000001
    - type: recall_at_100
      value: 29.282000000000004
    - type: recall_at_1000
      value: 56.720000000000006
    - type: recall_at_20
      value: 16.54
    - type: recall_at_3
      value: 5.808
    - type: recall_at_5
      value: 7.548000000000001
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 82.35546558185588
    - type: cos_sim_spearman
      value: 78.23859592249686
    - type: euclidean_pearson
      value: 79.98024519769696
    - type: euclidean_spearman
      value: 78.23859183509182
    - type: manhattan_pearson
      value: 79.89939470434149
    - type: manhattan_spearman
      value: 78.14002412024936
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 82.77892045885623
    - type: cos_sim_spearman
      value: 75.1886741501174
    - type: euclidean_pearson
      value: 79.25545188379738
    - type: euclidean_spearman
      value: 75.18638344905548
    - type: manhattan_pearson
      value: 79.22653149623625
    - type: manhattan_spearman
      value: 75.27810415336305
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.0780386627305
    - type: cos_sim_spearman
      value: 79.33304952540263
    - type: euclidean_pearson
      value: 78.8995877109086
    - type: euclidean_spearman
      value: 79.33304952540263
    - type: manhattan_pearson
      value: 78.53767885744242
    - type: manhattan_spearman
      value: 78.98963272082919
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.40102517193851
    - type: cos_sim_spearman
      value: 76.56213113240312
    - type: euclidean_pearson
      value: 77.28763789251809
    - type: euclidean_spearman
      value: 76.56214567337607
    - type: manhattan_pearson
      value: 77.07003484382906
    - type: manhattan_spearman
      value: 76.42170507923466
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 83.08619018791619
    - type: cos_sim_spearman
      value: 84.7000298638952
    - type: euclidean_pearson
      value: 84.45835118534818
    - type: euclidean_spearman
      value: 84.7000136316961
    - type: manhattan_pearson
      value: 84.49026098485562
    - type: manhattan_spearman
      value: 84.7341511290005
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 78.16153099155702
    - type: cos_sim_spearman
      value: 81.43851932231388
    - type: euclidean_pearson
      value: 80.64566170494548
    - type: euclidean_spearman
      value: 81.43851888295582
    - type: manhattan_pearson
      value: 80.60043965519766
    - type: manhattan_spearman
      value: 81.39436114361187
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 85.79691929686385
    - type: cos_sim_spearman
      value: 86.61476790521185
    - type: euclidean_pearson
      value: 87.19188107234186
    - type: euclidean_spearman
      value: 86.61476790521185
    - type: manhattan_pearson
      value: 87.1048361434476
    - type: manhattan_spearman
      value: 86.62564632760721
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 57.47315801345834
    - type: cos_sim_spearman
      value: 63.42561529682427
    - type: euclidean_pearson
      value: 61.72162209797075
    - type: euclidean_spearman
      value: 63.42561529682427
    - type: manhattan_pearson
      value: 61.90168887814704
    - type: manhattan_spearman
      value: 63.750754243527155
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 79.85854385132735
    - type: cos_sim_spearman
      value: 81.7934403165178
    - type: euclidean_pearson
      value: 81.76737446129472
    - type: euclidean_spearman
      value: 81.79344583519841
    - type: manhattan_pearson
      value: 81.51600708713269
    - type: manhattan_spearman
      value: 81.5208648976934
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 74.47725483163819
    - type: mrr
      value: 91.68947066005887
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 36.75
    - type: map_at_10
      value: 45.448
    - type: map_at_100
      value: 46.25
    - type: map_at_1000
      value: 46.333
    - type: map_at_20
      value: 45.965
    - type: map_at_3
      value: 42.848000000000006
    - type: map_at_5
      value: 44.098
    - type: mrr_at_1
      value: 39.0
    - type: mrr_at_10
      value: 46.916000000000004
    - type: mrr_at_100
      value: 47.61
    - type: mrr_at_1000
      value: 47.684
    - type: mrr_at_20
      value: 47.402
    - type: mrr_at_3
      value: 44.667
    - type: mrr_at_5
      value: 45.867000000000004
    - type: ndcg_at_1
      value: 39.0
    - type: ndcg_at_10
      value: 50.241
    - type: ndcg_at_100
      value: 53.701
    - type: ndcg_at_1000
      value: 55.84
    - type: ndcg_at_20
      value: 52.022
    - type: ndcg_at_3
      value: 45.248
    - type: ndcg_at_5
      value: 47.332
    - type: precision_at_1
      value: 39.0
    - type: precision_at_10
      value: 7.199999999999999
    - type: precision_at_100
      value: 0.903
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_20
      value: 3.9829999999999997
    - type: precision_at_3
