sentence-transformers gguf mteb transformers Qwen sentence-similarity llama-cpp gguf-my-repo model-index autotrain_compatible endpoints_compatible region:us conversational
---
tags:
- mteb
- sentence-transformers
- transformers
- Qwen
- sentence-similarity
- llama-cpp
- gguf-my-repo
model-index:
- name: gte-qwen1.5-7b
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 83.16417910447761
    - type: ap
      value: 49.37655308937739
    - type: f1
      value: 77.52987230462615
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 96.6959
    - type: ap
      value: 94.90885739242472
    - type: f1
      value: 96.69477648952649
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 62.168
    - type: f1
      value: 60.411431278343755
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 36.415
    - type: map_at_10
      value: 53.505
    - type: map_at_100
      value: 54.013
    - type: map_at_1000
      value: 54.013
    - type: map_at_3
      value: 48.459
    - type: map_at_5
      value: 51.524
    - type: mrr_at_1
      value: 36.842000000000006
    - type: mrr_at_10
      value: 53.679
    - type: mrr_at_100
      value: 54.17999999999999
    - type: mrr_at_1000
      value: 54.17999999999999
    - type: mrr_at_3
      value: 48.613
    - type: mrr_at_5
      value: 51.696
    - type: ndcg_at_1
      value: 36.415
    - type: ndcg_at_10
      value: 62.644999999999996
    - type: ndcg_at_100
      value: 64.60000000000001
    - type: ndcg_at_1000
      value: 64.60000000000001
    - type: ndcg_at_3
      value: 52.44799999999999
    - type: ndcg_at_5
      value: 57.964000000000006
    - type: precision_at_1
      value: 36.415
    - type: precision_at_10
      value: 9.161
    - type: precision_at_100
      value: 0.996
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 21.337
    - type: precision_at_5
      value: 15.476999999999999
    - type: recall_at_1
      value: 36.415
    - type: recall_at_10
      value: 91.607
    - type: recall_at_100
      value: 99.644
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 64.011
    - type: recall_at_5
      value: 77.383
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 56.40183100758549
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 51.44814171373338
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 66.00208703259058
    - type: mrr
      value: 78.95165545442553
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 82.12591694410098
    - type: cos_sim_spearman
      value: 81.11570369802254
    - type: euclidean_pearson
      value: 80.91709076204458
    - type: euclidean_spearman
      value: 81.11570369802254
    - type: manhattan_pearson
      value: 80.71719561024605
    - type: manhattan_spearman
      value: 81.21510355327713
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 81.67857142857142
    - type: f1
      value: 80.84103272994895
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 49.008657468552016
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 45.05901064421589
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 32.694
    - type: map_at_10
      value: 43.895
    - type: map_at_100
      value: 45.797
    - type: map_at_1000
      value: 45.922000000000004
    - type: map_at_3
      value: 40.141
    - type: map_at_5
      value: 42.077
    - type: mrr_at_1
      value: 40.2
    - type: mrr_at_10
      value: 50.11
    - type: mrr_at_100
      value: 51.101
    - type: mrr_at_1000
      value: 51.13100000000001
    - type: mrr_at_3
      value: 47.735
    - type: mrr_at_5
      value: 48.922
    - type: ndcg_at_1
      value: 40.2
    - type: ndcg_at_10
      value: 50.449999999999996
    - type: ndcg_at_100
      value: 56.85
    - type: ndcg_at_1000
      value: 58.345
    - type: ndcg_at_3
      value: 45.261
    - type: ndcg_at_5
      value: 47.298
    - type: precision_at_1
      value: 40.2
    - type: precision_at_10
      value: 9.742
    - type: precision_at_100
      value: 1.6480000000000001
    - type: precision_at_1000
      value: 0.214
    - type: precision_at_3
      value: 21.841
    - type: precision_at_5
      value: 15.68
    - type: recall_at_1
      value: 32.694
    - type: recall_at_10
      value: 62.751999999999995
    - type: recall_at_100
      value: 88.619
    - type: recall_at_1000
      value: 97.386
    - type: recall_at_3
      value: 47.087
    - type: recall_at_5
      value: 53.108999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 27.849
    - type: map_at_10
      value: 37.938
    - type: map_at_100
      value: 39.211
    - type: map_at_1000
      value: 39.333
    - type: map_at_3
      value: 35.314
    - type: map_at_5
      value: 36.666
    - type: mrr_at_1
      value: 34.904
    - type: mrr_at_10
      value: 43.869
    - type: mrr_at_100
      value: 44.614
    - type: mrr_at_1000
      value: 44.662
    - type: mrr_at_3
      value: 41.815000000000005
    - type: mrr_at_5
      value: 42.943
    - type: ndcg_at_1
      value: 34.904
    - type: ndcg_at_10
      value: 43.605
    - type: ndcg_at_100
      value: 48.339999999999996
    - type: ndcg_at_1000
      value: 50.470000000000006
    - type: ndcg_at_3
      value: 39.835
    - type: ndcg_at_5
      value: 41.364000000000004
    - type: precision_at_1
      value: 34.904
    - type: precision_at_10
      value: 8.222999999999999
    - type: precision_at_100
      value: 1.332
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 19.575
    - type: precision_at_5
      value: 13.58
    - type: recall_at_1
      value: 27.849
    - type: recall_at_10
      value: 53.635
    - type: recall_at_100
      value: 73.932
    - type: recall_at_1000
      value: 87.29599999999999
    - type: recall_at_3
      value: 42.019
    - type: recall_at_5
      value: 46.58
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 29.182999999999996
    - type: map_at_10
      value: 41.233
    - type: map_at_100
      value: 42.52
    - type: map_at_1000
      value: 42.589
    - type: map_at_3
      value: 37.284
    - type: map_at_5
      value: 39.586
    - type: mrr_at_1
      value: 33.793
    - type: mrr_at_10
      value: 44.572
    - type: mrr_at_100
      value: 45.456
    - type: mrr_at_1000
      value: 45.497
    - type: mrr_at_3
      value: 41.275
    - type: mrr_at_5
      value: 43.278
    - type: ndcg_at_1
      value: 33.793
    - type: ndcg_at_10
      value: 47.823
    - type: ndcg_at_100
      value: 52.994
    - type: ndcg_at_1000
      value: 54.400000000000006
    - type: ndcg_at_3
      value: 40.82
    - type: ndcg_at_5
      value: 44.426
    - type: precision_at_1
      value: 33.793
    - type: precision_at_10
      value: 8.312999999999999
    - type: precision_at_100
      value: 1.191
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 18.662
    - type: precision_at_5
      value: 13.668
    - type: recall_at_1
      value: 29.182999999999996
    - type: recall_at_10
      value: 64.14999999999999
    - type: recall_at_100
      value: 86.533
    - type: recall_at_1000
      value: 96.492
    - type: recall_at_3
      value: 45.7
    - type: recall_at_5
      value: 54.330999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 24.389
    - type: map_at_10
      value: 33.858
    - type: map_at_100
      value: 35.081
    - type: map_at_1000
      value: 35.161
    - type: map_at_3
      value: 30.793
    - type: map_at_5
      value: 32.336
    - type: mrr_at_1
      value: 27.006000000000004
    - type: mrr_at_10
      value: 36.378
    - type: mrr_at_100
      value: 37.345
    - type: mrr_at_1000
      value: 37.405
    - type: mrr_at_3
      value: 33.578
    - type: mrr_at_5
      value: 34.991
    - type: ndcg_at_1
      value: 27.006000000000004
    - type: ndcg_at_10
      value: 39.612
    - type: ndcg_at_100
      value: 45.216
    - type: ndcg_at_1000
      value: 47.12
    - type: ndcg_at_3
      value: 33.566
    - type: ndcg_at_5
      value: 36.105
    - type: precision_at_1
      value: 27.006000000000004
    - type: precision_at_10
      value: 6.372999999999999
    - type: precision_at_100
      value: 0.968
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 14.501
