---
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: Bulbasaur
  results:
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (en)
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.86567164179104
    - type: ap
      value: 34.08685244750869
    - type: f1
      value: 65.66014356237362
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_polarity
      name: MTEB AmazonPolarityClassification
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 78.78927499999999
    - type: ap
      value: 73.46960735629719
    - type: f1
      value: 78.6951990840684
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (en)
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 39.312
    - type: f1
      value: 38.94567141563064
  - task:
      type: Retrieval
    dataset:
      type: mteb/arguana
      name: MTEB ArguAna
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 22.191
    - type: map_at_10
      value: 36.504
    - type: map_at_100
      value: 37.676
    - type: map_at_1000
      value: 37.693
    - type: map_at_20
      value: 37.329
    - type: map_at_3
      value: 31.840000000000003
    - type: map_at_5
      value: 34.333000000000006
    - type: mrr_at_1
      value: 23.186
    - type: mrr_at_10
      value: 36.856
    - type: mrr_at_100
      value: 38.048
    - type: mrr_at_1000
      value: 38.065
    - type: mrr_at_20
      value: 37.701
    - type: mrr_at_3
      value: 32.16
    - type: mrr_at_5
      value: 34.756
    - type: ndcg_at_1
      value: 22.191
    - type: ndcg_at_10
      value: 44.798
    - type: ndcg_at_100
      value: 50.141999999999996
    - type: ndcg_at_1000
      value: 50.599000000000004
    - type: ndcg_at_20
      value: 47.778999999999996
    - type: ndcg_at_3
      value: 35.071999999999996
    - type: ndcg_at_5
      value: 39.574
    - type: precision_at_1
      value: 22.191
    - type: precision_at_10
      value: 7.148000000000001
    - type: precision_at_100
      value: 0.9570000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_20
      value: 4.1610000000000005
    - type: precision_at_3
      value: 14.817
    - type: precision_at_5
      value: 11.081000000000001
    - type: recall_at_1
      value: 22.191
    - type: recall_at_10
      value: 71.479
    - type: recall_at_100
      value: 95.661
    - type: recall_at_1000
      value: 99.289
    - type: recall_at_20
      value: 83.21499999999999
    - type: recall_at_3
      value: 44.452000000000005
    - type: recall_at_5
      value: 55.405
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-p2p
      name: MTEB ArxivClusteringP2P
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 40.283298409035076
    - 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: 31.058723747886102
    - 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: 57.489775602270086
    - type: mrr
      value: 71.4973838104032
  - task:
      type: STS
    dataset:
      type: mteb/biosses-sts
      name: MTEB BIOSSES
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 85.81314286759594
    - type: cos_sim_spearman
      value: 85.04832342591277
    - type: euclidean_pearson
      value: 84.20540608390993
    - type: euclidean_spearman
      value: 84.54831203281398
    - type: manhattan_pearson
      value: 84.11283044138868
    - type: manhattan_spearman
      value: 84.13384475757064
  - task:
      type: Classification
    dataset:
      type: mteb/banking77
      name: MTEB Banking77Classification
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 80.57792207792207
    - type: f1
      value: 80.510338047888
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-p2p
      name: MTEB BiorxivClusteringP2P
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 35.17908628951979
    - 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: 28.18471478622865
    - 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: 31.7776266029616
    - type: mrr
      value: 32.9057970138914
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack
      name: MTEB CQADupstackRetrieval
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 24.78675
    - type: map_at_10
      value: 33.18391666666666
    - type: map_at_100
      value: 34.34583333333333
    - type: map_at_1000
      value: 34.46825
    - type: map_at_20
      value: 33.819
    - type: map_at_3
      value: 30.636500000000005
    - type: map_at_5
      value: 32.02091666666667
    - type: mrr_at_1
      value: 29.478749999999998
    - type: mrr_at_10
      value: 37.385
    - type: mrr_at_100
      value: 38.23491666666667
    - type: mrr_at_1000
      value: 38.298833333333334
    - type: mrr_at_20
      value: 37.87508333333333
    - type: mrr_at_3
      value: 35.089666666666666
    - type: mrr_at_5
      value: 36.36816666666667
    - type: ndcg_at_1
      value: 29.478749999999998
    - type: ndcg_at_10
      value: 38.2035
    - type: ndcg_at_100
      value: 43.301083333333324
    - type: ndcg_at_1000
      value: 45.758666666666656
    - type: ndcg_at_20
      value: 40.15116666666667
    - type: ndcg_at_3
      value: 33.86033333333334
    - type: ndcg_at_5
      value: 35.81266666666666
    - type: precision_at_1
      value: 29.478749999999998
    - type: precision_at_10
      value: 6.642833333333334
    - type: precision_at_100
      value: 1.08425
    - type: precision_at_1000
      value: 0.14850000000000002
    - type: precision_at_20
      value: 3.948083333333334
    - type: precision_at_3
      value: 15.511
    - type: precision_at_5
      value: 10.929833333333333
    - type: recall_at_1
      value: 24.78675
    - type: recall_at_10
      value: 48.9305
    - type: recall_at_100
      value: 71.49416666666666
    - type: recall_at_1000
      value: 88.54375
    - type: recall_at_20
      value: 56.06475
    - type: recall_at_3
      value: 36.66891666666666
    - type: recall_at_5
      value: 41.790499999999994
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-android
      name: MTEB CQADupstackAndroidRetrieval
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 24.271
    - type: map_at_10
      value: 33.5
    - type: map_at_100
      value: 34.818
    - type: map_at_1000
      value: 34.967
    - type: map_at_20
      value: 34.238
    - type: map_at_3
      value: 30.488
    - type: map_at_5
      value: 32.303
    - type: mrr_at_1
      value: 30.615
    - type: mrr_at_10
      value: 39.076
    - type: mrr_at_100
      value: 40.022000000000006
    - type: mrr_at_1000
      value: 40.082
    - type: mrr_at_20
      value: 39.669
    - type: mrr_at_3
      value: 36.552
    - type: mrr_at_5
      value: 38.096999999999994
    - type: ndcg_at_1
      value: 30.615
    - type: ndcg_at_10
      value: 39.106
    - type: ndcg_at_100
      value: 44.519
    - type: ndcg_at_1000
      value: 47.274
    - type: ndcg_at_20
      value: 41.289
    - type: ndcg_at_3
      value: 34.55
    - type: ndcg_at_5
      value: 36.815999999999995
    - type: precision_at_1
      value: 30.615
    - type: precision_at_10
      value: 7.5249999999999995
    - type: precision_at_100
      value: 1.282
    - type: precision_at_1000
      value: 0.181
    - type: precision_at_20
      value: 4.549
    - type: precision_at_3
      value: 16.643
    - type: precision_at_5
      value: 12.275
    - type: recall_at_1
      value: 24.271
    - type: recall_at_10
      value: 49.714000000000006
    - type: recall_at_100
      value: 72.792
    - type: recall_at_1000
      value: 91.21000000000001
    - type: recall_at_20
      value: 57.799
    - type: recall_at_3
      value: 36.494
    - type: recall_at_5
      value: 42.764
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-english
