---
base_model: Mihaiii/Bulbasaur
license: mit
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- gte
- mteb
datasets:
- Mihaiii/qa-assistant
model-index:
- name: Venusaur
  results:
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (en)
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 73.17910447761194
    - type: ap
      value: 35.29994612283548
    - type: f1
      value: 66.87845205993153
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_polarity
      name: MTEB AmazonPolarityClassification
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 79.993525
    - type: ap
      value: 74.7042261687233
    - type: f1
      value: 79.9004149386498
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (en)
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 39.656000000000006
    - type: f1
      value: 39.287139345446256
  - task:
      type: Retrieval
    dataset:
      type: mteb/arguana
      name: MTEB ArguAna
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 16.643
    - type: map_at_10
      value: 28.276
    - type: map_at_100
      value: 29.543999999999997
    - type: map_at_1000
      value: 29.595
    - type: map_at_20
      value: 29.043000000000003
    - type: map_at_3
      value: 24.739
    - type: map_at_5
      value: 26.592
    - type: mrr_at_1
      value: 17.639
    - type: mrr_at_10
      value: 28.631
    - type: mrr_at_100
      value: 29.891000000000002
    - type: mrr_at_1000
      value: 29.942999999999998
    - type: mrr_at_20
      value: 29.391000000000002
    - type: mrr_at_3
      value: 25.107000000000003
    - type: mrr_at_5
      value: 26.942
    - type: ndcg_at_1
      value: 16.643
    - type: ndcg_at_10
      value: 34.8
    - type: ndcg_at_100
      value: 41.179
    - type: ndcg_at_1000
      value: 42.564
    - type: ndcg_at_20
      value: 37.601
    - type: ndcg_at_3
      value: 27.356
    - type: ndcg_at_5
      value: 30.725
    - type: precision_at_1
      value: 16.643
    - type: precision_at_10
      value: 5.576
    - type: precision_at_100
      value: 0.861
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_20
      value: 3.343
    - type: precision_at_3
      value: 11.641
    - type: precision_at_5
      value: 8.634
    - type: recall_at_1
      value: 16.643
    - type: recall_at_10
      value: 55.761
    - type: recall_at_100
      value: 86.06
    - type: recall_at_1000
      value: 97.013
    - type: recall_at_20
      value: 66.85600000000001
    - type: recall_at_3
      value: 34.922
    - type: recall_at_5
      value: 43.172
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-p2p
      name: MTEB ArxivClusteringP2P
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 31.76467048453136
    - type: v_measures
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  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-s2s
      name: MTEB ArxivClusteringS2S
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 21.06388933035354
    - type: v_measures
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  - task:
      type: Reranking
    dataset:
      type: mteb/askubuntudupquestions-reranking
      name: MTEB AskUbuntuDupQuestions
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 53.770982215325056
    - type: mrr
      value: 68.00400123114805
  - task:
      type: STS
    dataset:
      type: mteb/biosses-sts
      name: MTEB BIOSSES
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 77.20301104745533
    - type: cos_sim_spearman
      value: 77.59453912854975
    - type: euclidean_pearson
      value: 74.21678798189272
    - type: euclidean_spearman
      value: 74.9956847311664
    - type: manhattan_pearson
      value: 74.55059214013183
    - type: manhattan_spearman
      value: 75.51557609531613
  - task:
      type: Classification
    dataset:
      type: mteb/banking77
      name: MTEB Banking77Classification
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 77.9512987012987
    - type: f1
      value: 77.89256430400536
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-p2p
      name: MTEB BiorxivClusteringP2P
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 29.83922611010262
    - type: v_measures
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  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-s2s
      name: MTEB BiorxivClusteringS2S
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 18.34253917925029
    - type: v_measures
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  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-android
      name: MTEB CQADupstackAndroidRetrieval
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 19.709
    - type: map_at_10
      value: 26.522000000000002
    - type: map_at_100
      value: 27.613
    - type: map_at_1000
      value: 27.750999999999998
    - type: map_at_20
      value: 27.033
    - type: map_at_3
      value: 24.127000000000002
    - type: map_at_5
      value: 25.319000000000003
    - type: mrr_at_1
      value: 24.607
    - type: mrr_at_10
      value: 31.776
    - type: mrr_at_100
      value: 32.629999999999995
    - type: mrr_at_1000
      value: 32.699
    - type: mrr_at_20
      value: 32.23
    - type: mrr_at_3
      value: 29.423
    - type: mrr_at_5
      value: 30.703000000000003
    - type: ndcg_at_1
      value: 24.607
    - type: ndcg_at_10
      value: 31.311
    - type: ndcg_at_100
      value: 36.412
    - type: ndcg_at_1000
      value: 39.428999999999995
    - type: ndcg_at_20
      value: 32.793
    - type: ndcg_at_3
      value: 27.388
    - type: ndcg_at_5
      value: 28.899
    - type: precision_at_1
      value: 24.607
    - type: precision_at_10
      value: 5.951
    - type: precision_at_100
      value: 1.083
    - type: precision_at_1000
      value: 0.165
    - type: precision_at_20
      value: 3.5479999999999996
    - type: precision_at_3
      value: 12.971
    - type: precision_at_5
      value: 9.356
    - type: recall_at_1
      value: 19.709
    - type: recall_at_10
      value: 40.274
    - type: recall_at_100
      value: 62.926
    - type: recall_at_1000
      value: 83.54599999999999
    - type: recall_at_20
      value: 45.585
    - type: recall_at_3
      value: 28.587
    - type: recall_at_5
      value: 32.967999999999996
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-english
      name: MTEB CQADupstackEnglishRetrieval
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 11.749
    - type: map_at_10
      value: 15.958
    - type: map_at_100
      value: 16.694
    - type: map_at_1000
      value: 16.805
    - type: map_at_20
      value: 16.325
    - type: map_at_3
      value: 14.469000000000001
    - type: map_at_5
      value: 15.286
    - type: mrr_at_1
      value: 14.521999999999998
    - type: mrr_at_10
      value: 19.076999999999998
    - type: mrr_at_100
      value: 19.785
    - type: mrr_at_1000
      value: 19.863
    - type: mrr_at_20
      value: 19.451999999999998
    - type: mrr_at_3
      value: 17.419999999999998
    - type: mrr_at_5
      value: 18.379
    - type: ndcg_at_1
      value: 14.521999999999998
    - type: ndcg_at_10
      value: 18.944
    - type: ndcg_at_100
      value: 22.685
    - type: ndcg_at_1000
      value: 25.562
    - type: ndcg_at_20
      value: 20.169999999999998
    - type: ndcg_at_3
      value: 16.18
    - type: ndcg_at_5
      value: 17.476
    - type: precision_at_1
      value: 14.521999999999998
    - type: precision_at_10
      value: 3.5409999999999995
    - type: precision_at_100
      value: 0.679
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_20
      value: 2.185
    - type: precision_at_3
      value: 7.495
    - type: precision_at_5
      value: 5.541
    - type: recall_at_1
      value: 11.749
    - type: recall_at_10
      value: 24.759999999999998
    - type: recall_at_100
      value: 41.54
    - type: recall_at_1000
      value: 61.836
    - type: recall_at_20
      value: 29.252
    - type: recall_at_3
      value: 17.278
    - type: recall_at_5
      value: 20.57
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-gaming
      name: MTEB CQADupstackGamingRetrieval
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 19.827
    - type: map_at_10
      value: 27.417
    - type: map_at_100