    - type: precision_at_5
      value: 10.169
    - type: recall_at_1
      value: 24.389
    - type: recall_at_10
      value: 55.131
    - type: recall_at_100
      value: 80.315
    - type: recall_at_1000
      value: 94.284
    - type: recall_at_3
      value: 38.643
    - type: recall_at_5
      value: 44.725
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 15.845999999999998
    - type: map_at_10
      value: 25.019000000000002
    - type: map_at_100
      value: 26.478
    - type: map_at_1000
      value: 26.598
    - type: map_at_3
      value: 21.595
    - type: map_at_5
      value: 23.335
    - type: mrr_at_1
      value: 20.274
    - type: mrr_at_10
      value: 29.221000000000004
    - type: mrr_at_100
      value: 30.354999999999997
    - type: mrr_at_1000
      value: 30.419
    - type: mrr_at_3
      value: 26.161
    - type: mrr_at_5
      value: 27.61
    - type: ndcg_at_1
      value: 20.274
    - type: ndcg_at_10
      value: 31.014000000000003
    - type: ndcg_at_100
      value: 37.699
    - type: ndcg_at_1000
      value: 40.363
    - type: ndcg_at_3
      value: 24.701999999999998
    - type: ndcg_at_5
      value: 27.261999999999997
    - type: precision_at_1
      value: 20.274
    - type: precision_at_10
      value: 6.219
    - type: precision_at_100
      value: 1.101
    - type: precision_at_1000
      value: 0.146
    - type: precision_at_3
      value: 12.231
    - type: precision_at_5
      value: 9.129
    - type: recall_at_1
      value: 15.845999999999998
    - type: recall_at_10
      value: 45.358
    - type: recall_at_100
      value: 74.232
    - type: recall_at_1000
      value: 92.985
    - type: recall_at_3
      value: 28.050000000000004
    - type: recall_at_5
      value: 34.588
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 33.808
    - type: map_at_10
      value: 46.86
    - type: map_at_100
      value: 48.237
    - type: map_at_1000
      value: 48.331
    - type: map_at_3
      value: 42.784
    - type: map_at_5
      value: 45.015
    - type: mrr_at_1
      value: 41.771
    - type: mrr_at_10
      value: 52.35300000000001
    - type: mrr_at_100
      value: 53.102000000000004
    - type: mrr_at_1000
      value: 53.132999999999996
    - type: mrr_at_3
      value: 49.663000000000004
    - type: mrr_at_5
      value: 51.27
    - type: ndcg_at_1
      value: 41.771
    - type: ndcg_at_10
      value: 53.562
    - type: ndcg_at_100
      value: 58.809999999999995
    - type: ndcg_at_1000
      value: 60.23
    - type: ndcg_at_3
      value: 47.514
    - type: ndcg_at_5
      value: 50.358999999999995
    - type: precision_at_1
      value: 41.771
    - type: precision_at_10
      value: 10.038
    - type: precision_at_100
      value: 1.473
    - type: precision_at_1000
      value: 0.17600000000000002
    - type: precision_at_3
      value: 22.875
    - type: precision_at_5
      value: 16.477
    - type: recall_at_1
      value: 33.808
    - type: recall_at_10
      value: 67.721
    - type: recall_at_100
      value: 89.261
    - type: recall_at_1000
      value: 98.042
    - type: recall_at_3
      value: 50.807
    - type: recall_at_5
      value: 58.162000000000006
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 28.105000000000004
    - type: map_at_10
      value: 40.354
    - type: map_at_100
      value: 41.921
    - type: map_at_1000
      value: 42.021
    - type: map_at_3
      value: 36.532
    - type: map_at_5
      value: 38.671
    - type: mrr_at_1
      value: 34.475
    - type: mrr_at_10
      value: 45.342
    - type: mrr_at_100
      value: 46.300000000000004
    - type: mrr_at_1000
      value: 46.343
    - type: mrr_at_3
      value: 42.637
    - type: mrr_at_5
      value: 44.207
    - type: ndcg_at_1
      value: 34.475
    - type: ndcg_at_10
      value: 46.945
    - type: ndcg_at_100
      value: 52.939
    - type: ndcg_at_1000
      value: 54.645999999999994
    - type: ndcg_at_3
      value: 41.065000000000005
    - type: ndcg_at_5
      value: 43.832
    - type: precision_at_1
      value: 34.475
    - type: precision_at_10
      value: 8.892999999999999
    - type: precision_at_100
      value: 1.377
    - type: precision_at_1000
      value: 0.17099999999999999
    - type: precision_at_3
      value: 20.091
    - type: precision_at_5
      value: 14.452000000000002
    - type: recall_at_1
      value: 28.105000000000004
    - type: recall_at_10
      value: 61.253
    - type: recall_at_100
      value: 85.92
    - type: recall_at_1000
      value: 96.799
    - type: recall_at_3
      value: 45.094
    - type: recall_at_5
      value: 52.455
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 24.613833333333332
    - type: map_at_10
      value: 34.763
    - type: map_at_100
      value: 36.17066666666667
    - type: map_at_1000
      value: 36.2905
    - type: map_at_3
      value: 31.53541666666666
    - type: map_at_5
      value: 33.29216666666667
    - type: mrr_at_1
      value: 29.48725
    - type: mrr_at_10
      value: 38.92066666666667
    - type: mrr_at_100
      value: 39.88725000000001
    - type: mrr_at_1000
      value: 39.9435
    - type: mrr_at_3
      value: 36.284083333333335
    - type: mrr_at_5
      value: 37.73941666666667
    - type: ndcg_at_1
      value: 29.48725
    - type: ndcg_at_10
      value: 40.635083333333334
    - type: ndcg_at_100
      value: 46.479416666666665
    - type: ndcg_at_1000
      value: 48.63308333333334
    - type: ndcg_at_3
      value: 35.19483333333333
    - type: ndcg_at_5
      value: 37.68016666666667
    - type: precision_at_1
      value: 29.48725
    - type: precision_at_10
      value: 7.406499999999998
    - type: precision_at_100
      value: 1.2225833333333334
    - type: precision_at_1000
      value: 0.16108333333333336
    - type: precision_at_3
      value: 16.53375
    - type: precision_at_5
      value: 11.919416666666665
    - type: recall_at_1
      value: 24.613833333333332
    - type: recall_at_10
      value: 53.91766666666666
    - type: recall_at_100
      value: 79.18
    - type: recall_at_1000
      value: 93.85133333333333
    - type: recall_at_3
      value: 38.866166666666665
    - type: recall_at_5
      value: 45.21275000000001
    - type: map_at_1
      value: 12.328999999999999
    - type: map_at_10
      value: 20.078
    - type: map_at_100
      value: 21.166999999999998
    - type: map_at_1000
      value: 21.308
    - type: map_at_3
      value: 17.702
    - type: map_at_5
      value: 18.725
    - type: mrr_at_1
      value: 13.678
    - type: mrr_at_10
      value: 21.859
    - type: mrr_at_100
      value: 22.816
    - type: mrr_at_1000
      value: 22.926
    - type: mrr_at_3
      value: 19.378
    - type: mrr_at_5
      value: 20.385
    - type: ndcg_at_1
      value: 13.678
    - type: ndcg_at_10
      value: 24.993000000000002
    - type: ndcg_at_100
      value: 30.464999999999996
    - type: ndcg_at_1000
      value: 33.916000000000004
    - type: ndcg_at_3
      value: 19.966
    - type: ndcg_at_5
      value: 21.712999999999997
    - type: precision_at_1
      value: 13.678
    - type: precision_at_10
      value: 4.473
    - type: precision_at_100
      value: 0.784
    - type: precision_at_1000
      value: 0.116
    - type: precision_at_3
      value: 9.181000000000001
    - type: precision_at_5
      value: 6.506
    - type: recall_at_1
      value: 12.328999999999999
    - type: recall_at_10
      value: 38.592
    - type: recall_at_100
      value: 63.817
    - type: recall_at_1000
      value: 89.67500000000001
    - type: recall_at_3
      value: 24.726
    - type: recall_at_5
      value: 28.959000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 25.106
    - type: map_at_10
      value: 33.367999999999995
    - type: map_at_100
      value: 34.586
    - type: map_at_1000
      value: 34.681
    - type: map_at_3
      value: 31.022
    - type: map_at_5
      value: 32.548
    - type: mrr_at_1
      value: 28.374
    - type: mrr_at_10
      value: 36.521
    - type: mrr_at_100
      value: 37.55
    - type: mrr_at_1000
      value: 37.614999999999995
    - type: mrr_at_3
      value: 34.509
    - type: mrr_at_5