      name: MTEB CQADupstackEnglishRetrieval
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 19.414
    - type: map_at_10
      value: 25.766
    - type: map_at_100
      value: 26.627000000000002
    - type: map_at_1000
      value: 26.749000000000002
    - type: map_at_20
      value: 26.201999999999998
    - type: map_at_3
      value: 23.738
    - type: map_at_5
      value: 24.829
    - type: mrr_at_1
      value: 24.013
    - type: mrr_at_10
      value: 30.208000000000002
    - type: mrr_at_100
      value: 30.903000000000002
    - type: mrr_at_1000
      value: 30.976
    - type: mrr_at_20
      value: 30.585
    - type: mrr_at_3
      value: 28.376
    - type: mrr_at_5
      value: 29.462
    - type: ndcg_at_1
      value: 24.013
    - type: ndcg_at_10
      value: 29.871
    - type: ndcg_at_100
      value: 33.867999999999995
    - type: ndcg_at_1000
      value: 36.565
    - type: ndcg_at_20
      value: 31.251
    - type: ndcg_at_3
      value: 26.579000000000004
    - type: ndcg_at_5
      value: 28.094
    - type: precision_at_1
      value: 24.013
    - type: precision_at_10
      value: 5.503
    - type: precision_at_100
      value: 0.936
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_20
      value: 3.2800000000000002
    - type: precision_at_3
      value: 12.590000000000002
    - type: precision_at_5
      value: 8.994
    - type: recall_at_1
      value: 19.414
    - type: recall_at_10
      value: 37.582
    - type: recall_at_100
      value: 55.181000000000004
    - type: recall_at_1000
      value: 73.342
    - type: recall_at_20
      value: 42.596000000000004
    - type: recall_at_3
      value: 28.102
    - type: recall_at_5
      value: 32.267
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-gaming
      name: MTEB CQADupstackGamingRetrieval
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 31.5
    - type: map_at_10
      value: 42.179
    - type: map_at_100
      value: 43.231
    - type: map_at_1000
      value: 43.302
    - type: map_at_20
      value: 42.786
    - type: map_at_3
      value: 39.17
    - type: map_at_5
      value: 40.854
    - type: mrr_at_1
      value: 36.113
    - type: mrr_at_10
      value: 45.378
    - type: mrr_at_100
      value: 46.153
    - type: mrr_at_1000
      value: 46.194
    - type: mrr_at_20
      value: 45.831
    - type: mrr_at_3
      value: 42.947
    - type: mrr_at_5
      value: 44.339
    - type: ndcg_at_1
      value: 36.113
    - type: ndcg_at_10
      value: 47.616
    - type: ndcg_at_100
      value: 52.125
    - type: ndcg_at_1000
      value: 53.717999999999996
    - type: ndcg_at_20
      value: 49.495
    - type: ndcg_at_3
      value: 42.354
    - type: ndcg_at_5
      value: 44.885999999999996
    - type: precision_at_1
      value: 36.113
    - type: precision_at_10
      value: 7.799
    - type: precision_at_100
      value: 1.093
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_20
      value: 4.4670000000000005
    - type: precision_at_3
      value: 19.017999999999997
    - type: precision_at_5
      value: 13.254
    - type: recall_at_1
      value: 31.5
    - type: recall_at_10
      value: 60.67
    - type: recall_at_100
      value: 80.484
    - type: recall_at_1000
      value: 92.04599999999999
    - type: recall_at_20
      value: 67.644
    - type: recall_at_3
      value: 46.671
    - type: recall_at_5
      value: 52.723
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-gis
      name: MTEB CQADupstackGisRetrieval
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 17.339
    - type: map_at_10
      value: 23.014000000000003
    - type: map_at_100
      value: 23.918
    - type: map_at_1000
      value: 24.027
    - type: map_at_20
      value: 23.507
    - type: map_at_3
      value: 21.176000000000002
    - type: map_at_5
      value: 22.126
    - type: mrr_at_1
      value: 18.531
    - type: mrr_at_10
      value: 24.356
    - type: mrr_at_100
      value: 25.247000000000003
    - type: mrr_at_1000
      value: 25.338
    - type: mrr_at_20
      value: 24.858
    - type: mrr_at_3
      value: 22.542
    - type: mrr_at_5
      value: 23.508000000000003
    - type: ndcg_at_1
      value: 18.531
    - type: ndcg_at_10
      value: 26.51
    - type: ndcg_at_100
      value: 31.367
    - type: ndcg_at_1000
      value: 34.38
    - type: ndcg_at_20
      value: 28.328999999999997
    - type: ndcg_at_3
      value: 22.861
    - type: ndcg_at_5
      value: 24.456
    - type: precision_at_1
      value: 18.531
    - type: precision_at_10
      value: 4.147
    - type: precision_at_100
      value: 0.695
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_20
      value: 2.492
    - type: precision_at_3
      value: 9.793000000000001
    - type: precision_at_5
      value: 6.825
    - type: recall_at_1
      value: 17.339
    - type: recall_at_10
      value: 36.010999999999996
    - type: recall_at_100
      value: 59.040000000000006
    - type: recall_at_1000
      value: 82.282
    - type: recall_at_20
      value: 43.04
    - type: recall_at_3
      value: 25.904
    - type: recall_at_5
      value: 29.837000000000003
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-mathematica
      name: MTEB CQADupstackMathematicaRetrieval
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 9.251
    - type: map_at_10
      value: 14.848
    - type: map_at_100
      value: 15.940999999999999
    - type: map_at_1000
      value: 16.055
    - type: map_at_20
      value: 15.423
    - type: map_at_3
      value: 12.556999999999999
    - type: map_at_5
      value: 13.649000000000001
    - type: mrr_at_1
      value: 12.313
    - type: mrr_at_10
      value: 18.528
    - type: mrr_at_100
      value: 19.522000000000002
    - type: mrr_at_1000
      value: 19.601
    - type: mrr_at_20
      value: 19.107
    - type: mrr_at_3
      value: 16.231
    - type: mrr_at_5
      value: 17.294999999999998
    - type: ndcg_at_1
      value: 12.313
    - type: ndcg_at_10
      value: 19.303
    - type: ndcg_at_100
      value: 24.728
    - type: ndcg_at_1000
      value: 27.823999999999998
    - type: ndcg_at_20
      value: 21.318
    - type: ndcg_at_3
      value: 14.848
    - type: ndcg_at_5
      value: 16.509
    - type: precision_at_1
      value: 12.313
    - type: precision_at_10
      value: 4.03
    - type: precision_at_100
      value: 0.777
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_20
      value: 2.562
    - type: precision_at_3
      value: 7.546
    - type: precision_at_5
      value: 5.672
    - type: recall_at_1
      value: 9.251
    - type: recall_at_10
      value: 29.677999999999997
    - type: recall_at_100
      value: 53.586
    - type: recall_at_1000
      value: 76.181
    - type: recall_at_20
      value: 36.963
    - type: recall_at_3
      value: 17.072000000000003
    - type: recall_at_5
      value: 21.481
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-physics
      name: MTEB CQADupstackPhysicsRetrieval
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 21.135
    - type: map_at_10
      value: 29.431
    - type: map_at_100
      value: 30.662
    - type: map_at_1000
      value: 30.792
    - type: map_at_20
      value: 30.086000000000002
    - type: map_at_3
      value: 26.593
    - type: map_at_5
      value: 28.011999999999997
    - type: mrr_at_1
      value: 26.564
    - type: mrr_at_10
      value: 34.735
    - type: mrr_at_100
      value: 35.65
    - type: mrr_at_1000
      value: 35.711999999999996
    - type: mrr_at_20
      value: 35.286
    - type: mrr_at_3
      value: 32.002
    - type: mrr_at_5
      value: 33.527
    - type: ndcg_at_1
      value: 26.564
    - type: ndcg_at_10
      value: 35.108