      value: 18.333
    - type: precision_at_5
      value: 12.2
    - type: recall_at_1
      value: 36.75
    - type: recall_at_10
      value: 63.62799999999999
    - type: recall_at_100
      value: 78.85600000000001
    - type: recall_at_1000
      value: 95.6
    - type: recall_at_20
      value: 70.489
    - type: recall_at_3
      value: 49.928
    - type: recall_at_5
      value: 55.161
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.68514851485149
    - type: cos_sim_ap
      value: 89.84995835652664
    - type: cos_sim_f1
      value: 83.54037267080744
    - type: cos_sim_precision
      value: 86.58798283261802
    - type: cos_sim_recall
      value: 80.7
    - type: dot_accuracy
      value: 99.68514851485149
    - type: dot_ap
      value: 89.84995822010269
    - type: dot_f1
      value: 83.54037267080744
    - type: dot_precision
      value: 86.58798283261802
    - type: dot_recall
      value: 80.7
    - type: euclidean_accuracy
      value: 99.68514851485149
    - type: euclidean_ap
      value: 89.84995835652664
    - type: euclidean_f1
      value: 83.54037267080744
    - type: euclidean_precision
      value: 86.58798283261802
    - type: euclidean_recall
      value: 80.7
    - type: manhattan_accuracy
      value: 99.69504950495049
    - type: manhattan_ap
      value: 90.15934028795763
    - type: manhattan_f1
      value: 84.10256410256412
    - type: manhattan_precision
      value: 86.31578947368422
    - type: manhattan_recall
      value: 82.0
    - type: max_accuracy
      value: 99.69504950495049
    - type: max_ap
      value: 90.15934028795763
    - type: max_f1
      value: 84.10256410256412
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 45.30526182881455
    - type: v_measures
      value:
      - 0.4344425345974089
      - 0.5135881589154038
      - 0.37360609992777216
      - 0.44322308669982985
      - 0.4258373836686056
      - 0.37002419178401297
      - 0.3950750262645659
      - 0.4703810042020446
      - 0.4910523906839406
      - 0.45466057667041015
      - 0.5726496772458282
      - 0.4854711941992666
      - 0.5369040307391952
      - 0.47225744279530213
      - 0.4343396666563287
      - 0.43259528575250467
      - 0.4576684562107158
      - 0.4584484754489512
      - 0.45112618895014645
      - 0.4529676773831033
      - 0.46470509372382
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  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.907825848421005
    - type: v_measures
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  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 42.29730951798082
    - type: mrr
      value: 42.927117816823696
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.06400884629347
    - type: cos_sim_spearman
      value: 30.706758615234286
    - type: dot_pearson
      value: 31.064025024903586
    - type: dot_spearman
      value: 30.70979367079321
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.131
    - type: map_at_10
      value: 0.699
    - type: map_at_100
      value: 2.7279999999999998
    - type: map_at_1000
      value: 6.349
    - type: map_at_20
      value: 1.0999999999999999
    - type: map_at_3
      value: 0.292
    - type: map_at_5
      value: 0.422
    - type: mrr_at_1
      value: 48.0
    - type: mrr_at_10
      value: 56.233
    - type: mrr_at_100
      value: 57.57600000000001
    - type: mrr_at_1000
      value: 57.582
    - type: mrr_at_20
      value: 57.17100000000001
    - type: mrr_at_3
      value: 54.333
    - type: mrr_at_5
      value: 56.033
    - type: ndcg_at_1
      value: 44.0
    - type: ndcg_at_10
      value: 35.736000000000004
    - type: ndcg_at_100
      value: 23.53
    - type: ndcg_at_1000
      value: 20.848
    - type: ndcg_at_20
      value: 32.458
    - type: ndcg_at_3
      value: 40.765
    - type: ndcg_at_5
      value: 38.32
    - type: precision_at_1
      value: 48.0
    - type: precision_at_10
      value: 37.0
    - type: precision_at_100
      value: 23.44
    - type: precision_at_1000
      value: 9.754
    - type: precision_at_20
      value: 33.300000000000004
    - type: precision_at_3
      value: 42.667
    - type: precision_at_5
      value: 40.400000000000006
    - type: recall_at_1
      value: 0.131
    - type: recall_at_10
      value: 0.8789999999999999
    - type: recall_at_100
      value: 4.9590000000000005
    - type: recall_at_1000
      value: 19.534000000000002
    - type: recall_at_20
      value: 1.539
    - type: recall_at_3
      value: 0.314
    - type: recall_at_5
      value: 0.484
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.175
    - type: map_at_10
      value: 2.59
    - type: map_at_100
      value: 3.3169999999999997
    - type: map_at_1000
      value: 3.7449999999999997
    - type: map_at_20
      value: 2.881
    - type: map_at_3
      value: 1.76
    - type: map_at_5
      value: 2.2030000000000003
    - type: mrr_at_1
      value: 16.326999999999998
    - type: mrr_at_10
      value: 24.189