      value: 35.836
    - type: ndcg_at_1
      value: 28.374
    - type: ndcg_at_10
      value: 37.893
    - type: ndcg_at_100
      value: 43.694
    - type: ndcg_at_1000
      value: 46.001999999999995
    - type: ndcg_at_3
      value: 33.825
    - type: ndcg_at_5
      value: 36.201
    - type: precision_at_1
      value: 28.374
    - type: precision_at_10
      value: 5.966
    - type: precision_at_100
      value: 0.9650000000000001
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 14.774999999999999
    - type: precision_at_5
      value: 10.459999999999999
    - type: recall_at_1
      value: 25.106
    - type: recall_at_10
      value: 48.607
    - type: recall_at_100
      value: 74.66000000000001
    - type: recall_at_1000
      value: 91.562
    - type: recall_at_3
      value: 37.669999999999995
    - type: recall_at_5
      value: 43.484
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 13.755
    - type: map_at_10
      value: 20.756
    - type: map_at_100
      value: 22.05
    - type: map_at_1000
      value: 22.201
    - type: map_at_3
      value: 18.243000000000002
    - type: map_at_5
      value: 19.512
    - type: mrr_at_1
      value: 16.93
    - type: mrr_at_10
      value: 24.276
    - type: mrr_at_100
      value: 25.349
    - type: mrr_at_1000
      value: 25.441000000000003
    - type: mrr_at_3
      value: 21.897
    - type: mrr_at_5
      value: 23.134
    - type: ndcg_at_1
      value: 16.93
    - type: ndcg_at_10
      value: 25.508999999999997
    - type: ndcg_at_100
      value: 31.777
    - type: ndcg_at_1000
      value: 35.112
    - type: ndcg_at_3
      value: 20.896
    - type: ndcg_at_5
      value: 22.857
    - type: precision_at_1
      value: 16.93
    - type: precision_at_10
      value: 4.972
    - type: precision_at_100
      value: 0.963
    - type: precision_at_1000
      value: 0.145
    - type: precision_at_3
      value: 10.14
    - type: precision_at_5
      value: 7.536
    - type: recall_at_1
      value: 13.755
    - type: recall_at_10
      value: 36.46
    - type: recall_at_100
      value: 64.786
    - type: recall_at_1000
      value: 88.287
    - type: recall_at_3
      value: 23.681
    - type: recall_at_5
      value: 28.615000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 26.99
    - type: map_at_10
      value: 38.009
    - type: map_at_100
      value: 39.384
    - type: map_at_1000
      value: 39.481
    - type: map_at_3
      value: 34.593
    - type: map_at_5
      value: 36.449999999999996
    - type: mrr_at_1
      value: 31.81
    - type: mrr_at_10
      value: 41.943000000000005
    - type: mrr_at_100
      value: 42.914
    - type: mrr_at_1000
      value: 42.962
    - type: mrr_at_3
      value: 39.179
    - type: mrr_at_5
      value: 40.798
    - type: ndcg_at_1
      value: 31.81
    - type: ndcg_at_10
      value: 44.086
    - type: ndcg_at_100
      value: 50.026
    - type: ndcg_at_1000
      value: 51.903999999999996
    - type: ndcg_at_3
      value: 38.23
    - type: ndcg_at_5
      value: 40.926
    - type: precision_at_1
      value: 31.81
    - type: precision_at_10
      value: 7.761
    - type: precision_at_100
      value: 1.205
    - type: precision_at_1000
      value: 0.148
    - type: precision_at_3
      value: 17.537
    - type: precision_at_5
      value: 12.649
    - type: recall_at_1
      value: 26.99
    - type: recall_at_10
      value: 58.467
    - type: recall_at_100
      value: 83.93
    - type: recall_at_1000
      value: 96.452
    - type: recall_at_3
      value: 42.685
    - type: recall_at_5
      value: 49.341
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 25.312
    - type: map_at_10
      value: 35.788
    - type: map_at_100
      value: 37.616
    - type: map_at_1000
      value: 37.86
    - type: map_at_3
      value: 32.422000000000004
    - type: map_at_5
      value: 34.585
    - type: mrr_at_1
      value: 30.631999999999998
    - type: mrr_at_10
      value: 40.604
    - type: mrr_at_100
      value: 41.745
    - type: mrr_at_1000
      value: 41.788
    - type: mrr_at_3
      value: 37.582
    - type: mrr_at_5
      value: 39.499
    - type: ndcg_at_1
      value: 30.631999999999998
    - type: ndcg_at_10
      value: 42.129
    - type: ndcg_at_100
      value: 48.943
    - type: ndcg_at_1000
      value: 51.089
    - type: ndcg_at_3
      value: 36.658
    - type: ndcg_at_5
      value: 39.818999999999996
    - type: precision_at_1
      value: 30.631999999999998
    - type: precision_at_10
      value: 7.904999999999999
    - type: precision_at_100
      value: 1.664
    - type: precision_at_1000
      value: 0.256
    - type: precision_at_3
      value: 16.996
    - type: precision_at_5
      value: 12.727
    - type: recall_at_1
      value: 25.312
    - type: recall_at_10
      value: 54.886
    - type: recall_at_100
      value: 84.155
    - type: recall_at_1000
      value: 96.956
    - type: recall_at_3
      value: 40.232
    - type: recall_at_5
      value: 48.204
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: mteb/climate-fever
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 19.147
    - type: map_at_10
      value: 33.509
    - type: map_at_100
      value: 35.573
    - type: map_at_1000
      value: 35.769
    - type: map_at_3
      value: 27.983999999999998
    - type: map_at_5
      value: 31.012
    - type: mrr_at_1
      value: 43.844
    - type: mrr_at_10
      value: 56.24
    - type: mrr_at_100
      value: 56.801
    - type: mrr_at_1000
      value: 56.826
    - type: mrr_at_3
      value: 53.290000000000006
    - type: mrr_at_5
      value: 55.13
    - type: ndcg_at_1
      value: 43.844
    - type: ndcg_at_10
      value: 43.996
    - type: ndcg_at_100
      value: 50.965
    - type: ndcg_at_1000
      value: 53.927
    - type: ndcg_at_3
      value: 37.263000000000005
    - type: ndcg_at_5
      value: 39.553
    - type: precision_at_1
      value: 43.844
    - type: precision_at_10
      value: 13.687
    - type: precision_at_100
      value: 2.139
    - type: precision_at_1000
      value: 0.269
    - type: precision_at_3
      value: 28.122000000000003
    - type: precision_at_5
      value: 21.303
    - type: recall_at_1
      value: 19.147
    - type: recall_at_10
      value: 50.449999999999996
    - type: recall_at_100
      value: 74.00099999999999
    - type: recall_at_1000
      value: 90.098
    - type: recall_at_3
      value: 33.343
    - type: recall_at_5
      value: 40.744
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: mteb/dbpedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 8.773
    - type: map_at_10
      value: 21.172
    - type: map_at_100
      value: 30.244
    - type: map_at_1000
      value: 32.127
    - type: map_at_3
      value: 14.510000000000002
    - type: map_at_5
      value: 17.483
    - type: mrr_at_1
      value: 68.25
    - type: mrr_at_10
      value: 77.33
    - type: mrr_at_100
      value: 77.529
    - type: mrr_at_1000
      value: 77.536
    - type: mrr_at_3
      value: 75.708
    - type: mrr_at_5
      value: 76.72099999999999
    - type: ndcg_at_1
      value: 60.0
    - type: ndcg_at_10
      value: 48.045
    - type: ndcg_at_100
      value: 51.620999999999995
    - type: ndcg_at_1000
      value: 58.843999999999994
    - type: ndcg_at_3
      value: 52.922000000000004
    - type: ndcg_at_5
      value: 50.27
    - type: precision_at_1
      value: 68.25
    - type: precision_at_10
      value: 37.625
    - type: precision_at_100
      value: 11.774999999999999
    - type: precision_at_1000
      value: 2.395
    - type: precision_at_3
      value: 55.25
    - type: precision_at_5
      value: 47.599999999999994
    - type: recall_at_1
      value: 8.773
    - type: recall_at_10
      value: 27.332
    - type: recall_at_100
      value: 55.48499999999999
    - type: recall_at_1000
      value: 79.886
    - type: recall_at_3
      value: 15.823
    - type: recall_at_5
      value: 20.523
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 54.52999999999999
    - type: f1
      value: 47.396628088963645
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: mteb/fever