    - type: ndcg_at_100
      value: 40.601
    - type: ndcg_at_1000
      value: 43.329
    - type: ndcg_at_20
      value: 37.192
    - type: ndcg_at_3
      value: 29.961
    - type: ndcg_at_5
      value: 32.131
    - type: precision_at_1
      value: 26.564
    - type: precision_at_10
      value: 6.564
    - type: precision_at_100
      value: 1.105
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_20
      value: 3.941
    - type: precision_at_3
      value: 14.212
    - type: precision_at_5
      value: 10.337
    - type: recall_at_1
      value: 21.135
    - type: recall_at_10
      value: 47.242
    - type: recall_at_100
      value: 70.645
    - type: recall_at_1000
      value: 89.403
    - type: recall_at_20
      value: 54.663
    - type: recall_at_3
      value: 32.647
    - type: recall_at_5
      value: 38.122
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-programmers
      name: MTEB CQADupstackProgrammersRetrieval
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 16.86
    - type: map_at_10
      value: 23.477999999999998
    - type: map_at_100
      value: 24.68
    - type: map_at_1000
      value: 24.826999999999998
    - type: map_at_20
      value: 24.122
    - type: map_at_3
      value: 21.288999999999998
    - type: map_at_5
      value: 22.453
    - type: mrr_at_1
      value: 20.776
    - type: mrr_at_10
      value: 28.029
    - type: mrr_at_100
      value: 28.951
    - type: mrr_at_1000
      value: 29.038000000000004
    - type: mrr_at_20
      value: 28.546
    - type: mrr_at_3
      value: 25.818
    - type: mrr_at_5
      value: 26.994
    - type: ndcg_at_1
      value: 20.776
    - type: ndcg_at_10
      value: 28.152
    - type: ndcg_at_100
      value: 33.82
    - type: ndcg_at_1000
      value: 37.039
    - type: ndcg_at_20
      value: 30.238
    - type: ndcg_at_3
      value: 24.197
    - type: ndcg_at_5
      value: 25.861
    - type: precision_at_1
      value: 20.776
    - type: precision_at_10
      value: 5.297000000000001
    - type: precision_at_100
      value: 0.96
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_20
      value: 3.276
    - type: precision_at_3
      value: 11.606
    - type: precision_at_5
      value: 8.356
    - type: recall_at_1
      value: 16.86
    - type: recall_at_10
      value: 37.782
    - type: recall_at_100
      value: 62.67
    - type: recall_at_1000
      value: 85.03
    - type: recall_at_20
      value: 45.2
    - type: recall_at_3
      value: 26.506999999999998
    - type: recall_at_5
      value: 31.113000000000003
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-stats
      name: MTEB CQADupstackStatsRetrieval
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 15.234
    - type: map_at_10
      value: 20.939
    - type: map_at_100
      value: 21.704
    - type: map_at_1000
      value: 21.804000000000002
    - type: map_at_20
      value: 21.311
    - type: map_at_3
      value: 18.972
    - type: map_at_5
      value: 19.929
    - type: mrr_at_1
      value: 17.485
    - type: mrr_at_10
      value: 23.267
    - type: mrr_at_100
      value: 23.967
    - type: mrr_at_1000
      value: 24.054000000000002
    - type: mrr_at_20
      value: 23.604
    - type: mrr_at_3
      value: 21.345
    - type: mrr_at_5
      value: 22.303
    - type: ndcg_at_1
      value: 17.485
    - type: ndcg_at_10
      value: 24.744
    - type: ndcg_at_100
      value: 28.801
    - type: ndcg_at_1000
      value: 31.619999999999997
    - type: ndcg_at_20
      value: 26.046000000000003
    - type: ndcg_at_3
      value: 20.862
    - type: ndcg_at_5
      value: 22.459
    - type: precision_at_1
      value: 17.485
    - type: precision_at_10
      value: 4.109999999999999
    - type: precision_at_100
      value: 0.676
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_20
      value: 2.3619999999999997
    - type: precision_at_3
      value: 9.254
    - type: precision_at_5
      value: 6.503
    - type: recall_at_1
      value: 15.234
    - type: recall_at_10
      value: 34.48
    - type: recall_at_100
      value: 53.225
    - type: recall_at_1000
      value: 74.64699999999999
    - type: recall_at_20
      value: 39.421
    - type: recall_at_3
      value: 23.554
    - type: recall_at_5
      value: 27.662
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-tex
      name: MTEB CQADupstackTexRetrieval
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 9.564
    - type: map_at_10
      value: 13.869000000000002
    - type: map_at_100
      value: 14.728
    - type: map_at_1000
      value: 14.853
    - type: map_at_20
      value: 14.32
    - type: map_at_3
      value: 12.307
    - type: map_at_5
      value: 13.177
    - type: mrr_at_1
      value: 11.941
    - type: mrr_at_10
      value: 16.777
    - type: mrr_at_100
      value: 17.571
    - type: mrr_at_1000
      value: 17.663999999999998
    - type: mrr_at_20
      value: 17.203
    - type: mrr_at_3
      value: 15.067
    - type: mrr_at_5
      value: 16.003999999999998
    - type: ndcg_at_1
      value: 11.941
    - type: ndcg_at_10
      value: 17.111
    - type: ndcg_at_100
      value: 21.438
    - type: ndcg_at_1000
      value: 24.756
    - type: ndcg_at_20
      value: 18.616
    - type: ndcg_at_3
      value: 14.143
    - type: ndcg_at_5
      value: 15.501000000000001
    - type: precision_at_1
      value: 11.941
    - type: precision_at_10
      value: 3.304
    - type: precision_at_100
      value: 0.658
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_20
      value: 2.077
    - type: precision_at_3
      value: 6.882000000000001
    - type: precision_at_5
      value: 5.12
    - type: recall_at_1
      value: 9.564
    - type: recall_at_10
      value: 24.068
    - type: recall_at_100
      value: 43.759
    - type: recall_at_1000
      value: 68.101
    - type: recall_at_20
      value: 29.657
    - type: recall_at_3
      value: 15.68
    - type: recall_at_5
      value: 19.238
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-unix
      name: MTEB CQADupstackUnixRetrieval
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 16.171
    - type: map_at_10
      value: 22.142
    - type: map_at_100
      value: 23.261000000000003
    - type: map_at_1000
      value: 23.371
    - type: map_at_20
      value: 22.766000000000002
    - type: map_at_3
      value: 20.251
    - type: map_at_5
      value: 21.349
    - type: mrr_at_1
      value: 19.403000000000002
    - type: mrr_at_10
      value: 25.619999999999997
    - type: mrr_at_100
      value: 26.659
    - type: mrr_at_1000
      value: 26.735
    - type: mrr_at_20
      value: 26.212000000000003
    - type: mrr_at_3
      value: 23.694000000000003
    - type: mrr_at_5
      value: 24.781
    - type: ndcg_at_1
      value: 19.403000000000002
    - type: ndcg_at_10
      value: 26.104
    - type: ndcg_at_100
      value: 31.724000000000004
    - type: ndcg_at_1000
      value: 34.581
    - type: ndcg_at_20
      value: 28.231
    - type: ndcg_at_3
      value: 22.464000000000002
    - type: ndcg_at_5
      value: 24.233
    - type: precision_at_1
      value: 19.403000000000002
    - type: precision_at_10
      value: 4.422000000000001
    - type: precision_at_100
      value: 0.8170000000000001
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_20
      value: 2.78
    - type: precision_at_3
      value: 10.168000000000001
    - type: precision_at_5
      value: 7.295
    - type: recall_at_1
      value: 16.171
    - type: recall_at_10
      value: 34.899
    - type: recall_at_100
      value: 60.197
    - type: recall_at_1000
      value: 80.798
    - type: recall_at_20
      value: 42.591
    - type: recall_at_3
      value: 25.024