    - type: mrr_at_100
      value: 25.686999999999998
    - type: mrr_at_1000
      value: 25.743
    - type: mrr_at_20
      value: 24.937
    - type: mrr_at_3
      value: 22.448999999999998
    - type: mrr_at_5
      value: 23.366999999999997
    - type: ndcg_at_1
      value: 14.285999999999998
    - type: ndcg_at_10
      value: 8.001999999999999
    - type: ndcg_at_100
      value: 10.833
    - type: ndcg_at_1000
      value: 18.258
    - type: ndcg_at_20
      value: 7.707999999999999
    - type: ndcg_at_3
      value: 11.213
    - type: ndcg_at_5
      value: 9.934
    - type: precision_at_1
      value: 16.326999999999998
    - type: precision_at_10
      value: 7.3469999999999995
    - type: precision_at_100
      value: 2.4899999999999998
    - type: precision_at_1000
      value: 0.7100000000000001
    - type: precision_at_20
      value: 5.408
    - type: precision_at_3
      value: 12.925
    - type: precision_at_5
      value: 10.612
    - type: recall_at_1
      value: 1.175
    - type: recall_at_10
      value: 4.596
    - type: recall_at_100
      value: 14.41
    - type: recall_at_1000
      value: 39.294000000000004
    - type: recall_at_20
      value: 6.436999999999999
    - type: recall_at_3
      value: 2.367
    - type: recall_at_5
      value: 3.3230000000000004
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 65.1513671875
    - type: ap
      value: 12.303071109448203
    - type: f1
      value: 50.43533728860237
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 62.5438596491228
    - type: f1
      value: 62.69763355089073
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 31.692515423088473
    - type: v_measures
      value:
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  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 84.00190737318948
    - type: cos_sim_ap
      value: 67.48296380006165
    - type: cos_sim_f1
      value: 62.996718920889535
    - type: cos_sim_precision
      value: 58.39152962378914
    - type: cos_sim_recall
      value: 68.3905013192612
    - type: dot_accuracy
      value: 84.00190737318948
    - type: dot_ap
      value: 67.48295942427862
    - type: dot_f1
      value: 62.996718920889535
    - type: dot_precision
      value: 58.39152962378914
    - type: dot_recall
      value: 68.3905013192612
    - type: euclidean_accuracy
      value: 84.00190737318948
    - type: euclidean_ap
      value: 67.482961801317
    - type: euclidean_f1
      value: 62.996718920889535
    - type: euclidean_precision
      value: 58.39152962378914
    - type: euclidean_recall
      value: 68.3905013192612
    - type: manhattan_accuracy
      value: 83.94826250223521
    - type: manhattan_ap
      value: 67.32115101507013
    - type: manhattan_f1
      value: 62.665684830633275
    - type: manhattan_precision
      value: 58.5819183111519
    - type: manhattan_recall
      value: 67.36147757255937
    - type: max_accuracy
      value: 84.00190737318948
    - type: max_ap
      value: 67.48296380006165
    - type: max_f1
      value: 62.996718920889535
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.30286800946948
    - type: cos_sim_ap
      value: 84.5306725053528
    - type: cos_sim_f1
      value: 76.5947752126367
    - type: cos_sim_precision
      value: 75.56188192987715
    - type: cos_sim_recall
      value: 77.65629812134279
    - type: dot_accuracy
      value: 88.30286800946948
    - type: dot_ap
      value: 84.53066920468329
    - type: dot_f1
      value: 76.5947752126367
    - type: dot_precision
      value: 75.56188192987715
    - type: dot_recall
      value: 77.65629812134279
    - type: euclidean_accuracy
      value: 88.30286800946948
    - type: euclidean_ap
      value: 84.53066432305307
    - type: euclidean_f1
      value: 76.5947752126367
    - type: euclidean_precision
      value: 75.56188192987715
    - type: euclidean_recall
      value: 77.65629812134279
    - type: manhattan_accuracy
      value: 88.39795086738852
    - type: manhattan_ap
      value: 84.51446339083833
    - type: manhattan_f1
      value: 76.57867106644667
    - type: manhattan_precision
      value: 74.64181286549709
    - type: manhattan_recall
      value: 78.61872497690176
    - type: max_accuracy
      value: 88.39795086738852
    - type: max_ap
      value: 84.5306725053528
    - type: max_f1
      value: 76.5947752126367
---
# Wartortle

Wartortle is a distill of [bge-base-en-v1.5](BAAI/bge-base-en-v1.5).

## Intended purpose

<span style="color:blue">This model is designed for use in semantic-autocomplete ([click here for demo](https://mihaiii.github.io/semantic-autocomplete/)).</span>
Make sure you also pass `pipelineParams={{ pooling: "cls", normalize: true }}` since the default pooling in the component is mean.

## Usage

Other than within [semantic-autocomplete](https://github.com/Mihaiii/semantic-autocomplete), you can use this model same as [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5#usage).