      value: 28.383000000000003
    - type: map_at_1000
      value: 28.483000000000004
    - type: map_at_20
      value: 27.901999999999997
    - type: map_at_3
      value: 25.3
    - type: map_at_5
      value: 26.432
    - type: mrr_at_1
      value: 22.947
    - type: mrr_at_10
      value: 30.279
    - type: mrr_at_100
      value: 31.1
    - type: mrr_at_1000
      value: 31.171
    - type: mrr_at_20
      value: 30.714000000000002
    - type: mrr_at_3
      value: 28.37
    - type: mrr_at_5
      value: 29.37
    - type: ndcg_at_1
      value: 22.947
    - type: ndcg_at_10
      value: 31.793
    - type: ndcg_at_100
      value: 36.571999999999996
    - type: ndcg_at_1000
      value: 39.106
    - type: ndcg_at_20
      value: 33.376
    - type: ndcg_at_3
      value: 27.872000000000003
    - type: ndcg_at_5
      value: 29.601
    - type: precision_at_1
      value: 22.947
    - type: precision_at_10
      value: 5.3420000000000005
    - type: precision_at_100
      value: 0.856
    - type: precision_at_1000
      value: 0.116
    - type: precision_at_20
      value: 3.107
    - type: precision_at_3
      value: 12.684999999999999
    - type: precision_at_5
      value: 8.790000000000001
    - type: recall_at_1
      value: 19.827
    - type: recall_at_10
      value: 42.191
    - type: recall_at_100
      value: 64.307
    - type: recall_at_1000
      value: 83.161
    - type: recall_at_20
      value: 48.046
    - type: recall_at_3
      value: 31.352999999999998
    - type: recall_at_5
      value: 35.783
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-gis
      name: MTEB CQADupstackGisRetrieval
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 11.802
    - type: map_at_10
      value: 15.799
    - type: map_at_100
      value: 16.53
    - type: map_at_1000
      value: 16.638
    - type: map_at_20
      value: 16.161
    - type: map_at_3
      value: 14.495
    - type: map_at_5
      value: 15.128
    - type: mrr_at_1
      value: 12.655
    - type: mrr_at_10
      value: 17.03
    - type: mrr_at_100
      value: 17.785999999999998
    - type: mrr_at_1000
      value: 17.88
    - type: mrr_at_20
      value: 17.416
    - type: mrr_at_3
      value: 15.65
    - type: mrr_at_5
      value: 16.305
    - type: ndcg_at_1
      value: 12.655
    - type: ndcg_at_10
      value: 18.411
    - type: ndcg_at_100
      value: 22.547
    - type: ndcg_at_1000
      value: 25.685999999999996
    - type: ndcg_at_20
      value: 19.732
    - type: ndcg_at_3
      value: 15.713
    - type: ndcg_at_5
      value: 16.821
    - type: precision_at_1
      value: 12.655
    - type: precision_at_10
      value: 2.904
    - type: precision_at_100
      value: 0.525
    - type: precision_at_1000
      value: 0.083
    - type: precision_at_20
      value: 1.7399999999999998
    - type: precision_at_3
      value: 6.6290000000000004
    - type: precision_at_5
      value: 4.655
    - type: recall_at_1
      value: 11.802
    - type: recall_at_10
      value: 25.373
    - type: recall_at_100
      value: 45.462
    - type: recall_at_1000
      value: 69.98299999999999
    - type: recall_at_20
      value: 30.455
    - type: recall_at_3
      value: 17.941
    - type: recall_at_5
      value: 20.61
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-mathematica
      name: MTEB CQADupstackMathematicaRetrieval
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.6739999999999995
    - type: map_at_10
      value: 10.181
    - type: map_at_100
      value: 11.138
    - type: map_at_1000
      value: 11.258
    - type: map_at_20
      value: 10.673
    - type: map_at_3
      value: 8.997
    - type: map_at_5
      value: 9.587
    - type: mrr_at_1
      value: 8.209
    - type: mrr_at_10
      value: 12.356
    - type: mrr_at_100
      value: 13.370000000000001
    - type: mrr_at_1000
      value: 13.466000000000001
    - type: mrr_at_20
      value: 12.889000000000001
    - type: mrr_at_3
      value: 10.821
    - type: mrr_at_5
      value: 11.604000000000001
    - type: ndcg_at_1
      value: 8.209
    - type: ndcg_at_10
      value: 12.849
    - type: ndcg_at_100
      value: 17.916
    - type: ndcg_at_1000
      value: 21.192
    - type: ndcg_at_20
      value: 14.643
    - type: ndcg_at_3
      value: 10.299
    - type: ndcg_at_5
      value: 11.350999999999999
    - type: precision_at_1
      value: 8.209
    - type: precision_at_10
      value: 2.5
    - type: precision_at_100
      value: 0.577
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_20
      value: 1.667
    - type: precision_at_3
      value: 5.017
    - type: precision_at_5
      value: 3.7560000000000002
    - type: recall_at_1
      value: 6.6739999999999995
    - type: recall_at_10
      value: 19.016
    - type: recall_at_100
      value: 41.806
    - type: recall_at_1000
      value: 65.605
    - type: recall_at_20
      value: 25.764
    - type: recall_at_3
      value: 12.030000000000001
    - type: recall_at_5
      value: 14.568
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-physics
      name: MTEB CQADupstackPhysicsRetrieval
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 12.133
    - type: map_at_10
      value: 17.32
    - type: map_at_100
      value: 18.294
    - type: map_at_1000
      value: 18.404
    - type: map_at_20
      value: 17.804000000000002
    - type: map_at_3
      value: 15.626000000000001
    - type: map_at_5
      value: 16.572
    - type: mrr_at_1
      value: 15.399
    - type: mrr_at_10
      value: 21.054000000000002
    - type: mrr_at_100
      value: 21.951999999999998
    - type: mrr_at_1000
      value: 22.03
    - type: mrr_at_20
      value: 21.522
    - type: mrr_at_3
      value: 19.297
    - type: mrr_at_5
      value: 20.294
    - type: ndcg_at_1
      value: 15.399
    - type: ndcg_at_10
      value: 21.02
    - type: ndcg_at_100
      value: 25.978
    - type: ndcg_at_1000
      value: 28.803
    - type: ndcg_at_20
      value: 22.642
    - type: ndcg_at_3
      value: 17.864
    - type: ndcg_at_5
      value: 19.335
    - type: precision_at_1
      value: 15.399
    - type: precision_at_10
      value: 3.9079999999999995
    - type: precision_at_100
      value: 0.781
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_20
      value: 2.493
    - type: precision_at_3
      value: 8.502
    - type: precision_at_5
      value: 6.16
    - type: recall_at_1
      value: 12.133
    - type: recall_at_10
      value: 28.753
    - type: recall_at_100
      value: 50.806
    - type: recall_at_1000
      value: 70.75399999999999
    - type: recall_at_20
      value: 34.485
    - type: recall_at_3
      value: 19.664
    - type: recall_at_5
      value: 23.566000000000003
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-programmers
      name: MTEB CQADupstackProgrammersRetrieval
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 9.555
    - type: map_at_10
      value: 13.553
    - type: map_at_100
      value: 14.438
    - type: map_at_1000
      value: 14.562
    - type: map_at_20
      value: 13.977999999999998
    - type: map_at_3
      value: 12.118
    - type: map_at_5
      value: 12.811
    - type: mrr_at_1
      value: 11.872
    - type: mrr_at_10
      value: 16.613
    - type: mrr_at_100
      value: 17.512
    - type: mrr_at_1000
      value: 17.607
    - type: mrr_at_20
      value: 17.108
    - type: mrr_at_3
      value: 15.068000000000001
    - type: mrr_at_5
      value: 15.839
    - type: ndcg_at_1
      value: 11.872
    - type: ndcg_at_10
      value: 16.556
    - type: ndcg_at_100
      value: 21.34
    - type: ndcg_at_1000
      value: 24.903
    - type: ndcg_at_20
      value: 18.102
    - type: ndcg_at_3
      value: 13.844000000000001
    - type: ndcg_at_5
      value: 14.893999999999998
    - type: precision_at_1
      value: 11.872
    - type: precision_at_10
      value: 3.082
    - type: precision_at_100
      value: 0.658
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_20
      value: 1.992
    - type: precision_at_3
      value: 6.544999999999999
    - type: precision_at_5
      value: 4.68
    - type: recall_at_1
      value: 9.555
    - type: recall_at_10
      value: 22.931
    - type: recall_at_100
      value: 44.535000000000004