    - type: recall_at_5
      value: 29.42
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-webmasters
      name: MTEB CQADupstackWebmastersRetrieval
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 16.412
    - type: map_at_10
      value: 23.138
    - type: map_at_100
      value: 24.46
    - type: map_at_1000
      value: 24.668
    - type: map_at_20
      value: 23.791
    - type: map_at_3
      value: 20.965
    - type: map_at_5
      value: 22.005
    - type: mrr_at_1
      value: 20.949
    - type: mrr_at_10
      value: 27.46
    - type: mrr_at_100
      value: 28.546
    - type: mrr_at_1000
      value: 28.619
    - type: mrr_at_20
      value: 28.038999999999998
    - type: mrr_at_3
      value: 25.461
    - type: mrr_at_5
      value: 26.528000000000002
    - type: ndcg_at_1
      value: 20.949
    - type: ndcg_at_10
      value: 27.919
    - type: ndcg_at_100
      value: 33.886
    - type: ndcg_at_1000
      value: 37.284
    - type: ndcg_at_20
      value: 29.876
    - type: ndcg_at_3
      value: 24.246000000000002
    - type: ndcg_at_5
      value: 25.607999999999997
    - type: precision_at_1
      value: 20.949
    - type: precision_at_10
      value: 5.534
    - type: precision_at_100
      value: 1.2409999999999999
    - type: precision_at_1000
      value: 0.22
    - type: precision_at_20
      value: 3.5180000000000002
    - type: precision_at_3
      value: 11.726
    - type: precision_at_5
      value: 8.498
    - type: recall_at_1
      value: 16.412
    - type: recall_at_10
      value: 37.012
    - type: recall_at_100
      value: 64.702
    - type: recall_at_1000
      value: 87.442
    - type: recall_at_20
      value: 44.797
    - type: recall_at_3
      value: 25.872
    - type: recall_at_5
      value: 29.732999999999997
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-wordpress
      name: MTEB CQADupstackWordpressRetrieval
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.158
    - type: map_at_10
      value: 15.809999999999999
    - type: map_at_100
      value: 16.821
    - type: map_at_1000
      value: 16.925
    - type: map_at_20
      value: 16.403000000000002
    - type: map_at_3
      value: 13.791999999999998
    - type: map_at_5
      value: 14.817
    - type: mrr_at_1
      value: 12.384
    - type: mrr_at_10
      value: 17.291999999999998
    - type: mrr_at_100
      value: 18.271
    - type: mrr_at_1000
      value: 18.360000000000003
    - type: mrr_at_20
      value: 17.854999999999997
    - type: mrr_at_3
      value: 15.096000000000002
    - type: mrr_at_5
      value: 16.214000000000002
    - type: ndcg_at_1
      value: 12.384
    - type: ndcg_at_10
      value: 19.250999999999998
    - type: ndcg_at_100
      value: 24.524
    - type: ndcg_at_1000
      value: 27.624
    - type: ndcg_at_20
      value: 21.387999999999998
    - type: ndcg_at_3
      value: 14.995
    - type: ndcg_at_5
      value: 16.861
    - type: precision_at_1
      value: 12.384
    - type: precision_at_10
      value: 3.29
    - type: precision_at_100
      value: 0.632
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_20
      value: 2.1260000000000003
    - type: precision_at_3
      value: 6.47
    - type: precision_at_5
      value: 4.917
    - type: recall_at_1
      value: 11.158
    - type: recall_at_10
      value: 28.737000000000002
    - type: recall_at_100
      value: 53.400000000000006
    - type: recall_at_1000
      value: 77.509
    - type: recall_at_20
      value: 36.969
    - type: recall_at_3
      value: 17.197000000000003
    - type: recall_at_5
      value: 21.701
  - task:
      type: Retrieval
    dataset:
      type: mteb/climate-fever
      name: MTEB ClimateFEVER
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 7.172000000000001
    - type: map_at_10
      value: 11.935
    - type: map_at_100
      value: 13.305
    - type: map_at_1000
      value: 13.517000000000001
    - type: map_at_20
      value: 12.589
    - type: map_at_3
      value: 9.9
    - type: map_at_5
      value: 10.839
    - type: mrr_at_1
      value: 15.895999999999999
    - type: mrr_at_10
      value: 24.215999999999998
    - type: mrr_at_100
      value: 25.418000000000003
    - type: mrr_at_1000
      value: 25.480000000000004
    - type: mrr_at_20
      value: 24.934
    - type: mrr_at_3
      value: 21.064
    - type: mrr_at_5
      value: 22.676
    - type: ndcg_at_1
      value: 15.895999999999999
    - type: ndcg_at_10
      value: 17.69
    - type: ndcg_at_100
      value: 24.232
    - type: ndcg_at_1000
      value: 28.405
    - type: ndcg_at_20
      value: 19.933999999999997
    - type: ndcg_at_3
      value: 13.761000000000001
    - type: ndcg_at_5
      value: 14.963000000000001
    - type: precision_at_1
      value: 15.895999999999999
    - type: precision_at_10
      value: 5.733
    - type: precision_at_100
      value: 1.266
    - type: precision_at_1000
      value: 0.203
    - type: precision_at_20
      value: 3.798
    - type: precision_at_3
      value: 10.076
    - type: precision_at_5
      value: 7.9479999999999995
    - type: recall_at_1
      value: 7.172000000000001
    - type: recall_at_10
      value: 22.149
    - type: recall_at_100
      value: 45.491
    - type: recall_at_1000
      value: 69.34
    - type: recall_at_20
      value: 28.634999999999998
    - type: recall_at_3
      value: 12.701
    - type: recall_at_5
      value: 15.952
  - task:
      type: Retrieval
    dataset:
      type: mteb/dbpedia
      name: MTEB DBPedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 7.101
    - type: map_at_10
      value: 15.125
    - type: map_at_100
      value: 20.026
    - type: map_at_1000
      value: 21.194
    - type: map_at_20
      value: 17.008000000000003
    - type: map_at_3
      value: 10.915999999999999
    - type: map_at_5
      value: 12.705
    - type: mrr_at_1
      value: 53.5
    - type: mrr_at_10
      value: 63.475
    - type: mrr_at_100
      value: 63.998
    - type: mrr_at_1000
      value: 64.019
    - type: mrr_at_20
      value: 63.800999999999995
    - type: mrr_at_3
      value: 62.041999999999994
    - type: mrr_at_5
      value: 62.678999999999995
    - type: ndcg_at_1
      value: 41.875
    - type: ndcg_at_10
      value: 32.967
    - type: ndcg_at_100
      value: 35.557
    - type: ndcg_at_1000
      value: 42.537000000000006
    - type: ndcg_at_20
      value: 31.930999999999997
    - type: ndcg_at_3
      value: 36.67
    - type: ndcg_at_5
      value: 34.474
    - type: precision_at_1
      value: 53.5
    - type: precision_at_10
      value: 27.0
    - type: precision_at_100
      value: 7.872999999999999
    - type: precision_at_1000
      value: 1.637
    - type: precision_at_20
      value: 19.487
    - type: precision_at_3
      value: 41.583
    - type: precision_at_5
      value: 34.699999999999996
    - type: recall_at_1
      value: 7.101
    - type: recall_at_10
      value: 20.408
    - type: recall_at_100
      value: 40.286
    - type: recall_at_1000
      value: 63.49399999999999
    - type: recall_at_20
      value: 25.478
    - type: recall_at_3
      value: 12.278
    - type: recall_at_5
      value: 15.392
  - task:
      type: Classification
    dataset:
      type: mteb/emotion
      name: MTEB EmotionClassification
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 44.79
    - type: f1
      value: 39.606429663804356
  - task:
      type: Retrieval
    dataset:
      type: mteb/fever
      name: MTEB FEVER
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 27.898
    - type: map_at_10
      value: 39.315
    - type: map_at_100
      value: 40.219
    - type: map_at_1000
      value: 40.268
    - type: map_at_20