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 85.397
    - type: map_at_10
      value: 90.917
    - type: map_at_100
      value: 91.109
    - type: map_at_1000
      value: 91.121
    - type: map_at_3
      value: 90.045
    - type: map_at_5
      value: 90.602
    - type: mrr_at_1
      value: 92.00399999999999
    - type: mrr_at_10
      value: 95.39999999999999
    - type: mrr_at_100
      value: 95.41
    - type: mrr_at_1000
      value: 95.41
    - type: mrr_at_3
      value: 95.165
    - type: mrr_at_5
      value: 95.348
    - type: ndcg_at_1
      value: 92.00399999999999
    - type: ndcg_at_10
      value: 93.345
    - type: ndcg_at_100
      value: 93.934
    - type: ndcg_at_1000
      value: 94.108
    - type: ndcg_at_3
      value: 92.32000000000001
    - type: ndcg_at_5
      value: 92.899
    - type: precision_at_1
      value: 92.00399999999999
    - type: precision_at_10
      value: 10.839
    - type: precision_at_100
      value: 1.1440000000000001
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 34.298
    - type: precision_at_5
      value: 21.128
    - type: recall_at_1
      value: 85.397
    - type: recall_at_10
      value: 96.375
    - type: recall_at_100
      value: 98.518
    - type: recall_at_1000
      value: 99.515
    - type: recall_at_3
      value: 93.59100000000001
    - type: recall_at_5
      value: 95.134
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: mteb/fiqa
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 27.36
    - type: map_at_10
      value: 46.847
    - type: map_at_100
      value: 49.259
    - type: map_at_1000
      value: 49.389
    - type: map_at_3
      value: 41.095
    - type: map_at_5
      value: 44.084
    - type: mrr_at_1
      value: 51.852
    - type: mrr_at_10
      value: 61.67
    - type: mrr_at_100
      value: 62.395999999999994
    - type: mrr_at_1000
      value: 62.414
    - type: mrr_at_3
      value: 59.465
    - type: mrr_at_5
      value: 60.584
    - type: ndcg_at_1
      value: 51.852
    - type: ndcg_at_10
      value: 55.311
    - type: ndcg_at_100
      value: 62.6
    - type: ndcg_at_1000
      value: 64.206
    - type: ndcg_at_3
      value: 51.159
    - type: ndcg_at_5
      value: 52.038
    - type: precision_at_1
      value: 51.852
    - type: precision_at_10
      value: 15.370000000000001
    - type: precision_at_100
      value: 2.282
    - type: precision_at_1000
      value: 0.258
    - type: precision_at_3
      value: 34.721999999999994
    - type: precision_at_5
      value: 24.846
    - type: recall_at_1
      value: 27.36
    - type: recall_at_10
      value: 63.932
    - type: recall_at_100
      value: 89.824
    - type: recall_at_1000
      value: 98.556
    - type: recall_at_3
      value: 47.227999999999994
    - type: recall_at_5
      value: 53.724000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: mteb/hotpotqa
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 40.655
    - type: map_at_10
      value: 63.824999999999996
    - type: map_at_100
      value: 64.793
    - type: map_at_1000
      value: 64.848
    - type: map_at_3
      value: 60.221000000000004
    - type: map_at_5
      value: 62.474
    - type: mrr_at_1
      value: 81.31
    - type: mrr_at_10
      value: 86.509
    - type: mrr_at_100
      value: 86.677
    - type: mrr_at_1000
      value: 86.682
    - type: mrr_at_3
      value: 85.717
    - type: mrr_at_5
      value: 86.21
    - type: ndcg_at_1
      value: 81.31
    - type: ndcg_at_10
      value: 72.251
    - type: ndcg_at_100
      value: 75.536
    - type: ndcg_at_1000
      value: 76.558
    - type: ndcg_at_3
      value: 67.291
    - type: ndcg_at_5
      value: 70.045
    - type: precision_at_1
      value: 81.31
    - type: precision_at_10
      value: 15.082999999999998
    - type: precision_at_100
      value: 1.764
    - type: precision_at_1000
      value: 0.19
    - type: precision_at_3
      value: 42.971
    - type: precision_at_5
      value: 27.956999999999997
    - type: recall_at_1
      value: 40.655
    - type: recall_at_10
      value: 75.41499999999999
    - type: recall_at_100
      value: 88.224
    - type: recall_at_1000
      value: 94.943
    - type: recall_at_3
      value: 64.456
    - type: recall_at_5
      value: 69.892
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 95.58120000000001
    - type: ap
      value: 93.0407063004784
    - type: f1
      value: 95.57849992996822
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 22.031
    - type: map_at_10
      value: 34.628
    - type: map_at_100
      value: 35.833
    - type: map_at_1000
      value: 35.881
    - type: map_at_3
      value: 30.619000000000003
    - type: map_at_5
      value: 32.982
    - type: mrr_at_1
      value: 22.736
    - type: mrr_at_10
      value: 35.24
    - type: mrr_at_100
      value: 36.381
    - type: mrr_at_1000
      value: 36.424
    - type: mrr_at_3
      value: 31.287
    - type: mrr_at_5
      value: 33.617000000000004
    - type: ndcg_at_1
      value: 22.736
    - type: ndcg_at_10
      value: 41.681000000000004
    - type: ndcg_at_100
      value: 47.371
    - type: ndcg_at_1000
      value: 48.555
    - type: ndcg_at_3
      value: 33.553
    - type: ndcg_at_5
      value: 37.771
    - type: precision_at_1
      value: 22.736
    - type: precision_at_10
      value: 6.625
    - type: precision_at_100
      value: 0.9450000000000001
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 14.331
    - type: precision_at_5
      value: 10.734
    - type: recall_at_1
      value: 22.031
    - type: recall_at_10
      value: 63.378
    - type: recall_at_100
      value: 89.47699999999999
    - type: recall_at_1000
      value: 98.48400000000001
    - type: recall_at_3
      value: 41.388000000000005
    - type: recall_at_5
      value: 51.522999999999996
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 95.75239398084815
    - type: f1
      value: 95.51228043205194
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 84.25900592795259
    - type: f1
      value: 62.14790420114562
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 78.47007397444519
    - type: f1
      value: 76.92133583932912
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 78.19098856758575
    - type: f1
      value: 78.10820805879119
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 44.37013684222983
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 42.003012591979704
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 32.70743071063257
    - type: mrr
      value: 33.938337390083994
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 6.369
    - type: map_at_10
      value: 14.313
    - type: map_at_100
      value: 18.329
    - type: map_at_1000
      value: 20.017
    - type: map_at_3
      value: 10.257
    - type: map_at_5
      value: 12.264999999999999
    - type: mrr_at_1
      value: 49.536
    - type: mrr_at_10
      value: 58.464000000000006
    - type: mrr_at_100
      value: 59.016000000000005
    - type: mrr_at_1000
      value: 59.053
    - type: mrr_at_3
      value: 56.294999999999995
    - type: mrr_at_5
      value: 57.766
    - type: ndcg_at_1
      value: 47.678
    - type: ndcg_at_10
      value: 38.246
    - type: ndcg_at_100
      value: 35.370000000000005
    - type: ndcg_at_1000
      value: 44.517
    - type: ndcg_at_3
      value: 43.368
    - type: ndcg_at_5
      value: 41.892
    - type: precision_at_1
      value: 49.536
    - type: precision_at_10
      value: 28.235
    - type: precision_at_100
      value: 9.014999999999999
    - type: precision_at_1000
      value: 2.257
    - type: precision_at_3
      value: 40.557
    - type: precision_at_5
      value: 36.409000000000006
    - type: recall_at_1
      value: 6.369
    - type: recall_at_10
      value: 19.195999999999998
    - type: recall_at_100
      value: 37.042
    - type: recall_at_1000
      value: 69.203
    - type: recall_at_3
      value: 11.564
    - type: recall_at_5
      value: 15.264
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 39.323
    - type: map_at_10
      value: 54.608999999999995
    - type: map_at_100
      value: 55.523