    - type: recall_at_1000
      value: 70.77799999999999
    - type: recall_at_20
      value: 28.403
    - type: recall_at_3
      value: 15.201
    - type: recall_at_5
      value: 18.145
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack
      name: MTEB CQADupstackRetrieval
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.476083333333333
    - type: map_at_10
      value: 16.002499999999998
    - type: map_at_100
      value: 16.875083333333333
    - type: map_at_1000
      value: 16.991916666666665
    - type: map_at_20
      value: 16.445416666666667
    - type: map_at_3
      value: 14.473666666666668
    - type: map_at_5
      value: 15.269583333333333
    - type: mrr_at_1
      value: 13.799083333333334
    - type: mrr_at_10
      value: 18.69941666666667
    - type: mrr_at_100
      value: 19.54075
    - type: mrr_at_1000
      value: 19.62791666666667
    - type: mrr_at_20
      value: 19.15166666666667
    - type: mrr_at_3
      value: 17.079666666666665
    - type: mrr_at_5
      value: 17.93583333333333
    - type: ndcg_at_1
      value: 13.799083333333334
    - type: ndcg_at_10
      value: 19.157583333333335
    - type: ndcg_at_100
      value: 23.675666666666668
    - type: ndcg_at_1000
      value: 26.761499999999998
    - type: ndcg_at_20
      value: 20.688416666666665
    - type: ndcg_at_3
      value: 16.23775
    - type: ndcg_at_5
      value: 17.494500000000002
    - type: precision_at_1
      value: 13.799083333333334
    - type: precision_at_10
      value: 3.449666666666667
    - type: precision_at_100
      value: 0.6782499999999999
    - type: precision_at_1000
      value: 0.11108333333333333
    - type: precision_at_20
      value: 2.1610833333333335
    - type: precision_at_3
      value: 7.496333333333332
    - type: precision_at_5
      value: 5.4156666666666675
    - type: recall_at_1
      value: 11.476083333333333
    - type: recall_at_10
      value: 26.132916666666667
    - type: recall_at_100
      value: 46.88099999999999
    - type: recall_at_1000
      value: 69.47425
    - type: recall_at_20
      value: 31.838583333333336
    - type: recall_at_3
      value: 17.943749999999998
    - type: recall_at_5
      value: 21.176833333333335
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-stats
      name: MTEB CQADupstackStatsRetrieval
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.166
    - type: map_at_10
      value: 13.980999999999998
    - type: map_at_100
      value: 14.728
    - type: map_at_1000
      value: 14.812
    - type: map_at_20
      value: 14.338000000000001
    - type: map_at_3
      value: 12.5
    - type: map_at_5
      value: 13.408000000000001
    - type: mrr_at_1
      value: 11.503
    - type: mrr_at_10
      value: 15.799
    - type: mrr_at_100
      value: 16.539
    - type: mrr_at_1000
      value: 16.614
    - type: mrr_at_20
      value: 16.155
    - type: mrr_at_3
      value: 14.213000000000001
    - type: mrr_at_5
      value: 15.201999999999998
    - type: ndcg_at_1
      value: 11.503
    - type: ndcg_at_10
      value: 16.647000000000002
    - type: ndcg_at_100
      value: 20.84
    - type: ndcg_at_1000
      value: 23.385
    - type: ndcg_at_20
      value: 17.93
    - type: ndcg_at_3
      value: 13.761999999999999
    - type: ndcg_at_5
      value: 15.311
    - type: precision_at_1
      value: 11.503
    - type: precision_at_10
      value: 2.7449999999999997
    - type: precision_at_100
      value: 0.541
    - type: precision_at_1000
      value: 0.082
    - type: precision_at_20
      value: 1.6789999999999998
    - type: precision_at_3
      value: 6.033
    - type: precision_at_5
      value: 4.5089999999999995
    - type: recall_at_1
      value: 10.166
    - type: recall_at_10
      value: 23.284
    - type: recall_at_100
      value: 43.224000000000004
    - type: recall_at_1000
      value: 62.856
    - type: recall_at_20
      value: 28.166000000000004
    - type: recall_at_3
      value: 15.396
    - type: recall_at_5
      value: 19.248
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-tex
      name: MTEB CQADupstackTexRetrieval
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 6.516
    - type: map_at_10
      value: 9.185
    - type: map_at_100
      value: 9.795
    - type: map_at_1000
      value: 9.902
    - type: map_at_20
      value: 9.508999999999999
    - type: map_at_3
      value: 8.245
    - type: map_at_5
      value: 8.724
    - type: mrr_at_1
      value: 8.121
    - type: mrr_at_10
      value: 11.228
    - type: mrr_at_100
      value: 11.885
    - type: mrr_at_1000
      value: 11.978
    - type: mrr_at_20
      value: 11.583
    - type: mrr_at_3
      value: 10.145999999999999
    - type: mrr_at_5
      value: 10.688
    - type: ndcg_at_1
      value: 8.121
    - type: ndcg_at_10
      value: 11.245
    - type: ndcg_at_100
      value: 14.524999999999999
    - type: ndcg_at_1000
      value: 17.62
    - type: ndcg_at_20
      value: 12.385
    - type: ndcg_at_3
      value: 9.429
    - type: ndcg_at_5
      value: 10.181999999999999
    - type: precision_at_1
      value: 8.121
    - type: precision_at_10
      value: 2.137
    - type: precision_at_100
      value: 0.451
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_20
      value: 1.387
    - type: precision_at_3
      value: 4.4510000000000005
    - type: precision_at_5
      value: 3.2620000000000005
    - type: recall_at_1
      value: 6.516
    - type: recall_at_10
      value: 15.456
    - type: recall_at_100
      value: 30.709999999999997
    - type: recall_at_1000
      value: 53.854
    - type: recall_at_20
      value: 19.756
    - type: recall_at_3
      value: 10.41
    - type: recall_at_5
      value: 12.317
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-unix
      name: MTEB CQADupstackUnixRetrieval
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 10.955
    - type: map_at_10
      value: 14.689
    - type: map_at_100
      value: 15.482000000000001
    - type: map_at_1000
      value: 15.614
    - type: map_at_20
      value: 15.085
    - type: map_at_3
      value: 13.318
    - type: map_at_5
      value: 13.950999999999999
    - type: mrr_at_1
      value: 13.34
    - type: mrr_at_10
      value: 17.514
    - type: mrr_at_100
      value: 18.3
    - type: mrr_at_1000
      value: 18.406
    - type: mrr_at_20
      value: 17.924
    - type: mrr_at_3
      value: 15.920000000000002
    - type: mrr_at_5
      value: 16.625
    - type: ndcg_at_1
      value: 13.34
    - type: ndcg_at_10
      value: 17.574
    - type: ndcg_at_100
      value: 21.909
    - type: ndcg_at_1000
      value: 25.402
    - type: ndcg_at_20
      value: 19.017
    - type: ndcg_at_3
      value: 14.75
    - type: ndcg_at_5
      value: 15.787999999999998
    - type: precision_at_1
      value: 13.34
    - type: precision_at_10
      value: 3.041
    - type: precision_at_100
      value: 0.599
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 1.908
    - type: precision_at_3
      value: 6.529999999999999
    - type: precision_at_5
      value: 4.646
    - type: recall_at_1
      value: 10.955
    - type: recall_at_10
      value: 23.831
    - type: recall_at_100
      value: 43.747
    - type: recall_at_1000
      value: 69.327
    - type: recall_at_20
      value: 29.17
    - type: recall_at_3
      value: 16.165
    - type: recall_at_5
      value: 18.701
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-webmasters
      name: MTEB CQADupstackWebmastersRetrieval
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 11.936
    - type: map_at_10
      value: 16.878
    - type: map_at_100
      value: 17.921
    - type: map_at_1000
      value: 18.093
    - type: map_at_20
      value: 17.468
    - type: map_at_3
      value: 15.21
    - type: map_at_5
      value: 16.056
    - type: mrr_at_1
      value: 15.02
    - type: mrr_at_10
      value: 20.023
    - type: mrr_at_100
      value: 20.965
    - type: mrr_at_1000
      value: 21.060000000000002
    - type: mrr_at_20
      value: 20.576
    - type: mrr_at_3
      value: 18.215
    - type: mrr_at_5
      value: 19.134
    - type: ndcg_at_1
      value: 15.02
    - type: ndcg_at_10
      value: 20.459
    - type: ndcg_at_100
      value: 25.163999999999998