      value: 39.893
    - type: map_at_3
      value: 35.993
    - type: map_at_5
      value: 38.016
    - type: mrr_at_1
      value: 30.003
    - type: mrr_at_10
      value: 41.85
    - type: mrr_at_100
      value: 42.722
    - type: mrr_at_1000
      value: 42.760999999999996
    - type: mrr_at_20
      value: 42.419000000000004
    - type: mrr_at_3
      value: 38.451
    - type: mrr_at_5
      value: 40.547
    - type: ndcg_at_1
      value: 30.003
    - type: ndcg_at_10
      value: 45.907
    - type: ndcg_at_100
      value: 50.198
    - type: ndcg_at_1000
      value: 51.405
    - type: ndcg_at_20
      value: 47.97
    - type: ndcg_at_3
      value: 39.234
    - type: ndcg_at_5
      value: 42.844
    - type: precision_at_1
      value: 30.003
    - type: precision_at_10
      value: 7.0040000000000004
    - type: precision_at_100
      value: 0.9259999999999999
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_20
      value: 3.9510000000000005
    - type: precision_at_3
      value: 16.647000000000002
    - type: precision_at_5
      value: 11.914
    - type: recall_at_1
      value: 27.898
    - type: recall_at_10
      value: 64.003
    - type: recall_at_100
      value: 83.42500000000001
    - type: recall_at_1000
      value: 92.448
    - type: recall_at_20
      value: 71.93
    - type: recall_at_3
      value: 46.12
    - type: recall_at_5
      value: 54.812000000000005
  - task:
      type: Retrieval
    dataset:
      type: mteb/fiqa
      name: MTEB FiQA2018
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 10.282
    - type: map_at_10
      value: 16.141
    - type: map_at_100
      value: 17.634
    - type: map_at_1000
      value: 17.836
    - type: map_at_20
      value: 16.99
    - type: map_at_3
      value: 13.947000000000001
    - type: map_at_5
      value: 15.149000000000001
    - type: mrr_at_1
      value: 20.679
    - type: mrr_at_10
      value: 26.966
    - type: mrr_at_100
      value: 28.108
    - type: mrr_at_1000
      value: 28.183999999999997
    - type: mrr_at_20
      value: 27.672
    - type: mrr_at_3
      value: 24.743000000000002
    - type: mrr_at_5
      value: 25.916
    - type: ndcg_at_1
      value: 20.679
    - type: ndcg_at_10
      value: 21.291
    - type: ndcg_at_100
      value: 27.884999999999998
    - type: ndcg_at_1000
      value: 32.122
    - type: ndcg_at_20
      value: 23.898
    - type: ndcg_at_3
      value: 18.553
    - type: ndcg_at_5
      value: 19.468
    - type: precision_at_1
      value: 20.679
    - type: precision_at_10
      value: 6.019
    - type: precision_at_100
      value: 1.252
    - type: precision_at_1000
      value: 0.201
    - type: precision_at_20
      value: 4.0120000000000005
    - type: precision_at_3
      value: 12.243
    - type: precision_at_5
      value: 9.321
    - type: recall_at_1
      value: 10.282
    - type: recall_at_10
      value: 25.901999999999997
    - type: recall_at_100
      value: 50.956999999999994
    - type: recall_at_1000
      value: 76.935
    - type: recall_at_20
      value: 34.104
    - type: recall_at_3
      value: 16.973
    - type: recall_at_5
      value: 20.549999999999997
  - task:
      type: Retrieval
    dataset:
      type: mteb/hotpotqa
      name: MTEB HotpotQA
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 30.567
    - type: map_at_10
      value: 42.314
    - type: map_at_100
      value: 43.205
    - type: map_at_1000
      value: 43.288
    - type: map_at_20
      value: 42.812
    - type: map_at_3
      value: 39.695
    - type: map_at_5
      value: 41.214
    - type: mrr_at_1
      value: 61.134
    - type: mrr_at_10
      value: 68.57600000000001
    - type: mrr_at_100
      value: 68.95599999999999
    - type: mrr_at_1000
      value: 68.97999999999999
    - type: mrr_at_20
      value: 68.818
    - type: mrr_at_3
      value: 66.99300000000001
    - type: mrr_at_5
      value: 67.919
    - type: ndcg_at_1
      value: 61.134
    - type: ndcg_at_10
      value: 51.518
    - type: ndcg_at_100
      value: 55.022000000000006
    - type: ndcg_at_1000
      value: 56.81699999999999
    - type: ndcg_at_20
      value: 52.893
    - type: ndcg_at_3
      value: 47.216
    - type: ndcg_at_5
      value: 49.413000000000004
    - type: precision_at_1
      value: 61.134
    - type: precision_at_10
      value: 10.729
    - type: precision_at_100
      value: 1.351
    - type: precision_at_1000
      value: 0.159
    - type: precision_at_20
      value: 5.8069999999999995
    - type: precision_at_3
      value: 29.336000000000002
    - type: precision_at_5
      value: 19.346
    - type: recall_at_1
      value: 30.567
    - type: recall_at_10
      value: 53.64600000000001
    - type: recall_at_100
      value: 67.562
    - type: recall_at_1000
      value: 79.521
    - type: recall_at_20
      value: 58.069
    - type: recall_at_3
      value: 44.004
    - type: recall_at_5
      value: 48.366
  - task:
      type: Classification
    dataset:
      type: mteb/imdb
      name: MTEB ImdbClassification
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 71.5272
    - type: ap
      value: 65.49215755861609
    - type: f1
      value: 71.4156268611186
  - task:
      type: Retrieval
    dataset:
      type: mteb/msmarco
      name: MTEB MSMARCO
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 14.574000000000002
    - type: map_at_10
      value: 23.966
    - type: map_at_100
      value: 25.19
    - type: map_at_1000
      value: 25.266
    - type: map_at_20
      value: 24.668
    - type: map_at_3
      value: 20.815
    - type: map_at_5
      value: 22.576
    - type: mrr_at_1
      value: 14.957
    - type: mrr_at_10
      value: 24.413999999999998
    - type: mrr_at_100
      value: 25.616
    - type: mrr_at_1000
      value: 25.685999999999996
    - type: mrr_at_20
      value: 25.11
    - type: mrr_at_3
      value: 21.304000000000002
    - type: mrr_at_5
      value: 23.047
    - type: ndcg_at_1
      value: 14.957
    - type: ndcg_at_10
      value: 29.49
    - type: ndcg_at_100
      value: 35.734
    - type: ndcg_at_1000
      value: 37.785000000000004
    - type: ndcg_at_20
      value: 32.004
    - type: ndcg_at_3
      value: 23.006999999999998
    - type: ndcg_at_5
      value: 26.154
    - type: precision_at_1
      value: 14.957
    - type: precision_at_10
      value: 4.8500000000000005
    - type: precision_at_100
      value: 0.8009999999999999
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_20
      value: 2.943
    - type: precision_at_3
      value: 9.962
    - type: precision_at_5
      value: 7.556
    - type: recall_at_1
      value: 14.574000000000002
    - type: recall_at_10
      value: 46.655
    - type: recall_at_100
      value: 76.26899999999999
    - type: recall_at_1000
      value: 92.303
    - type: recall_at_20
      value: 56.424
    - type: recall_at_3
      value: 28.874
    - type: recall_at_5
      value: 36.441
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (en)
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 90.78887368901049
    - type: f1
      value: 90.30465646125157
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (en)
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 68.71865025079799
    - type: f1
      value: 50.7484789245504
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (en)
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 68.8399462004035
    - type: f1
      value: 66.66574227334513
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (en)
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 73.74915938130464
    - type: f1
      value: 73.61179700374726
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-p2p