    - type: map_at_1000
      value: 55.544000000000004
    - type: map_at_3
      value: 50.580000000000005
    - type: map_at_5
      value: 53.064
    - type: mrr_at_1
      value: 44.263999999999996
    - type: mrr_at_10
      value: 57.416
    - type: mrr_at_100
      value: 58.037000000000006
    - type: mrr_at_1000
      value: 58.05200000000001
    - type: mrr_at_3
      value: 54.330999999999996
    - type: mrr_at_5
      value: 56.302
    - type: ndcg_at_1
      value: 44.263999999999996
    - type: ndcg_at_10
      value: 61.785999999999994
    - type: ndcg_at_100
      value: 65.40599999999999
    - type: ndcg_at_1000
      value: 65.859
    - type: ndcg_at_3
      value: 54.518
    - type: ndcg_at_5
      value: 58.53699999999999
    - type: precision_at_1
      value: 44.263999999999996
    - type: precision_at_10
      value: 9.652
    - type: precision_at_100
      value: 1.169
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 24.15
    - type: precision_at_5
      value: 16.848
    - type: recall_at_1
      value: 39.323
    - type: recall_at_10
      value: 80.663
    - type: recall_at_100
      value: 96.072
    - type: recall_at_1000
      value: 99.37700000000001
    - type: recall_at_3
      value: 62.23
    - type: recall_at_5
      value: 71.379
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: mteb/quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 72.02499999999999
    - type: map_at_10
      value: 86.14500000000001
    - type: map_at_100
      value: 86.764
    - type: map_at_1000
      value: 86.776
    - type: map_at_3
      value: 83.249
    - type: map_at_5
      value: 85.083
    - type: mrr_at_1
      value: 82.83
    - type: mrr_at_10
      value: 88.70599999999999
    - type: mrr_at_100
      value: 88.791
    - type: mrr_at_1000
      value: 88.791
    - type: mrr_at_3
      value: 87.815
    - type: mrr_at_5
      value: 88.435
    - type: ndcg_at_1
      value: 82.84
    - type: ndcg_at_10
      value: 89.61200000000001
    - type: ndcg_at_100
      value: 90.693
    - type: ndcg_at_1000
      value: 90.752
    - type: ndcg_at_3
      value: 86.96199999999999
    - type: ndcg_at_5
      value: 88.454
    - type: precision_at_1
      value: 82.84
    - type: precision_at_10
      value: 13.600000000000001
    - type: precision_at_100
      value: 1.543
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 38.092999999999996
    - type: precision_at_5
      value: 25.024
    - type: recall_at_1
      value: 72.02499999999999
    - type: recall_at_10
      value: 96.21600000000001
    - type: recall_at_100
      value: 99.76
    - type: recall_at_1000
      value: 99.996
    - type: recall_at_3
      value: 88.57000000000001
    - type: recall_at_5
      value: 92.814
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 73.37297191949929
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 72.50752304246946
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: mteb/scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 6.4479999999999995
    - type: map_at_10
      value: 17.268
    - type: map_at_100
      value: 20.502000000000002
    - type: map_at_1000
      value: 20.904
    - type: map_at_3
      value: 11.951
    - type: map_at_5
      value: 14.494000000000002
    - type: mrr_at_1
      value: 31.900000000000002
    - type: mrr_at_10
      value: 45.084999999999994
    - type: mrr_at_100
      value: 46.145
    - type: mrr_at_1000
      value: 46.164
    - type: mrr_at_3
      value: 41.6
    - type: mrr_at_5
      value: 43.76
    - type: ndcg_at_1
      value: 31.900000000000002
    - type: ndcg_at_10
      value: 27.694000000000003
    - type: ndcg_at_100
      value: 39.016
    - type: ndcg_at_1000
      value: 44.448
    - type: ndcg_at_3
      value: 26.279999999999998
    - type: ndcg_at_5
      value: 22.93
    - type: precision_at_1
      value: 31.900000000000002
    - type: precision_at_10
      value: 14.399999999999999
    - type: precision_at_100
      value: 3.082
    - type: precision_at_1000
      value: 0.436
    - type: precision_at_3
      value: 24.667
    - type: precision_at_5
      value: 20.200000000000003
    - type: recall_at_1
      value: 6.4479999999999995
    - type: recall_at_10
      value: 29.243000000000002
    - type: recall_at_100
      value: 62.547
    - type: recall_at_1000
      value: 88.40299999999999
    - type: recall_at_3
      value: 14.988000000000001
    - type: recall_at_5
      value: 20.485
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 80.37839336866843
    - type: cos_sim_spearman
      value: 79.14737320486729
    - type: euclidean_pearson
      value: 78.74010870392799
    - type: euclidean_spearman
      value: 79.1472505448557
    - type: manhattan_pearson
      value: 78.76735626972086
    - type: manhattan_spearman
      value: 79.18509055331465
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 84.98947740740309
    - type: cos_sim_spearman
      value: 76.52068694652895
    - type: euclidean_pearson
      value: 81.10952542010847
    - type: euclidean_spearman
      value: 76.52162808897668
    - type: manhattan_pearson
      value: 81.13752577872523
    - type: manhattan_spearman
      value: 76.55073892851847
    - type: cos_sim_pearson
      value: 84.99292517797305
    - type: cos_sim_spearman
      value: 76.52287451692155
    - type: euclidean_pearson
      value: 81.11616055544546
    - type: euclidean_spearman
      value: 76.525387473028
    - type: manhattan_pearson
      value: 81.14367598670032
    - type: manhattan_spearman
      value: 76.55571799438607
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 88.14795728641734
    - type: cos_sim_spearman
      value: 88.62720469210905
    - type: euclidean_pearson
      value: 87.96160445129142
    - type: euclidean_spearman
      value: 88.62615925428736
    - type: manhattan_pearson
      value: 87.86760858379527
    - type: manhattan_spearman
      value: 88.5613166629411
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 85.06444249948838
    - type: cos_sim_spearman
      value: 83.32346434965837
    - type: euclidean_pearson
      value: 83.86264166785146
    - type: euclidean_spearman
      value: 83.32323156068114
    - type: manhattan_pearson
      value: 83.87253909108084
    - type: manhattan_spearman
      value: 83.42760090819642
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 87.00847937091636
    - type: cos_sim_spearman
      value: 87.50432670473445
    - type: euclidean_pearson
      value: 87.21611485565168
    - type: euclidean_spearman
      value: 87.50387351928698
    - type: manhattan_pearson
      value: 87.30690660623411
    - type: manhattan_spearman
      value: 87.61147161393255
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 85.51456553517488
    - type: cos_sim_spearman
      value: 86.39208323626035
    - type: euclidean_pearson
      value: 85.74698473006475
    - type: euclidean_spearman
      value: 86.3892506146807
    - type: manhattan_pearson
      value: 85.77493611949014
    - type: manhattan_spearman
      value: 86.42961510735024
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 88.63402051628222
    - type: cos_sim_spearman
      value: 87.78994504115502
    - type: euclidean_pearson
      value: 88.44861926968403
    - type: euclidean_spearman
      value: 87.80670473078185
    - type: manhattan_pearson
      value: 88.4773722010208
    - type: manhattan_spearman
      value: 87.85175600656768
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 65.9659729672951
    - type: cos_sim_spearman
      value: 66.39891735341361
    - type: euclidean_pearson
      value: 68.040150710449
    - type: euclidean_spearman
      value: 66.41777234484414
    - type: manhattan_pearson
      value: 68.16264809387305
    - type: manhattan_spearman
      value: 66.31608161700346
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 86.91024857159385
    - type: cos_sim_spearman
      value: 87.35031011815016
    - type: euclidean_pearson
      value: 86.94569462996033
    - type: euclidean_spearman
      value: 87.34929703462852
    - type: manhattan_pearson
      value: 86.94404111225616