    - type: ndcg_at_1000
      value: 28.811999999999998
    - type: ndcg_at_20
      value: 22.387
    - type: ndcg_at_3
      value: 17.265
    - type: ndcg_at_5
      value: 18.605
    - type: precision_at_1
      value: 15.02
    - type: precision_at_10
      value: 3.9530000000000003
    - type: precision_at_100
      value: 0.8659999999999999
    - type: precision_at_1000
      value: 0.173
    - type: precision_at_20
      value: 2.619
    - type: precision_at_3
      value: 8.169
    - type: precision_at_5
      value: 6.047000000000001
    - type: recall_at_1
      value: 11.936
    - type: recall_at_10
      value: 27.694999999999997
    - type: recall_at_100
      value: 49.159000000000006
    - type: recall_at_1000
      value: 74.134
    - type: recall_at_20
      value: 35.258
    - type: recall_at_3
      value: 18.54
    - type: recall_at_5
      value: 21.959
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-wordpress
      name: MTEB CQADupstackWordpressRetrieval
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 6.691
    - type: map_at_10
      value: 10.546999999999999
    - type: map_at_100
      value: 11.485
    - type: map_at_1000
      value: 11.581
    - type: map_at_20
      value: 11.068999999999999
    - type: map_at_3
      value: 9.279
    - type: map_at_5
      value: 9.961
    - type: mrr_at_1
      value: 7.394
    - type: mrr_at_10
      value: 11.644
    - type: mrr_at_100
      value: 12.665000000000001
    - type: mrr_at_1000
      value: 12.761
    - type: mrr_at_20
      value: 12.251
    - type: mrr_at_3
      value: 10.413
    - type: mrr_at_5
      value: 11.087
    - type: ndcg_at_1
      value: 7.394
    - type: ndcg_at_10
      value: 13.081999999999999
    - type: ndcg_at_100
      value: 18.22
    - type: ndcg_at_1000
      value: 21.238
    - type: ndcg_at_20
      value: 15.084
    - type: ndcg_at_3
      value: 10.487
    - type: ndcg_at_5
      value: 11.671
    - type: precision_at_1
      value: 7.394
    - type: precision_at_10
      value: 2.292
    - type: precision_at_100
      value: 0.523
    - type: precision_at_1000
      value: 0.083
    - type: precision_at_20
      value: 1.608
    - type: precision_at_3
      value: 4.929
    - type: precision_at_5
      value: 3.5860000000000003
    - type: recall_at_1
      value: 6.691
    - type: recall_at_10
      value: 20.031
    - type: recall_at_100
      value: 44.35
    - type: recall_at_1000
      value: 67.857
    - type: recall_at_20
      value: 27.723
    - type: recall_at_3
      value: 12.76
    - type: recall_at_5
      value: 15.687000000000001
  - task:
      type: Retrieval
    dataset:
      type: mteb/climate-fever
      name: MTEB ClimateFEVER
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 3.218
    - type: map_at_10
      value: 5.554
    - type: map_at_100
      value: 6.216
    - type: map_at_1000
      value: 6.338000000000001
    - type: map_at_20
      value: 5.907
    - type: map_at_3
      value: 4.707
    - type: map_at_5
      value: 5.094
    - type: mrr_at_1
      value: 6.84
    - type: mrr_at_10
      value: 11.296000000000001
    - type: mrr_at_100
      value: 12.224
    - type: mrr_at_1000
      value: 12.31
    - type: mrr_at_20
      value: 11.791
    - type: mrr_at_3
      value: 9.609
    - type: mrr_at_5
      value: 10.404
    - type: ndcg_at_1
      value: 6.84
    - type: ndcg_at_10
      value: 8.346
    - type: ndcg_at_100
      value: 12.06
    - type: ndcg_at_1000
      value: 15.132000000000001
    - type: ndcg_at_20
      value: 9.652
    - type: ndcg_at_3
      value: 6.489000000000001
    - type: ndcg_at_5
      value: 7.045999999999999
    - type: precision_at_1
      value: 6.84
    - type: precision_at_10
      value: 2.658
    - type: precision_at_100
      value: 0.655
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_20
      value: 1.863
    - type: precision_at_3
      value: 4.691
    - type: precision_at_5
      value: 3.6479999999999997
    - type: recall_at_1
      value: 3.218
    - type: recall_at_10
      value: 10.725
    - type: recall_at_100
      value: 24.131
    - type: recall_at_1000
      value: 42.106
    - type: recall_at_20
      value: 14.539
    - type: recall_at_3
      value: 6.3020000000000005
    - type: recall_at_5
      value: 7.763000000000001
  - task:
      type: Retrieval
    dataset:
      type: mteb/dbpedia
      name: MTEB DBPedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.506
    - type: map_at_10
      value: 8.535
    - type: map_at_100
      value: 11.072
    - type: map_at_1000
      value: 11.764
    - type: map_at_20
      value: 9.492
    - type: map_at_3
      value: 6.697
    - type: map_at_5
      value: 7.452
    - type: mrr_at_1
      value: 36.75
    - type: mrr_at_10
      value: 46.35
    - type: mrr_at_100
      value: 47.034
    - type: mrr_at_1000
      value: 47.08
    - type: mrr_at_20
      value: 46.784
    - type: mrr_at_3
      value: 44.0
    - type: mrr_at_5
      value: 45.262
    - type: ndcg_at_1
      value: 29.25
    - type: ndcg_at_10
      value: 21.318
    - type: ndcg_at_100
      value: 23.449
    - type: ndcg_at_1000
      value: 29.267
    - type: ndcg_at_20
      value: 20.735
    - type: ndcg_at_3
      value: 24.45
    - type: ndcg_at_5
      value: 22.637999999999998
    - type: precision_at_1
      value: 36.75
    - type: precision_at_10
      value: 16.775000000000002
    - type: precision_at_100
      value: 5.212
    - type: precision_at_1000
      value: 1.167
    - type: precision_at_20
      value: 12.225
    - type: precision_at_3
      value: 26.917
    - type: precision_at_5
      value: 22.0
    - type: recall_at_1
      value: 4.506
    - type: recall_at_10
      value: 12.341000000000001
    - type: recall_at_100
      value: 26.723000000000003
    - type: recall_at_1000
      value: 46.293
    - type: recall_at_20
      value: 15.903
    - type: recall_at_3
      value: 7.994999999999999
    - type: recall_at_5
      value: 9.407
  - task:
      type: Classification
    dataset:
      type: mteb/emotion
      name: MTEB EmotionClassification
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 44.375
    - type: f1
      value: 39.487258967288
  - task:
      type: Retrieval
    dataset:
      type: mteb/fever
      name: MTEB FEVER
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 16.572
    - type: map_at_10
      value: 22.349
    - type: map_at_100
      value: 23.145
    - type: map_at_1000
      value: 23.22
    - type: map_at_20
      value: 22.771
    - type: map_at_3
      value: 20.326
    - type: map_at_5
      value: 21.404
    - type: mrr_at_1
      value: 17.657
    - type: mrr_at_10
      value: 23.679
    - type: mrr_at_100
      value: 24.504
    - type: mrr_at_1000
      value: 24.576999999999998
    - type: mrr_at_20
      value: 24.122
    - type: mrr_at_3
      value: 21.557000000000002
    - type: mrr_at_5
      value: 22.695
    - type: ndcg_at_1
      value: 17.657
    - type: ndcg_at_10
      value: 26.081
    - type: ndcg_at_100
      value: 30.366
    - type: ndcg_at_1000
      value: 32.607
    - type: ndcg_at_20
      value: 27.608
    - type: ndcg_at_3
      value: 21.85
    - type: ndcg_at_5
      value: 23.796999999999997
    - type: precision_at_1
      value: 17.657
    - type: precision_at_10
      value: 3.968
    - type: precision_at_100
      value: 0.626
    - type: precision_at_1000
      value: 0.083
    - type: precision_at_20
      value: 2.3120000000000003
    - type: precision_at_3
      value: 8.951
    - type: precision_at_5
      value: 6.4
    - type: recall_at_1
      value: 16.572
    - type: recall_at_10
      value: 36.634
    - type: recall_at_100
      value: 57.135000000000005
    - type: recall_at_1000
      value: 74.832
    - type: recall_at_20
      value: 42.491
    - type: recall_at_3
      value: 25.087
    - type: recall_at_5
      value: 29.744999999999997
  - task:
      type: Retrieval
    dataset:
      type: mteb/fiqa
      name: MTEB FiQA2018
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 4.891
    - type: map_at_10
      value: 8.346
    - type: map_at_100
      value: 9.286
    - type: map_at_1000
      value: 9.465
    - type: map_at_20