      name: MTEB MedrxivClusteringP2P
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 30.3983428793953
    - type: v_measures
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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: 28.78917156239751
    - type: v_measures
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  - task:
      type: Retrieval
    dataset:
      type: mteb/nfcorpus
      name: MTEB NFCorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.726
    - type: map_at_10
      value: 8.604000000000001
    - type: map_at_100
      value: 10.95
    - type: map_at_1000
      value: 12.256
    - type: map_at_20
      value: 9.573
    - type: map_at_3
      value: 6.264
    - type: map_at_5
      value: 7.343
    - type: mrr_at_1
      value: 37.771
    - type: mrr_at_10
      value: 46.476
    - type: mrr_at_100
      value: 47.164
    - type: mrr_at_1000
      value: 47.213
    - type: mrr_at_20
      value: 46.792
    - type: mrr_at_3
      value: 44.272
    - type: mrr_at_5
      value: 45.728
    - type: ndcg_at_1
      value: 35.604
    - type: ndcg_at_10
      value: 26.778000000000002
    - type: ndcg_at_100
      value: 24.313000000000002
    - type: ndcg_at_1000
      value: 33.601
    - type: ndcg_at_20
      value: 24.788
    - type: ndcg_at_3
      value: 30.991999999999997
    - type: ndcg_at_5
      value: 28.9
    - type: precision_at_1
      value: 37.152
    - type: precision_at_10
      value: 19.875999999999998
    - type: precision_at_100
      value: 6.449000000000001
    - type: precision_at_1000
      value: 1.934
    - type: precision_at_20
      value: 14.721
    - type: precision_at_3
      value: 28.999000000000002
    - type: precision_at_5
      value: 24.582
    - type: recall_at_1
      value: 3.726
    - type: recall_at_10
      value: 12.529000000000002
    - type: recall_at_100
      value: 25.726
    - type: recall_at_1000
      value: 58.336
    - type: recall_at_20
      value: 16.028000000000002
    - type: recall_at_3
      value: 7.176
    - type: recall_at_5
      value: 9.511
  - task:
      type: Retrieval
    dataset:
      type: mteb/nq
      name: MTEB NQ
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 15.110000000000001
    - type: map_at_10
      value: 25.983
    - type: map_at_100
      value: 27.332
    - type: map_at_1000
      value: 27.406999999999996
    - type: map_at_20
      value: 26.804
    - type: map_at_3
      value: 22.182
    - type: map_at_5
      value: 24.247
    - type: mrr_at_1
      value: 17.236
    - type: mrr_at_10
      value: 28.177999999999997
    - type: mrr_at_100
      value: 29.346
    - type: mrr_at_1000
      value: 29.401
    - type: mrr_at_20
      value: 28.906
    - type: mrr_at_3
      value: 24.593999999999998
    - type: mrr_at_5
      value: 26.540999999999997
    - type: ndcg_at_1
      value: 17.207
    - type: ndcg_at_10
      value: 32.603
    - type: ndcg_at_100
      value: 38.883
    - type: ndcg_at_1000
      value: 40.708
    - type: ndcg_at_20
      value: 35.397
    - type: ndcg_at_3
      value: 25.002999999999997
    - type: ndcg_at_5
      value: 28.572999999999997
    - type: precision_at_1
      value: 17.207
    - type: precision_at_10
      value: 5.985
    - type: precision_at_100
      value: 0.951
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_20
      value: 3.656
    - type: precision_at_3
      value: 11.848
    - type: precision_at_5
      value: 9.125
    - type: recall_at_1
      value: 15.110000000000001
    - type: recall_at_10
      value: 51.00900000000001
    - type: recall_at_100
      value: 79.193
    - type: recall_at_1000
      value: 92.828
    - type: recall_at_20
      value: 61.402
    - type: recall_at_3
      value: 30.791
    - type: recall_at_5
      value: 39.091
  - task:
      type: Retrieval
    dataset:
      type: mteb/quora
      name: MTEB QuoraRetrieval
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 67.465
    - type: map_at_10
      value: 81.035
    - type: map_at_100
      value: 81.718
    - type: map_at_1000
      value: 81.742
    - type: map_at_20
      value: 81.486
    - type: map_at_3
      value: 77.972
    - type: map_at_5
      value: 79.903
    - type: mrr_at_1
      value: 77.64
    - type: mrr_at_10
      value: 84.584
    - type: mrr_at_100
      value: 84.722
    - type: mrr_at_1000
      value: 84.724
    - type: mrr_at_20
      value: 84.684
    - type: mrr_at_3
      value: 83.325
    - type: mrr_at_5
      value: 84.15899999999999
    - type: ndcg_at_1
      value: 77.66999999999999
    - type: ndcg_at_10
      value: 85.30499999999999
    - type: ndcg_at_100
      value: 86.834
    - type: ndcg_at_1000
      value: 87.033
    - type: ndcg_at_20
      value: 86.12100000000001
    - type: ndcg_at_3
      value: 81.974
    - type: ndcg_at_5
      value: 83.813
    - type: precision_at_1
      value: 77.66999999999999
    - type: precision_at_10
      value: 12.931000000000001
    - type: precision_at_100
      value: 1.5
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_20
      value: 6.903
    - type: precision_at_3
      value: 35.730000000000004
    - type: precision_at_5
      value: 23.642
    - type: recall_at_1
      value: 67.465
    - type: recall_at_10
      value: 93.581
    - type: recall_at_100
      value: 98.91499999999999
    - type: recall_at_1000
      value: 99.90599999999999
    - type: recall_at_20
      value: 96.221
    - type: recall_at_3
      value: 84.071
    - type: recall_at_5
      value: 89.14999999999999
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering
      name: MTEB RedditClustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 45.929215298244664
    - 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: 51.444598402601414
    - 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: 3.5929999999999995
    - type: map_at_10
      value: 8.753
    - type: map_at_100
      value: 10.349
    - type: map_at_1000
      value: 10.624
    - type: map_at_20
      value: 9.553
    - type: map_at_3
      value: 6.2700000000000005
    - type: map_at_5
      value: 7.5329999999999995
    - type: mrr_at_1
      value: 17.7
    - type: mrr_at_10
      value: 27.167
    - type: mrr_at_100
      value: 28.351
    - type: mrr_at_1000
      value: 28.418
    - type: mrr_at_20
      value: 27.819
    - type: mrr_at_3
      value: 24.282999999999998
    - type: mrr_at_5
      value: 26.073
    - type: ndcg_at_1
      value: 17.7
    - type: ndcg_at_10
      value: 15.312000000000001
    - type: ndcg_at_100
      value: 22.178
    - type: ndcg_at_1000
      value: 27.575
    - type: ndcg_at_20
      value: 17.648
    - type: ndcg_at_3
      value: 14.41
    - type: ndcg_at_5
      value: 12.774
    - type: precision_at_1
      value: 17.7
    - type: precision_at_10
      value: 7.93
    - type: precision_at_100
      value: 1.7930000000000001
    - type: precision_at_1000
      value: 0.31
    - type: precision_at_20
      value: 5.315
    - type: precision_at_3
      value: 13.367
    - type: precision_at_5
      value: 11.26
    - type: recall_at_1
      value: 3.5929999999999995
    - type: recall_at_10
      value: 16.088
    - type: recall_at_100
      value: 36.39
    - type: recall_at_1000
      value: 62.932
    - type: recall_at_20
      value: 21.562
    - type: recall_at_3
      value: 8.123
    - type: recall_at_5
      value: 11.393
  - task:
      type: STS
    dataset:
      type: mteb/sickr-sts
      name: MTEB SICK-R
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 82.6885494958054
    - type: cos_sim_spearman
      value: 76.0433546110243
    - type: euclidean_pearson
      value: 79.85820435751087