    - type: manhattan_spearman
      value: 87.37827218003393
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 87.89077927002596
    - type: mrr
      value: 96.94650937297997
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 57.994
    - type: map_at_10
      value: 70.07100000000001
    - type: map_at_100
      value: 70.578
    - type: map_at_1000
      value: 70.588
    - type: map_at_3
      value: 67.228
    - type: map_at_5
      value: 68.695
    - type: mrr_at_1
      value: 61.333000000000006
    - type: mrr_at_10
      value: 71.342
    - type: mrr_at_100
      value: 71.739
    - type: mrr_at_1000
      value: 71.75
    - type: mrr_at_3
      value: 69.389
    - type: mrr_at_5
      value: 70.322
    - type: ndcg_at_1
      value: 61.333000000000006
    - type: ndcg_at_10
      value: 75.312
    - type: ndcg_at_100
      value: 77.312
    - type: ndcg_at_1000
      value: 77.50200000000001
    - type: ndcg_at_3
      value: 70.72
    - type: ndcg_at_5
      value: 72.616
    - type: precision_at_1
      value: 61.333000000000006
    - type: precision_at_10
      value: 10.167
    - type: precision_at_100
      value: 1.117
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 28.111000000000004
    - type: precision_at_5
      value: 18.333
    - type: recall_at_1
      value: 57.994
    - type: recall_at_10
      value: 89.944
    - type: recall_at_100
      value: 98.667
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_3
      value: 77.694
    - type: recall_at_5
      value: 82.339
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.81485148514851
    - type: cos_sim_ap
      value: 95.99339654021689
    - type: cos_sim_f1
      value: 90.45971329708354
    - type: cos_sim_precision
      value: 89.44281524926686
    - type: cos_sim_recall
      value: 91.5
    - type: dot_accuracy
      value: 99.81485148514851
    - type: dot_ap
      value: 95.990792367539
    - type: dot_f1
      value: 90.54187192118228
    - type: dot_precision
      value: 89.2233009708738
    - type: dot_recall
      value: 91.9
    - type: euclidean_accuracy
      value: 99.81386138613861
    - type: euclidean_ap
      value: 95.99403827746491
    - type: euclidean_f1
      value: 90.45971329708354
    - type: euclidean_precision
      value: 89.44281524926686
    - type: euclidean_recall
      value: 91.5
    - type: manhattan_accuracy
      value: 99.81485148514851
    - type: manhattan_ap
      value: 96.06741547889861
    - type: manhattan_f1
      value: 90.55666003976144
    - type: manhattan_precision
      value: 90.01976284584981
    - type: manhattan_recall
      value: 91.10000000000001
    - type: max_accuracy
      value: 99.81485148514851
    - type: max_ap
      value: 96.06741547889861
    - type: max_f1
      value: 90.55666003976144
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 79.0667992003181
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 49.57086425048946
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 53.929415255105894
    - type: mrr
      value: 54.93889790764791
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.050700527286658
    - type: cos_sim_spearman
      value: 31.46077656458546
    - type: dot_pearson
      value: 31.056448416258263
    - type: dot_spearman
      value: 31.435272601921042
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.23500000000000001
    - type: map_at_10
      value: 1.812
    - type: map_at_100
      value: 10.041
    - type: map_at_1000
      value: 24.095
    - type: map_at_3
      value: 0.643
    - type: map_at_5
      value: 1.0
    - type: mrr_at_1
      value: 86.0
    - type: mrr_at_10
      value: 92.0
    - type: mrr_at_100
      value: 92.0
    - type: mrr_at_1000
      value: 92.0
    - type: mrr_at_3
      value: 91.667
    - type: mrr_at_5
      value: 91.667
    - type: ndcg_at_1
      value: 79.0
    - type: ndcg_at_10
      value: 72.72
    - type: ndcg_at_100
      value: 55.82899999999999
    - type: ndcg_at_1000
      value: 50.72
    - type: ndcg_at_3
      value: 77.715
    - type: ndcg_at_5
      value: 75.036
    - type: precision_at_1
      value: 86.0
    - type: precision_at_10
      value: 77.60000000000001
    - type: precision_at_100
      value: 56.46
    - type: precision_at_1000
      value: 22.23
    - type: precision_at_3
      value: 82.667
    - type: precision_at_5
      value: 80.4
    - type: recall_at_1
      value: 0.23500000000000001
    - type: recall_at_10
      value: 2.046
    - type: recall_at_100
      value: 13.708
    - type: recall_at_1000
      value: 47.451
    - type: recall_at_3
      value: 0.6709999999999999
    - type: recall_at_5
      value: 1.078
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.252
    - type: map_at_10
      value: 7.958
    - type: map_at_100
      value: 12.293
    - type: map_at_1000
      value: 13.832
    - type: map_at_3
      value: 4.299
    - type: map_at_5
      value: 5.514
    - type: mrr_at_1
      value: 30.612000000000002
    - type: mrr_at_10
      value: 42.329
    - type: mrr_at_100
      value: 43.506
    - type: mrr_at_1000
      value: 43.506
    - type: mrr_at_3
      value: 38.775999999999996
    - type: mrr_at_5
      value: 39.592
    - type: ndcg_at_1
      value: 28.571
    - type: ndcg_at_10
      value: 20.301
    - type: ndcg_at_100
      value: 30.703999999999997
    - type: ndcg_at_1000
      value: 43.155
    - type: ndcg_at_3
      value: 22.738
    - type: ndcg_at_5
      value: 20.515
    - type: precision_at_1
      value: 30.612000000000002
    - type: precision_at_10
      value: 17.347
    - type: precision_at_100
      value: 6.327000000000001
    - type: precision_at_1000
      value: 1.443
    - type: precision_at_3
      value: 22.448999999999998
    - type: precision_at_5
      value: 19.184
    - type: recall_at_1
      value: 2.252
    - type: recall_at_10
      value: 13.206999999999999
    - type: recall_at_100
      value: 40.372
    - type: recall_at_1000
      value: 78.071
    - type: recall_at_3
      value: 5.189
    - type: recall_at_5
      value: 7.338
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 78.75399999999999
    - type: ap
      value: 19.666483622175363
    - type: f1
      value: 61.575187470329176
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 66.00452744765137
    - type: f1
      value: 66.18291586829227
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 51.308747717084316
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 87.81069321094355
    - type: cos_sim_ap
      value: 79.3576921453847
    - type: cos_sim_f1
      value: 71.75811286328685
    - type: cos_sim_precision
      value: 70.89878959567345
    - type: cos_sim_recall
      value: 72.63852242744063
    - type: dot_accuracy
      value: 87.79877212850927
    - type: dot_ap
      value: 79.35550320857683
    - type: dot_f1
      value: 71.78153446033811
    - type: dot_precision
      value: 70.76923076923077
    - type: dot_recall
      value: 72.82321899736148
    - type: euclidean_accuracy
      value: 87.80473266972642
    - type: euclidean_ap
      value: 79.35792655436586
    - type: euclidean_f1
      value: 71.75672148264161
    - type: euclidean_precision
      value: 70.99690082644628
    - type: euclidean_recall
      value: 72.53298153034301
    - type: manhattan_accuracy
      value: 87.76300888120642
    - type: manhattan_ap
      value: 79.33615959143606
    - type: manhattan_f1
      value: 71.73219978746015
    - type: manhattan_precision
      value: 72.23113964686998
    - type: manhattan_recall
      value: 71.2401055408971
    - type: max_accuracy
      value: 87.81069321094355
    - type: max_ap
      value: 79.35792655436586
    - type: max_f1
      value: 71.78153446033811
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.3778864439011
    - type: cos_sim_ap
      value: 86.79005637312795
    - type: cos_sim_f1
      value: 79.14617791685293
    - type: cos_sim_precision
      value: 76.66714780600462
    - type: cos_sim_recall
      value: 81.79088389282414
    - type: dot_accuracy
      value: 89.37206504443668
    - type: dot_ap
      value: 86.78770290102123