      value: 8.826
    - type: map_at_3
      value: 7.13
    - type: map_at_5
      value: 7.643999999999999
    - type: mrr_at_1
      value: 10.030999999999999
    - type: mrr_at_10
      value: 14.899000000000001
    - type: mrr_at_100
      value: 15.82
    - type: mrr_at_1000
      value: 15.931000000000001
    - type: mrr_at_20
      value: 15.408
    - type: mrr_at_3
      value: 13.169
    - type: mrr_at_5
      value: 13.971
    - type: ndcg_at_1
      value: 10.030999999999999
    - type: ndcg_at_10
      value: 11.713
    - type: ndcg_at_100
      value: 16.436999999999998
    - type: ndcg_at_1000
      value: 20.971999999999998
    - type: ndcg_at_20
      value: 13.341
    - type: ndcg_at_3
      value: 9.879999999999999
    - type: ndcg_at_5
      value: 10.249
    - type: precision_at_1
      value: 10.030999999999999
    - type: precision_at_10
      value: 3.519
    - type: precision_at_100
      value: 0.8330000000000001
    - type: precision_at_1000
      value: 0.16
    - type: precision_at_20
      value: 2.377
    - type: precision_at_3
      value: 6.687
    - type: precision_at_5
      value: 5.0
    - type: recall_at_1
      value: 4.891
    - type: recall_at_10
      value: 15.221000000000002
    - type: recall_at_100
      value: 33.432
    - type: recall_at_1000
      value: 62.475
    - type: recall_at_20
      value: 20.467
    - type: recall_at_3
      value: 9.393
    - type: recall_at_5
      value: 11.214
  - task:
      type: Retrieval
    dataset:
      type: mteb/hotpotqa
      name: MTEB HotpotQA
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 22.856
    - type: map_at_10
      value: 30.656
    - type: map_at_100
      value: 31.447000000000003
    - type: map_at_1000
      value: 31.545
    - type: map_at_20
      value: 31.066
    - type: map_at_3
      value: 28.692
    - type: map_at_5
      value: 29.817
    - type: mrr_at_1
      value: 45.712
    - type: mrr_at_10
      value: 52.481
    - type: mrr_at_100
      value: 53.049
    - type: mrr_at_1000
      value: 53.09
    - type: mrr_at_20
      value: 52.803999999999995
    - type: mrr_at_3
      value: 50.709
    - type: mrr_at_5
      value: 51.795
    - type: ndcg_at_1
      value: 45.712
    - type: ndcg_at_10
      value: 38.381
    - type: ndcg_at_100
      value: 41.965
    - type: ndcg_at_1000
      value: 44.234
    - type: ndcg_at_20
      value: 39.657
    - type: ndcg_at_3
      value: 34.776
    - type: ndcg_at_5
      value: 36.622
    - type: precision_at_1
      value: 45.712
    - type: precision_at_10
      value: 8.062999999999999
    - type: precision_at_100
      value: 1.094
    - type: precision_at_1000
      value: 0.13999999999999999
    - type: precision_at_20
      value: 4.443
    - type: precision_at_3
      value: 21.476
    - type: precision_at_5
      value: 14.35
    - type: recall_at_1
      value: 22.856
    - type: recall_at_10
      value: 40.317
    - type: recall_at_100
      value: 54.705999999999996
    - type: recall_at_1000
      value: 69.892
    - type: recall_at_20
      value: 44.429
    - type: recall_at_3
      value: 32.214999999999996
    - type: recall_at_5
      value: 35.874
  - task:
      type: Classification
    dataset:
      type: mteb/imdb
      name: MTEB ImdbClassification
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 73.02000000000001
    - type: ap
      value: 67.25944041954726
    - type: f1
      value: 72.8697134997555
  - task:
      type: Retrieval
    dataset:
      type: mteb/msmarco
      name: MTEB MSMARCO
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 8.751000000000001
    - type: map_at_10
      value: 13.916999999999998
    - type: map_at_100
      value: 14.684
    - type: map_at_1000
      value: 14.766000000000002
    - type: map_at_20
      value: 14.338999999999999
    - type: map_at_3
      value: 12.197
    - type: map_at_5
      value: 13.163
    - type: mrr_at_1
      value: 8.911
    - type: mrr_at_10
      value: 14.198
    - type: mrr_at_100
      value: 14.960999999999999
    - type: mrr_at_1000
      value: 15.040000000000001
    - type: mrr_at_20
      value: 14.616999999999999
    - type: mrr_at_3
      value: 12.452
    - type: mrr_at_5
      value: 13.427
    - type: ndcg_at_1
      value: 8.911
    - type: ndcg_at_10
      value: 16.963
    - type: ndcg_at_100
      value: 21.062
    - type: ndcg_at_1000
      value: 23.543
    - type: ndcg_at_20
      value: 18.482000000000003
    - type: ndcg_at_3
      value: 13.391
    - type: ndcg_at_5
      value: 15.139
    - type: precision_at_1
      value: 8.911
    - type: precision_at_10
      value: 2.741
    - type: precision_at_100
      value: 0.485
    - type: precision_at_1000
      value: 0.06999999999999999
    - type: precision_at_20
      value: 1.683
    - type: precision_at_3
      value: 5.688
    - type: precision_at_5
      value: 4.3069999999999995
    - type: recall_at_1
      value: 8.751000000000001
    - type: recall_at_10
      value: 26.368000000000002
    - type: recall_at_100
      value: 46.22
    - type: recall_at_1000
      value: 66.22
    - type: recall_at_20
      value: 32.291
    - type: recall_at_3
      value: 16.595
    - type: recall_at_5
      value: 20.802
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (en)
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.87232102143183
    - type: f1
      value: 89.25570902684863
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (en)
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 71.02599179206568
    - type: f1
      value: 52.14883678941826
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (en)
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 67.74714189643576
    - type: f1
      value: 65.4738868705899
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (en)
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 72.36381977135171
    - type: f1
      value: 71.5956356866047
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-p2p
      name: MTEB MedrxivClusteringP2P
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.418721421866266
    - type: v_measures
      value: [0.25699019421325164, 0.2551070596948231, 0.2691672146325009, 0.263190709241409, 0.25833683058459567, 0.2969925236078273, 0.2799007926692717, 0.29259126151386433, 0.2840268235473181, 0.2855687324817643, 0.25699019421325164, 0.2551070596948231, 0.2691672146325009, 0.263190709241409, 0.25833683058459567, 0.2969925236078273, 0.2799007926692717, 0.29259126151386433, 0.2840268235473181, 0.2855687324817643, 0.25699019421325164, 0.2551070596948231, 0.2691672146325009, 0.263190709241409, 0.25833683058459567, 0.2969925236078273, 0.2799007926692717, 0.29259126151386433, 0.2840268235473181, 0.2855687324817643, 0.25699019421325164, 0.2551070596948231, 0.2691672146325009, 0.263190709241409, 0.25833683058459567, 0.2969925236078273, 0.2799007926692717, 0.29259126151386433, 0.2840268235473181, 0.2855687324817643, 0.25699019421325164, 0.2551070596948231, 0.2691672146325009, 0.263190709241409, 0.25833683058459567, 0.2969925236078273, 0.2799007926692717, 0.29259126151386433, 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  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-s2s
      name: MTEB MedrxivClusteringS2S
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 22.40590099674712
    - type: v_measures
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  - task:
      type: Reranking
    dataset:
      type: mteb/mind_small
      name: MTEB MindSmallReranking
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.924796610724826
    - type: mrr
      value: 30.962158101843464
  - task:
      type: Retrieval
    dataset:
      type: mteb/nfcorpus
      name: MTEB NFCorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 1.3379999999999999
    - type: map_at_10
      value: 3.62
    - type: map_at_100
      value: 4.891
    - type: map_at_1000
      value: 5.87
    - type: map_at_20
      value: 4.164000000000001
    - type: map_at_3
      value: 2.608
    - type: map_at_5
      value: 3.1910000000000003
    - type: mrr_at_1
      value: 18.576
    - type: mrr_at_10
      value: 26.487
    - type: mrr_at_100
      value: 27.736
    - type: mrr_at_1000
      value: 27.828000000000003