    - type: euclidean_spearman
      value: 75.9326257444857
    - type: manhattan_pearson
      value: 79.6973024858654
    - type: manhattan_spearman
      value: 75.71084698490509
  - task:
      type: STS
    dataset:
      type: mteb/sts12-sts
      name: MTEB STS12
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 77.34659218404506
    - type: cos_sim_spearman
      value: 69.49541146727839
    - type: euclidean_pearson
      value: 74.80982564474151
    - type: euclidean_spearman
      value: 70.04102091813081
    - type: manhattan_pearson
      value: 75.00200126757426
    - type: manhattan_spearman
      value: 70.22802660355588
  - task:
      type: STS
    dataset:
      type: mteb/sts13-sts
      name: MTEB STS13
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 79.91444494464905
    - type: cos_sim_spearman
      value: 80.96085686108583
    - type: euclidean_pearson
      value: 80.5915387592164
    - type: euclidean_spearman
      value: 80.8861855866439
    - type: manhattan_pearson
      value: 80.46881359994653
    - type: manhattan_spearman
      value: 80.80230339264102
  - task:
      type: STS
    dataset:
      type: mteb/sts14-sts
      name: MTEB STS14
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 80.81974904249208
    - type: cos_sim_spearman
      value: 77.08348207580887
    - type: euclidean_pearson
      value: 80.13431221409199
    - type: euclidean_spearman
      value: 77.31778188790902
    - type: manhattan_pearson
      value: 80.05343415464556
    - type: manhattan_spearman
      value: 77.26095229151665
  - task:
      type: STS
    dataset:
      type: mteb/sts15-sts
      name: MTEB STS15
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 84.37398871508579
    - type: cos_sim_spearman
      value: 85.41548418250477
    - type: euclidean_pearson
      value: 85.18569982361353
    - type: euclidean_spearman
      value: 85.73446512176643
    - type: manhattan_pearson
      value: 85.1016252976206
    - type: manhattan_spearman
      value: 85.66092136939069
  - task:
      type: STS
    dataset:
      type: mteb/sts16-sts
      name: MTEB STS16
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 80.59702638640928
    - type: cos_sim_spearman
      value: 82.29583005583622
    - type: euclidean_pearson
      value: 81.83307796549182
    - type: euclidean_spearman
      value: 82.39554204652183
    - type: manhattan_pearson
      value: 81.78282737393326
    - type: manhattan_spearman
      value: 82.34235304571907
  - 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: 86.89190122908971
    - type: cos_sim_spearman
      value: 88.03461344591356
    - type: euclidean_pearson
      value: 87.81999485969313
    - type: euclidean_spearman
      value: 88.07040076481854
    - type: manhattan_pearson
      value: 87.53382294293554
    - type: manhattan_spearman
      value: 87.76615089464353
  - 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: 57.97869820676485
    - type: cos_sim_spearman
      value: 64.12171377270657
    - type: euclidean_pearson
      value: 60.9601725696545
    - type: euclidean_spearman
      value: 63.48982922146721
    - type: manhattan_pearson
      value: 61.37553142926566
    - type: manhattan_spearman
      value: 63.759462595791796
  - task:
      type: STS
    dataset:
      type: mteb/stsbenchmark-sts
      name: MTEB STSBenchmark
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 83.14812517797631
    - type: cos_sim_spearman
      value: 83.33681512924129
    - type: euclidean_pearson
      value: 84.0552689078266
    - type: euclidean_spearman
      value: 83.45075258664495
    - type: manhattan_pearson
      value: 83.94309504683835
    - type: manhattan_spearman
      value: 83.37311472277489
  - task:
      type: Reranking
    dataset:
      type: mteb/scidocs-reranking
      name: MTEB SciDocsRR
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 77.89395841192561
    - type: mrr
      value: 93.39039319431475
  - task:
      type: Retrieval
    dataset:
      type: mteb/scifact
      name: MTEB SciFact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 47.65
    - type: map_at_10
      value: 58.287
    - type: map_at_100
      value: 58.965999999999994
    - type: map_at_1000
      value: 58.998
    - type: map_at_20
      value: 58.709
    - type: map_at_3
      value: 55.272
    - type: map_at_5
      value: 57.135999999999996
    - type: mrr_at_1
      value: 50.333000000000006
    - type: mrr_at_10
      value: 59.589999999999996
    - type: mrr_at_100
      value: 60.129999999999995
    - type: mrr_at_1000
      value: 60.162000000000006
    - type: mrr_at_20
      value: 59.95700000000001
    - type: mrr_at_3
      value: 57.389
    - type: mrr_at_5
      value: 58.656
    - type: ndcg_at_1
      value: 50.333000000000006
    - type: ndcg_at_10
      value: 63.232
    - type: ndcg_at_100
      value: 66.213
    - type: ndcg_at_1000
      value: 67.203
    - type: ndcg_at_20
      value: 64.63499999999999
    - type: ndcg_at_3
      value: 58.163
    - type: ndcg_at_5
      value: 60.785999999999994
    - type: precision_at_1
      value: 50.333000000000006
    - type: precision_at_10
      value: 8.633000000000001
    - type: precision_at_100
      value: 1.03
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_20
      value: 4.633
    - type: precision_at_3
      value: 22.889
    - type: precision_at_5
      value: 15.4
    - type: recall_at_1
      value: 47.65
    - type: recall_at_10
      value: 76.95
    - type: recall_at_100
      value: 90.333
    - type: recall_at_1000
      value: 98.333
    - type: recall_at_20
      value: 82.267
    - type: recall_at_3
      value: 63.632999999999996
    - type: recall_at_5
      value: 69.978
  - task:
      type: PairClassification
    dataset:
      type: mteb/sprintduplicatequestions-pairclassification
      name: MTEB SprintDuplicateQuestions
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.82277227722773
    - type: cos_sim_ap
      value: 95.3535743677476
    - type: cos_sim_f1
      value: 91.00050276520865
    - type: cos_sim_precision
      value: 91.50657229524772
    - type: cos_sim_recall
      value: 90.5
    - type: dot_accuracy
      value: 99.73267326732673
    - type: dot_ap
      value: 92.1266370356305
    - type: dot_f1
      value: 86.13810741687979
    - type: dot_precision
      value: 88.1675392670157
    - type: dot_recall
      value: 84.2
    - type: euclidean_accuracy
      value: 99.82277227722773
    - type: euclidean_ap
      value: 95.24537694377634
    - type: euclidean_f1
      value: 90.91831557584982
    - type: euclidean_precision
      value: 92.27600411946447
    - type: euclidean_recall
      value: 89.60000000000001
    - type: manhattan_accuracy
      value: 99.81881188118813
    - type: manhattan_ap
      value: 95.30188096008806
    - type: manhattan_f1
      value: 90.83625438157236
    - type: manhattan_precision
      value: 90.97291875626881
    - type: manhattan_recall
      value: 90.7
    - type: max_accuracy
      value: 99.82277227722773
    - type: max_ap
      value: 95.3535743677476
    - type: max_f1
      value: 91.00050276520865
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering
      name: MTEB StackExchangeClustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 52.18146042107239
    - type: v_measures
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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: 30.666751785479224
    - 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: 46.78149995864765
    - type: mrr
      value: 47.45282393260334
  - task:
      type: Summarization
    dataset:
      type: mteb/summeval