    - type: dot_f1
      value: 79.14741392159786
    - type: dot_precision
      value: 76.6897746967071
    - type: dot_recall
      value: 81.76778564829073
    - type: euclidean_accuracy
      value: 89.37594597741297
    - type: euclidean_ap
      value: 86.7900899669397
    - type: euclidean_f1
      value: 79.13920845898953
    - type: euclidean_precision
      value: 76.62028692956528
    - type: euclidean_recall
      value: 81.8293809670465
    - type: manhattan_accuracy
      value: 89.38758877634183
    - type: manhattan_ap
      value: 86.78862564973224
    - type: manhattan_f1
      value: 79.1130985653065
    - type: manhattan_precision
      value: 76.6592041597458
    - type: manhattan_recall
      value: 81.72928857406838
    - type: max_accuracy
      value: 89.38758877634183
    - type: max_ap
      value: 86.7900899669397
    - type: max_f1
      value: 79.14741392159786
  - task:
      type: STS
    dataset:
      name: MTEB AFQMC
      type: C-MTEB/AFQMC
      config: default
      split: validation
      revision: b44c3b011063adb25877c13823db83bb193913c4
    metrics:
    - type: cos_sim_pearson
      value: 50.01571015887356
    - type: cos_sim_spearman
      value: 58.47419994907958
    - type: euclidean_pearson
      value: 55.63582004345212
    - type: euclidean_spearman
      value: 58.47514484211099
    - type: manhattan_pearson
      value: 55.58487268871911
    - type: manhattan_spearman
      value: 58.411916843600075
  - task:
      type: STS
    dataset:
      name: MTEB ATEC
      type: C-MTEB/ATEC
      config: default
      split: test
      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
    metrics:
    - type: cos_sim_pearson
      value: 44.99231617937922
    - type: cos_sim_spearman
      value: 55.459227458516416
    - type: euclidean_pearson
      value: 52.98483376548224
    - type: euclidean_spearman
      value: 55.45938733128155
    - type: manhattan_pearson
      value: 52.946854805143964
    - type: manhattan_spearman
      value: 55.4272663113618
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (zh)
      type: mteb/amazon_reviews_multi
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 52.946000000000005
    - type: f1
      value: 49.299873931232725
  - task:
      type: STS
    dataset:
      name: MTEB BQ
      type: C-MTEB/BQ
      config: default
      split: test
      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
    metrics:
    - type: cos_sim_pearson
      value: 74.66979530294986
    - type: cos_sim_spearman
      value: 77.59153258548018
    - type: euclidean_pearson
      value: 76.5862988380262
    - type: euclidean_spearman
      value: 77.59094368703879
    - type: manhattan_pearson
      value: 76.6034419552102
    - type: manhattan_spearman
      value: 77.6000715948404
  - task:
      type: Clustering
    dataset:
      name: MTEB CLSClusteringP2P
      type: C-MTEB/CLSClusteringP2P
      config: default
      split: test
      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
    metrics:
    - type: v_measure
      value: 47.20931915009524
  - task:
      type: Clustering
    dataset:
      name: MTEB CLSClusteringS2S
      type: C-MTEB/CLSClusteringS2S
      config: default
      split: test
      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
    metrics:
    - type: v_measure
      value: 45.787353610995474
  - task:
      type: Reranking
    dataset:
      name: MTEB CMedQAv1
      type: C-MTEB/CMedQAv1-reranking
      config: default
      split: test
      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
    metrics:
    - type: map
      value: 86.37146026784607
    - type: mrr
      value: 88.52309523809524
  - task:
      type: Reranking
    dataset:
      name: MTEB CMedQAv2
      type: C-MTEB/CMedQAv2-reranking
      config: default
      split: test
      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
    metrics:
    - type: map
      value: 87.40699302584699
    - type: mrr
      value: 89.51591269841269
  - task:
      type: Retrieval
    dataset:
      name: MTEB CmedqaRetrieval
      type: C-MTEB/CmedqaRetrieval
      config: default
      split: dev
      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
    metrics:
    - type: map_at_1
      value: 24.465
    - type: map_at_10
      value: 36.689
    - type: map_at_100
      value: 38.605000000000004
    - type: map_at_1000
      value: 38.718
    - type: map_at_3
      value: 32.399
    - type: map_at_5
      value: 34.784
    - type: mrr_at_1
      value: 37.234
    - type: mrr_at_10
      value: 45.634
    - type: mrr_at_100
      value: 46.676
    - type: mrr_at_1000
      value: 46.717
    - type: mrr_at_3
      value: 42.94
    - type: mrr_at_5
      value: 44.457
    - type: ndcg_at_1
      value: 37.234
    - type: ndcg_at_10
      value: 43.469
    - type: ndcg_at_100
      value: 51.048
    - type: ndcg_at_1000
      value: 52.925999999999995
    - type: ndcg_at_3
      value: 37.942
    - type: ndcg_at_5
      value: 40.253
    - type: precision_at_1
      value: 37.234
    - type: precision_at_10
      value: 9.745
    - type: precision_at_100
      value: 1.5879999999999999
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 21.505
    - type: precision_at_5
      value: 15.729000000000001
    - type: recall_at_1
      value: 24.465
    - type: recall_at_10
      value: 54.559999999999995
    - type: recall_at_100
      value: 85.97200000000001
    - type: recall_at_1000
      value: 98.32499999999999
    - type: recall_at_3
      value: 38.047
    - type: recall_at_5
      value: 45.08
  - task:
      type: PairClassification
    dataset:
      name: MTEB Cmnli
      type: C-MTEB/CMNLI
      config: default
      split: validation
      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
    metrics:
    - type: cos_sim_accuracy
      value: 84.50992182802165
    - type: cos_sim_ap
      value: 91.81488661281966
    - type: cos_sim_f1
      value: 85.46855802524294
    - type: cos_sim_precision
      value: 81.82207014542344
    - type: cos_sim_recall
      value: 89.4552256254384
    - type: dot_accuracy
      value: 84.50992182802165
    - type: dot_ap
      value: 91.80547588176556
    - type: dot_f1
      value: 85.46492111446794
    - type: dot_precision
      value: 81.95278969957081
    - type: dot_recall
      value: 89.29155950432546
    - type: euclidean_accuracy
      value: 84.49789536981359
    - type: euclidean_ap
      value: 91.81495039620808
    - type: euclidean_f1
      value: 85.46817317373308
    - type: euclidean_precision
      value: 81.93908193908193
    - type: euclidean_recall
      value: 89.31494037877017
    - type: manhattan_accuracy
      value: 84.46181599518941
    - type: manhattan_ap
      value: 91.85400573633447
    - type: manhattan_f1
      value: 85.54283809312146
    - type: manhattan_precision
      value: 81.51207115628971
    - type: manhattan_recall
      value: 89.99298573766659
    - type: max_accuracy
      value: 84.50992182802165
    - type: max_ap
      value: 91.85400573633447
    - type: max_f1
      value: 85.54283809312146
  - task:
      type: Retrieval
    dataset:
      name: MTEB CovidRetrieval
      type: C-MTEB/CovidRetrieval
      config: default
      split: dev
      revision: 1271c7809071a13532e05f25fb53511ffce77117
    metrics:
    - type: map_at_1
      value: 68.072
    - type: map_at_10
      value: 76.82900000000001
    - type: map_at_100
      value: 77.146
    - type: map_at_1000
      value: 77.14999999999999
    - type: map_at_3
      value: 74.939
    - type: map_at_5
      value: 76.009
    - type: mrr_at_1
      value: 68.282
    - type: mrr_at_10
      value: 76.818
    - type: mrr_at_100
      value: 77.13600000000001
    - type: mrr_at_1000
      value: 77.14
    - type: mrr_at_3
      value: 74.956
    - type: mrr_at_5
      value: 76.047
    - type: ndcg_at_1
      value: 68.282
    - type: ndcg_at_10
      value: 80.87299999999999
    - type: ndcg_at_100
      value: 82.191
    - type: ndcg_at_1000
      value: 82.286
    - type: ndcg_at_3
      value: 77.065
    - type: ndcg_at_5
      value: 78.965
    - type: precision_at_1