    - type: mrr_at_20
      value: 27.319
    - type: mrr_at_3
      value: 23.891000000000002
    - type: mrr_at_5
      value: 25.501
    - type: ndcg_at_1
      value: 17.957
    - type: ndcg_at_10
      value: 14.021
    - type: ndcg_at_100
      value: 14.41
    - type: ndcg_at_1000
      value: 24.197
    - type: ndcg_at_20
      value: 13.883000000000001
    - type: ndcg_at_3
      value: 15.913
    - type: ndcg_at_5
      value: 15.120000000000001
    - type: precision_at_1
      value: 18.576
    - type: precision_at_10
      value: 10.402000000000001
    - type: precision_at_100
      value: 4.334
    - type: precision_at_1000
      value: 1.661
    - type: precision_at_20
      value: 8.731
    - type: precision_at_3
      value: 15.067
    - type: precision_at_5
      value: 12.940999999999999
    - type: recall_at_1
      value: 1.3379999999999999
    - type: recall_at_10
      value: 6.711
    - type: recall_at_100
      value: 16.862
    - type: recall_at_1000
      value: 52.537
    - type: recall_at_20
      value: 9.89
    - type: recall_at_3
      value: 3.614
    - type: recall_at_5
      value: 5.428999999999999
  - task:
      type: Retrieval
    dataset:
      type: mteb/nq
      name: MTEB NQ
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 10.187
    - type: map_at_10
      value: 16.61
    - type: map_at_100
      value: 17.599
    - type: map_at_1000
      value: 17.689
    - type: map_at_20
      value: 17.141000000000002
    - type: map_at_3
      value: 14.405000000000001
    - type: map_at_5
      value: 15.543000000000001
    - type: mrr_at_1
      value: 11.327
    - type: mrr_at_10
      value: 18.184
    - type: mrr_at_100
      value: 19.137
    - type: mrr_at_1000
      value: 19.215
    - type: mrr_at_20
      value: 18.717
    - type: mrr_at_3
      value: 15.918
    - type: mrr_at_5
      value: 17.052
    - type: ndcg_at_1
      value: 11.327
    - type: ndcg_at_10
      value: 20.744
    - type: ndcg_at_100
      value: 25.865
    - type: ndcg_at_1000
      value: 28.419
    - type: ndcg_at_20
      value: 22.648
    - type: ndcg_at_3
      value: 16.147
    - type: ndcg_at_5
      value: 18.168
    - type: precision_at_1
      value: 11.327
    - type: precision_at_10
      value: 3.7220000000000004
    - type: precision_at_100
      value: 0.658
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_20
      value: 2.294
    - type: precision_at_3
      value: 7.503
    - type: precision_at_5
      value: 5.608
    - type: recall_at_1
      value: 10.187
    - type: recall_at_10
      value: 32.051
    - type: recall_at_100
      value: 56.016
    - type: recall_at_1000
      value: 75.649
    - type: recall_at_20
      value: 39.267
    - type: recall_at_3
      value: 19.689
    - type: recall_at_5
      value: 24.445
  - task:
      type: Retrieval
    dataset:
      type: mteb/quora
      name: MTEB QuoraRetrieval
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 58.404
    - type: map_at_10
      value: 70.125
    - type: map_at_100
      value: 70.923
    - type: map_at_1000
      value: 70.968
    - type: map_at_20
      value: 70.60300000000001
    - type: map_at_3
      value: 67.342
    - type: map_at_5
      value: 68.97999999999999
    - type: mrr_at_1
      value: 67.29
    - type: mrr_at_10
      value: 74.773
    - type: mrr_at_100
      value: 75.093
    - type: mrr_at_1000
      value: 75.106
    - type: mrr_at_20
      value: 74.973
    - type: mrr_at_3
      value: 73.188
    - type: mrr_at_5
      value: 74.165
    - type: ndcg_at_1
      value: 67.33
    - type: ndcg_at_10
      value: 74.936
    - type: ndcg_at_100
      value: 77.479
    - type: ndcg_at_1000
      value: 78.147
    - type: ndcg_at_20
      value: 76.048
    - type: ndcg_at_3
      value: 71.30499999999999
    - type: ndcg_at_5
      value: 73.09400000000001
    - type: precision_at_1
      value: 67.33
    - type: precision_at_10
      value: 11.335
    - type: precision_at_100
      value: 1.385
    - type: precision_at_1000
      value: 0.151
    - type: precision_at_20
      value: 6.116
    - type: precision_at_3
      value: 30.833
    - type: precision_at_5
      value: 20.384
    - type: recall_at_1
      value: 58.404
    - type: recall_at_10
      value: 84.138
    - type: recall_at_100
      value: 94.32000000000001
    - type: recall_at_1000
      value: 98.51299999999999
    - type: recall_at_20
      value: 87.996
    - type: recall_at_3
      value: 73.68400000000001
    - type: recall_at_5
      value: 78.681
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering
      name: MTEB RedditClustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 26.713463922652704
    - type: v_measures
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  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering-p2p
      name: MTEB RedditClusteringP2P
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: v_measure
      value: 44.135854520709856
    - type: v_measures
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  - task:
      type: Retrieval
    dataset:
      type: mteb/scidocs
      name: MTEB SCIDOCS
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 2.1350000000000002
    - type: map_at_10
      value: 5.118
    - type: map_at_100
      value: 6.08
    - type: map_at_1000
      value: 6.308
    - type: map_at_20
      value: 5.562
    - type: map_at_3
      value: 3.804
    - type: map_at_5
      value: 4.468
    - type: mrr_at_1
      value: 10.5
    - type: mrr_at_10
      value: 17.278
    - type: mrr_at_100
      value: 18.418
    - type: mrr_at_1000
      value: 18.526
    - type: mrr_at_20
      value: 17.876
    - type: mrr_at_3
      value: 14.832999999999998
    - type: mrr_at_5
      value: 16.317999999999998
    - type: ndcg_at_1
      value: 10.5
    - type: ndcg_at_10
      value: 9.39
    - type: ndcg_at_100
      value: 14.362
    - type: ndcg_at_1000
      value: 19.524
    - type: ndcg_at_20
      value: 10.949
    - type: ndcg_at_3
      value: 8.794
    - type: ndcg_at_5
      value: 7.789
    - type: precision_at_1
      value: 10.5
    - type: precision_at_10
      value: 4.91
    - type: precision_at_100
      value: 1.221
    - type: precision_at_1000
      value: 0.247
    - type: precision_at_20
      value: 3.36
    - type: precision_at_3
      value: 8.233
    - type: precision_at_5
      value: 6.9
    - type: recall_at_1
      value: 2.1350000000000002
    - type: recall_at_10
      value: 9.955
    - type: recall_at_100
      value: 24.778
    - type: recall_at_1000
      value: 50.222
    - type: recall_at_20
      value: 13.63
    - type: recall_at_3
      value: 5.01
    - type: recall_at_5
      value: 6.995
  - task:
      type: STS
    dataset:
      type: mteb/sickr-sts
      name: MTEB SICK-R
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 78.43659263950201
    - type: cos_sim_spearman
      value: 74.68461406509039
    - type: euclidean_pearson
      value: 76.31168073146695
    - type: euclidean_spearman
      value: 75.13681406263804
    - type: manhattan_pearson
      value: 76.2960985430519
    - type: manhattan_spearman
      value: 75.03513932091352
  - task:
      type: STS
    dataset:
      type: mteb/sts12-sts
      name: MTEB STS12
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 55.096195345864295
    - type: cos_sim_spearman
      value: 54.34570729554049
    - type: euclidean_pearson
      value: 64.79488422312815
    - type: euclidean_spearman
      value: 61.19116930098903
    - type: manhattan_pearson
      value: 65.04388378143294
    - type: manhattan_spearman
      value: 61.33457037020176
  - task:
      type: STS
    dataset:
      type: mteb/sts13-sts
      name: MTEB STS13
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 71.40902040706975
    - type: cos_sim_spearman
      value: 74.24315395719762
    - type: euclidean_pearson
      value: 75.94675003130055
    - type: euclidean_spearman
      value: 76.18445285168187
    - type: manhattan_pearson
      value: 75.88786726620313
    - type: manhattan_spearman
      value: 76.1188105671321
  - task:
      type: STS
    dataset:
      type: mteb/sts14-sts
      name: MTEB STS14