      name: MTEB SummEval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.202698233290022
    - type: cos_sim_spearman
      value: 30.971936219818662
    - type: dot_pearson
      value: 25.486069760264634
    - type: dot_spearman
      value: 25.811060638581246
  - task:
      type: Retrieval
    dataset:
      type: mteb/trec-covid
      name: MTEB TRECCOVID
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.16999999999999998
    - type: map_at_10
      value: 0.943
    - type: map_at_100
      value: 5.0200000000000005
    - type: map_at_1000
      value: 13.855
    - type: map_at_20
      value: 1.609
    - type: map_at_3
      value: 0.384
    - type: map_at_5
      value: 0.5660000000000001
    - type: mrr_at_1
      value: 68.0
    - type: mrr_at_10
      value: 77.983
    - type: mrr_at_100
      value: 78.16499999999999
    - type: mrr_at_1000
      value: 78.16499999999999
    - type: mrr_at_20
      value: 78.16499999999999
    - type: mrr_at_3
      value: 75.667
    - type: mrr_at_5
      value: 77.067
    - type: ndcg_at_1
      value: 62.0
    - type: ndcg_at_10
      value: 47.772999999999996
    - type: ndcg_at_100
      value: 36.15
    - type: ndcg_at_1000
      value: 36.071
    - type: ndcg_at_20
      value: 44.641
    - type: ndcg_at_3
      value: 52.608999999999995
    - type: ndcg_at_5
      value: 50.397999999999996
    - type: precision_at_1
      value: 68.0
    - type: precision_at_10
      value: 50.8
    - type: precision_at_100
      value: 37.62
    - type: precision_at_1000
      value: 16.97
    - type: precision_at_20
      value: 47.099999999999994
    - type: precision_at_3
      value: 56.667
    - type: precision_at_5
      value: 54.0
    - type: recall_at_1
      value: 0.16999999999999998
    - type: recall_at_10
      value: 1.2349999999999999
    - type: recall_at_100
      value: 8.666
    - type: recall_at_1000
      value: 35.326
    - type: recall_at_20
      value: 2.276
    - type: recall_at_3
      value: 0.428
    - type: recall_at_5
      value: 0.672
  - task:
      type: Retrieval
    dataset:
      type: mteb/touche2020
      name: MTEB Touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.897
    - type: map_at_10
      value: 6.034
    - type: map_at_100
      value: 10.475
    - type: map_at_1000
      value: 11.95
    - type: map_at_20
      value: 8.149000000000001
    - type: map_at_3
      value: 2.8449999999999998
    - type: map_at_5
      value: 3.972
    - type: mrr_at_1
      value: 24.490000000000002
    - type: mrr_at_10
      value: 33.751
    - type: mrr_at_100
      value: 35.544
    - type: mrr_at_1000
      value: 35.544
    - type: mrr_at_20
      value: 34.926
    - type: mrr_at_3
      value: 29.252
    - type: mrr_at_5
      value: 31.905
    - type: ndcg_at_1
      value: 22.448999999999998
    - type: ndcg_at_10
      value: 16.303
    - type: ndcg_at_100
      value: 27.165
    - type: ndcg_at_1000
      value: 39.736
    - type: ndcg_at_20
      value: 18.340999999999998
    - type: ndcg_at_3
      value: 15.137999999999998
    - type: ndcg_at_5
      value: 16.332
    - type: precision_at_1
      value: 24.490000000000002
    - type: precision_at_10
      value: 15.714
    - type: precision_at_100
      value: 6.184
    - type: precision_at_1000
      value: 1.439
    - type: precision_at_20
      value: 13.163
    - type: precision_at_3
      value: 15.645999999999999
    - type: precision_at_5
      value: 17.551
    - type: recall_at_1
      value: 1.897
    - type: recall_at_10
      value: 11.938
    - type: recall_at_100
      value: 39.249
    - type: recall_at_1000
      value: 78.121
    - type: recall_at_20
      value: 19.244
    - type: recall_at_3
      value: 3.5409999999999995
    - type: recall_at_5
      value: 6.297999999999999
  - task:
      type: Classification
    dataset:
      type: mteb/toxic_conversations_50k
      name: MTEB ToxicConversationsClassification
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 66.2939453125
    - type: ap
      value: 11.764275936169392
    - type: f1
      value: 50.50689429240701
  - task:
      type: Classification
    dataset:
      type: mteb/tweet_sentiment_extraction
      name: MTEB TweetSentimentExtractionClassification
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 59.49066213921902
    - type: f1
      value: 59.85044985699777
  - task:
      type: Clustering
    dataset:
      type: mteb/twentynewsgroups-clustering
      name: MTEB TwentyNewsgroupsClustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 39.44109250212289
    - 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: 84.25821064552662
    - type: cos_sim_ap
      value: 67.96785265119063
    - type: cos_sim_f1
      value: 65.0070788107598
    - type: cos_sim_precision
      value: 58.792146820315835
    - type: cos_sim_recall
      value: 72.69129287598945
    - type: dot_accuracy
      value: 81.47463789712106
    - type: dot_ap
      value: 58.234902049577684
    - type: dot_f1
      value: 56.73442037078401
    - type: dot_precision
      value: 49.18667699457785
    - type: dot_recall
      value: 67.01846965699208
    - type: euclidean_accuracy
      value: 84.30589497526375
    - type: euclidean_ap
      value: 68.07824251821404
    - type: euclidean_f1
      value: 65.09073543457498
    - type: euclidean_precision
      value: 59.44177932839075
    - type: euclidean_recall
      value: 71.92612137203166
    - type: manhattan_accuracy
      value: 84.24032902187518
    - type: manhattan_ap
      value: 67.76838044141897
    - type: manhattan_f1
      value: 64.75698520779525
    - type: manhattan_precision
      value: 58.333333333333336
    - type: manhattan_recall
      value: 72.77044854881267
    - type: max_accuracy
      value: 84.30589497526375
    - type: max_ap
      value: 68.07824251821404
    - type: max_f1
      value: 65.09073543457498
  - task:
      type: PairClassification
    dataset:
      type: mteb/twitterurlcorpus-pairclassification
      name: MTEB TwitterURLCorpus
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.2951061435169
    - type: cos_sim_ap
      value: 84.74905878045149
    - type: cos_sim_f1
      value: 77.01659871869538
    - type: cos_sim_precision
      value: 73.0392156862745
    - type: cos_sim_recall
      value: 81.45210963966738
    - type: dot_accuracy
      value: 86.37598478674273
    - type: dot_ap
      value: 79.17253140971533
    - type: dot_f1
      value: 73.19411657889958
    - type: dot_precision
      value: 69.27201484842236
    - type: dot_recall
      value: 77.58700338774254
    - type: euclidean_accuracy
      value: 88.29122521054062
    - type: euclidean_ap
      value: 84.64901724668165
    - type: euclidean_f1
      value: 76.99685189252507
    - type: euclidean_precision
      value: 73.39148639218422
    - type: euclidean_recall
      value: 80.97474591931014
    - type: manhattan_accuracy
      value: 88.29316567702877
    - type: manhattan_ap
      value: 84.5869003947086
    - type: manhattan_f1
      value: 76.9094138543517
    - type: manhattan_precision
      value: 74.03818751781134
    - type: manhattan_recall
      value: 80.01231906375116
    - type: max_accuracy
      value: 88.2951061435169
    - type: max_ap
      value: 84.74905878045149
    - type: max_f1
      value: 77.01659871869538
---
# Bulbasaur

This is a distill of [gte-tiny](https://huggingface.co/TaylorAI/gte-tiny) trained 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/Bulbasaur')
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/Bulbasaur')
model = AutoModel.from_pretrained('Mihaiii/Bulbasaur')

# 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.