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 71.9514442512574
    - type: cos_sim_spearman
      value: 69.99484176761607
    - type: euclidean_pearson
      value: 75.02706002860513
    - type: euclidean_spearman
      value: 72.9036480559019
    - type: manhattan_pearson
      value: 75.03815961673163
    - type: manhattan_spearman
      value: 72.92353672671821
  - task:
      type: STS
    dataset:
      type: mteb/sts15-sts
      name: MTEB STS15
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 72.80522195974591
    - type: cos_sim_spearman
      value: 75.73762657362906
    - type: euclidean_pearson
      value: 80.1521753666007
    - type: euclidean_spearman
      value: 80.25738481137047
    - type: manhattan_pearson
      value: 80.19317991797196
    - type: manhattan_spearman
      value: 80.31866668763018
  - task:
      type: STS
    dataset:
      type: mteb/sts16-sts
      name: MTEB STS16
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 69.45092072084951
    - type: cos_sim_spearman
      value: 73.6472761328024
    - type: euclidean_pearson
      value: 74.95031941602217
    - type: euclidean_spearman
      value: 75.37029502504294
    - type: manhattan_pearson
      value: 74.7846441654404
    - type: manhattan_spearman
      value: 75.19664481480419
  - 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: 82.66021611621103
    - type: cos_sim_spearman
      value: 84.81452353756737
    - type: euclidean_pearson
      value: 85.32338150846037
    - type: euclidean_spearman
      value: 85.46672916577448
    - type: manhattan_pearson
      value: 84.86427674633184
    - type: manhattan_spearman
      value: 85.098246631915
  - task:
      type: STS
    dataset:
      type: mteb/sts22-crosslingual-sts
      name: MTEB STS22 (en)
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 56.880105002604566
    - type: cos_sim_spearman
      value: 62.56487199261157
    - type: euclidean_pearson
      value: 57.49369653074593
    - type: euclidean_spearman
      value: 61.038143206328854
    - type: manhattan_pearson
      value: 57.85496348413732
    - type: manhattan_spearman
      value: 61.22736674852764
  - task:
      type: STS
    dataset:
      type: mteb/stsbenchmark-sts
      name: MTEB STSBenchmark
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 75.41209102908195
    - type: cos_sim_spearman
      value: 76.72196352753278
    - type: euclidean_pearson
      value: 79.97933288080695
    - type: euclidean_spearman
      value: 79.36350387100728
    - type: manhattan_pearson
      value: 79.89865614781017
    - type: manhattan_spearman
      value: 79.36099141428603
  - task:
      type: Reranking
    dataset:
      type: mteb/scidocs-reranking
      name: MTEB SciDocsRR
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 70.81824436527221
    - type: mrr
      value: 90.04096937920467
  - task:
      type: Retrieval
    dataset:
      type: mteb/scifact
      name: MTEB SciFact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 33.567
    - type: map_at_10
      value: 41.409
    - type: map_at_100
      value: 42.281
    - type: map_at_1000
      value: 42.358000000000004
    - type: map_at_20
      value: 41.916
    - type: map_at_3
      value: 38.784
    - type: map_at_5
      value: 40.355999999999995
    - type: mrr_at_1
      value: 35.667
    - type: mrr_at_10
      value: 43.189
    - type: mrr_at_100
      value: 43.885000000000005
    - type: mrr_at_1000
      value: 43.95
    - type: mrr_at_20
      value: 43.584
    - type: mrr_at_3
      value: 41.0
    - type: mrr_at_5
      value: 42.266999999999996
    - type: ndcg_at_1
      value: 35.667
    - type: ndcg_at_10
      value: 45.999
    - type: ndcg_at_100
      value: 50.153000000000006
    - type: ndcg_at_1000
      value: 52.161
    - type: ndcg_at_20
      value: 47.662
    - type: ndcg_at_3
      value: 41.178
    - type: ndcg_at_5
      value: 43.59
    - type: precision_at_1
      value: 35.667
    - type: precision_at_10
      value: 6.6000000000000005
    - type: precision_at_100
      value: 0.89
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_20
      value: 3.6830000000000003
    - type: precision_at_3
      value: 16.556
    - type: precision_at_5
      value: 11.466999999999999
    - type: recall_at_1
      value: 33.567
    - type: recall_at_10
      value: 58.599999999999994
    - type: recall_at_100
      value: 77.9
    - type: recall_at_1000
      value: 93.667
    - type: recall_at_20
      value: 64.878
    - type: recall_at_3
      value: 45.483000000000004
    - type: recall_at_5
      value: 51.4
  - task:
      type: PairClassification
    dataset:
      type: mteb/sprintduplicatequestions-pairclassification
      name: MTEB SprintDuplicateQuestions
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.6930693069307
    - type: cos_sim_ap
      value: 89.25594498972691
    - type: cos_sim_f1
      value: 83.84499245093104
    - type: cos_sim_precision
      value: 84.39716312056737
    - type: cos_sim_recall
      value: 83.3
    - type: dot_accuracy
      value: 99.48514851485149
    - type: dot_ap
      value: 75.92127370670867
    - type: dot_f1
      value: 71.16104868913857
    - type: dot_precision
      value: 76.52474108170311
    - type: dot_recall
      value: 66.5
    - type: euclidean_accuracy
      value: 99.6891089108911
    - type: euclidean_ap
      value: 89.2180446358921
    - type: euclidean_f1
      value: 83.57142857142857
    - type: euclidean_precision
      value: 85.3125
    - type: euclidean_recall
      value: 81.89999999999999
    - type: manhattan_accuracy
      value: 99.6980198019802
    - type: manhattan_ap
      value: 89.43047814044381
    - type: manhattan_f1
      value: 84.07445708376422
    - type: manhattan_precision
      value: 87.04496788008565
    - type: manhattan_recall
      value: 81.3
    - type: max_accuracy
      value: 99.6980198019802
    - type: max_ap
      value: 89.43047814044381
    - type: max_f1
      value: 84.07445708376422
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering
      name: MTEB StackExchangeClustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 32.83904946173562
    - type: v_measures
      value: [0.30110380679104903, 0.3953932981762184, 0.24615493206657874, 0.36457921033081425, 0.37818468307341996, 0.2458717382277342, 0.24597349476879382, 0.355495518705052, 0.32617546899939204, 0.3316784933295811, 0.4879686282712542, 0.4493952612804797, 0.4289659003483834, 0.25736076606300134, 0.31347948561233624, 0.32945691057021553, 0.2802921851023466, 0.30108517991402206, 0.2906340312531131, 0.3176973104574197, 0.32121506900305036, 0.27178906328240593, 0.2736797450244378, 0.3448789501821934, 0.3512532346006118, 0.30110380679104903, 0.3953932981762184, 0.24615493206657874, 0.36457921033081425, 0.37818468307341996, 0.2458717382277342, 0.24597349476879382, 0.355495518705052, 0.32617546899939204, 0.3316784933295811, 0.4879686282712542, 0.4493952612804797, 0.4289659003483834, 0.25736076606300134, 0.31347948561233624, 0.32945691057021553, 0.2802921851023466, 0.30108517991402206, 0.2906340312531131, 0.3176973104574197, 0.32121506900305036, 0.27178906328240593, 0.2736797450244378, 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  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering-p2p
      name: MTEB StackExchangeClusteringP2P
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 27.476810145753827
    - type: v_measures
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  - task:
      type: Reranking
    dataset:
      type: mteb/stackoverflowdupquestions-reranking
      name: MTEB StackOverflowDupQuestions
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.14055223869571
    - type: mrr
      value: 43.506533295136244
  - task:
      type: Summarization
    dataset:
      type: mteb/summeval
      name: MTEB SummEval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.24218821701958
    - type: cos_sim_spearman
      value: 29.907749825179124
    - type: dot_pearson
      value: 27.348198725124227
    - type: dot_spearman
      value: 25.950835375041038
  - task:
      type: Retrieval
    dataset:
      type: mteb/trec-covid
      name: MTEB TRECCOVID
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.1
    - type: map_at_10
      value: 0.505
    - type: map_at_100
      value: 2.207
    - type: map_at_1000
      value: 6.0600000000000005
    - type: map_at_20
      value: 0.814
    - type: map_at_3
      value: 0.218
    - type: map_at_5
      value: 0.329
    - type: mrr_at_1
      value: 44.0
    - type: mrr_at_10
      value: 54.763
    - type: mrr_at_100
      value: 55.345
    - type: mrr_at_1000
      value: 55.349000000000004
    - type: mrr_at_20
      value: 55.035000000000004
    - type: mrr_at_3
      value: 51.333
    - type: mrr_at_5
      value: 52.632999999999996
    - type: ndcg_at_1
      value: 39.0
    - type: ndcg_at_10
      value: 30.272
    - type: ndcg_at_100
      value: 21.906
    - type: ndcg_at_1000
      value: 22.439
    - type: ndcg_at_20
      value: 28.316000000000003
    - type: ndcg_at_3
      value: 35.235
    - type: ndcg_at_5
      value: 33.843
    - type: precision_at_1
      value: 44.0
    - type: precision_at_10
      value: 32.0
    - type: precision_at_100
      value: 22.5
    - type: precision_at_1000
      value: 10.9
    - type: precision_at_20
      value: 29.7
    - type: precision_at_3
      value: 38.0
    - type: precision_at_5
      value: 36.0
    - type: recall_at_1
      value: 0.1
    - type: recall_at_10
      value: 0.719
    - type: recall_at_100
      value: 4.7620000000000005
    - type: recall_at_1000
      value: 22.285
    - type: recall_at_20
      value: 1.277
    - type: recall_at_3
      value: 0.244
    - type: recall_at_5
      value: 0.40299999999999997
  - task:
      type: Retrieval
    dataset:
      type: mteb/touche2020
      name: MTEB Touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 0.865
    - type: map_at_10
      value: 2.962
    - type: map_at_100
      value: 5.713
    - type: map_at_1000
      value: 6.719
    - type: map_at_20
      value: 3.939
    - type: map_at_3
      value: 1.582
    - type: map_at_5
      value: 2.215
    - type: mrr_at_1
      value: 14.285999999999998
    - type: mrr_at_10
      value: 24.844
    - type: mrr_at_100
      value: 26.861
    - type: mrr_at_1000
      value: 26.904
    - type: mrr_at_20
      value: 26.375999999999998
    - type: mrr_at_3
      value: 20.068
    - type: mrr_at_5
      value: 22.619
    - type: ndcg_at_1
      value: 12.245000000000001
    - type: ndcg_at_10
      value: 10.508000000000001
    - type: ndcg_at_100
      value: 18.935
    - type: ndcg_at_1000
      value: 29.747
    - type: ndcg_at_20
      value: 11.701
    - type: ndcg_at_3
      value: 10.381
    - type: ndcg_at_5
      value: 11.339
    - type: precision_at_1
      value: 14.285999999999998
    - type: precision_at_10
      value: 10.612
    - type: precision_at_100
      value: 4.531000000000001
    - type: precision_at_1000
      value: 1.133
    - type: precision_at_20
      value: 8.98
    - type: precision_at_3
      value: 11.565
    - type: precision_at_5
      value: 12.653
    - type: recall_at_1
      value: 0.865
    - type: recall_at_10
      value: 6.493
    - type: recall_at_100
      value: 28.16
    - type: recall_at_1000
      value: 61.026
    - type: recall_at_20
      value: 11.726
    - type: recall_at_3
      value: 2.221
    - type: recall_at_5
      value: 3.849
  - task:
      type: Classification
    dataset:
      type: mteb/toxic_conversations_50k
      name: MTEB ToxicConversationsClassification
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 64.4091796875
    - type: ap
      value: 11.076947197887051
    - type: f1
      value: 49.07978901357373
  - task:
      type: Classification
    dataset:
      type: mteb/tweet_sentiment_extraction
      name: MTEB TweetSentimentExtractionClassification
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 59.663271080928126
    - type: f1
      value: 59.99492026885337
  - task:
      type: Clustering
    dataset:
      type: mteb/twentynewsgroups-clustering
      name: MTEB TwentyNewsgroupsClustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 26.09282097093625
    - type: v_measures
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  - task:
      type: PairClassification
    dataset:
      type: mteb/twittersemeval2015-pairclassification
      name: MTEB TwitterSemEval2015
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 84.88406747332658
    - type: cos_sim_ap
      value: 69.26105491403395
    - type: cos_sim_f1
      value: 65.52488910793494
    - type: cos_sim_precision
      value: 61.465557096625055
    - type: cos_sim_recall
      value: 70.15831134564644
    - type: dot_accuracy
      value: 82.16606067830959
    - type: dot_ap
      value: 61.09102948421686
    - type: dot_f1
      value: 57.59054713588492
    - type: dot_precision
      value: 56.106106106106104
    - type: dot_recall
      value: 59.155672823219
    - type: euclidean_accuracy
      value: 84.85426476724086
    - type: euclidean_ap
      value: 69.32917418684202
    - type: euclidean_f1
      value: 65.59770252482949
    - type: euclidean_precision
      value: 60.01751696956427
    - type: euclidean_recall
      value: 72.32189973614776
    - type: manhattan_accuracy
      value: 84.83638314358943
    - type: manhattan_ap
      value: 69.13012845791405
    - type: manhattan_f1
      value: 65.35336124107363
    - type: manhattan_precision
      value: 61.26500461680517
    - type: manhattan_recall
      value: 70.0263852242744
    - type: max_accuracy
      value: 84.88406747332658
    - type: max_ap
      value: 69.32917418684202
    - type: max_f1
      value: 65.59770252482949
  - task:
      type: PairClassification
    dataset:
      type: mteb/twitterurlcorpus-pairclassification
      name: MTEB TwitterURLCorpus
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.81387045445726
    - type: cos_sim_ap
      value: 83.19376576098023
    - type: cos_sim_f1
      value: 75.85641331494391
    - type: cos_sim_precision
      value: 73.52409856203484
    - type: cos_sim_recall
      value: 78.34154604250077
    - type: dot_accuracy
      value: 85.33007334963325
    - type: dot_ap
      value: 75.69925817222503
    - type: dot_f1
      value: 70.44983722994968
    - type: dot_precision
      value: 67.80119624038736
    - type: dot_recall
      value: 73.31382814906067
    - type: euclidean_accuracy
      value: 87.78864439011139
    - type: euclidean_ap
      value: 83.33289584854239
    - type: euclidean_f1
      value: 75.70217471433837
    - type: euclidean_precision
      value: 72.61349172677131
    - type: euclidean_recall
      value: 79.06529103788112
    - type: manhattan_accuracy
      value: 87.73819226141964
    - type: manhattan_ap
      value: 83.29254385989515
    - type: manhattan_f1
      value: 75.70975618644992
    - type: manhattan_precision
      value: 71.8773787281157
    - type: manhattan_recall
      value: 79.97382198952879
    - type: max_accuracy
      value: 87.81387045445726
    - type: max_ap
      value: 83.33289584854239
    - type: max_f1
      value: 75.85641331494391
---
# Venusaur

This is a distill of [Bulbasaur](https://huggingface.co/Mihaiii/Bulbasaur) using [qa-assistant](https://huggingface.co/datasets/Mihaiii/qa-assistant).

## 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>

## Usage (Sentence-Transformers) (same as [gte-tiny](https://huggingface.co/TaylorAI/gte-tiny))

Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:

```
pip install -U sentence-transformers
```

Then you can use the model like this:

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

model = SentenceTransformer('Mihaiii/Venusaur')
embeddings = model.encode(sentences)
print(embeddings)
```



## Usage (HuggingFace Transformers) (same as [gte-tiny](https://huggingface.co/TaylorAI/gte-tiny))
Without [sentence-transformers](https://www.SBERT.net), 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.

```python
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('Mihaiii/Venusaur')
model = AutoModel.from_pretrained('Mihaiii/Venusaur')

# 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)
```

### Limitation (same as [gte-small](https://huggingface.co/thenlper/gte-small))
This model exclusively caters to English texts, and any lengthy texts will be truncated to a maximum of 512 tokens.