      value: 68.282
    - type: precision_at_10
      value: 9.452
    - type: precision_at_100
      value: 1.002
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 27.889000000000003
    - type: precision_at_5
      value: 17.682000000000002
    - type: recall_at_1
      value: 68.072
    - type: recall_at_10
      value: 93.467
    - type: recall_at_100
      value: 99.157
    - type: recall_at_1000
      value: 99.895
    - type: recall_at_3
      value: 83.14
    - type: recall_at_5
      value: 87.67099999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB DuRetrieval
      type: C-MTEB/DuRetrieval
      config: default
      split: dev
      revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
    metrics:
    - type: map_at_1
      value: 26.107999999999997
    - type: map_at_10
      value: 78.384
    - type: map_at_100
      value: 81.341
    - type: map_at_1000
      value: 81.384
    - type: map_at_3
      value: 54.462999999999994
    - type: map_at_5
      value: 68.607
    - type: mrr_at_1
      value: 88.94999999999999
    - type: mrr_at_10
      value: 92.31
    - type: mrr_at_100
      value: 92.379
    - type: mrr_at_1000
      value: 92.38300000000001
    - type: mrr_at_3
      value: 91.85799999999999
    - type: mrr_at_5
      value: 92.146
    - type: ndcg_at_1
      value: 88.94999999999999
    - type: ndcg_at_10
      value: 86.00999999999999
    - type: ndcg_at_100
      value: 89.121
    - type: ndcg_at_1000
      value: 89.534
    - type: ndcg_at_3
      value: 84.69200000000001
    - type: ndcg_at_5
      value: 83.678
    - type: precision_at_1
      value: 88.94999999999999
    - type: precision_at_10
      value: 41.065000000000005
    - type: precision_at_100
      value: 4.781
    - type: precision_at_1000
      value: 0.488
    - type: precision_at_3
      value: 75.75
    - type: precision_at_5
      value: 63.93
    - type: recall_at_1
      value: 26.107999999999997
    - type: recall_at_10
      value: 87.349
    - type: recall_at_100
      value: 97.14699999999999
    - type: recall_at_1000
      value: 99.287
    - type: recall_at_3
      value: 56.601
    - type: recall_at_5
      value: 73.381
  - task:
      type: Retrieval
    dataset:
      name: MTEB EcomRetrieval
      type: C-MTEB/EcomRetrieval
      config: default
      split: dev
      revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
    metrics:
    - type: map_at_1
      value: 50.7
    - type: map_at_10
      value: 61.312999999999995
    - type: map_at_100
      value: 61.88399999999999
    - type: map_at_1000
      value: 61.9
    - type: map_at_3
      value: 58.983
    - type: map_at_5
      value: 60.238
    - type: mrr_at_1
      value: 50.7
    - type: mrr_at_10
      value: 61.312999999999995
    - type: mrr_at_100
      value: 61.88399999999999
    - type: mrr_at_1000
      value: 61.9
    - type: mrr_at_3
      value: 58.983
    - type: mrr_at_5
      value: 60.238
    - type: ndcg_at_1
      value: 50.7
    - type: ndcg_at_10
      value: 66.458
    - type: ndcg_at_100
      value: 69.098
    - type: ndcg_at_1000
      value: 69.539
    - type: ndcg_at_3
      value: 61.637
    - type: ndcg_at_5
      value: 63.92099999999999
    - type: precision_at_1
      value: 50.7
    - type: precision_at_10
      value: 8.260000000000002
    - type: precision_at_100
      value: 0.946
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 23.1
    - type: precision_at_5
      value: 14.979999999999999
    - type: recall_at_1
      value: 50.7
    - type: recall_at_10
      value: 82.6
    - type: recall_at_100
      value: 94.6
    - type: recall_at_1000
      value: 98.1
    - type: recall_at_3
      value: 69.3
    - type: recall_at_5
      value: 74.9
  - task:
      type: Classification
    dataset:
      name: MTEB IFlyTek
      type: C-MTEB/IFlyTek-classification
      config: default
      split: validation
      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
    metrics:
    - type: accuracy
      value: 53.76683339746056
    - type: f1
      value: 40.026100192683714
  - task:
      type: Classification
    dataset:
      name: MTEB JDReview
      type: C-MTEB/JDReview-classification
      config: default
      split: test
      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
    metrics:
    - type: accuracy
      value: 88.19887429643526
    - type: ap
      value: 59.02998120976959
    - type: f1
      value: 83.3659125921227
  - task:
      type: STS
    dataset:
      name: MTEB LCQMC
      type: C-MTEB/LCQMC
      config: default
      split: test
      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
    metrics:
    - type: cos_sim_pearson
      value: 72.53955204856854
    - type: cos_sim_spearman
      value: 76.28996886746215
    - type: euclidean_pearson
      value: 75.31184890026394
    - type: euclidean_spearman
      value: 76.28984471300522
    - type: manhattan_pearson
      value: 75.36930361638623
    - type: manhattan_spearman
      value: 76.34021995551348
  - task:
      type: Reranking
    dataset:
      name: MTEB MMarcoReranking
      type: C-MTEB/Mmarco-reranking
      config: default
      split: dev
      revision: None
    metrics:
    - type: map
      value: 23.63666512532725
    - type: mrr
      value: 22.49642857142857
  - task:
      type: Retrieval
    dataset:
      name: MTEB MMarcoRetrieval
      type: C-MTEB/MMarcoRetrieval
      config: default
      split: dev
      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
    metrics:
    - type: map_at_1
      value: 60.645
    - type: map_at_10
      value: 69.733
    - type: map_at_100
      value: 70.11699999999999
    - type: map_at_1000
      value: 70.135
    - type: map_at_3
      value: 67.585
    - type: map_at_5
      value: 68.904
    - type: mrr_at_1
      value: 62.765
    - type: mrr_at_10
      value: 70.428
    - type: mrr_at_100
      value: 70.77
    - type: mrr_at_1000
      value: 70.785
    - type: mrr_at_3
      value: 68.498
    - type: mrr_at_5
      value: 69.69
    - type: ndcg_at_1
      value: 62.765
    - type: ndcg_at_10
      value: 73.83
    - type: ndcg_at_100
      value: 75.593
    - type: ndcg_at_1000
      value: 76.05199999999999
    - type: ndcg_at_3
      value: 69.66499999999999
    - type: ndcg_at_5
      value: 71.929
    - type: precision_at_1
      value: 62.765
    - type: precision_at_10
      value: 9.117
    - type: precision_at_100
      value: 1.0
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 26.323
    - type: precision_at_5
      value: 16.971
    - type: recall_at_1
      value: 60.645
    - type: recall_at_10
      value: 85.907
    - type: recall_at_100
      value: 93.947
    - type: recall_at_1000
      value: 97.531
    - type: recall_at_3
      value: 74.773
    - type: recall_at_5
      value: 80.16799999999999
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (zh-CN)
      type: mteb/amazon_massive_intent
      config: zh-CN
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 76.25084061869536
    - type: f1
      value: 73.65064492827022
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (zh-CN)
      type: mteb/amazon_massive_scenario
      config: zh-CN
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 77.2595830531271
    - type: f1
      value: 77.15217273559321
  - task:
      type: Retrieval
    dataset:
      name: MTEB MedicalRetrieval
      type: C-MTEB/MedicalRetrieval
      config: default
      split: dev
      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
    metrics:
    - type: map_at_1
      value: 52.400000000000006
    - type: map_at_10
      value: 58.367000000000004
    - type: map_at_100
      value: 58.913000000000004
    - type: map_at_1000
      value: 58.961
    - type: map_at_3
      value: 56.882999999999996
    - type: map_at_5
      value: 57.743
    - type: mrr_at_1
      value: 52.400000000000006
    - type: mrr_at_10
      value: 58.367000000000004
    - type: mrr_at_100
      value: 58.913000000000004
    - type: mrr_at_1000
      value: 58.961
    - type: mrr_at_3
      value: 56.882999999999996
    - type: mrr_at_5
      value: 57.743
    - type: ndcg_at_1
      value: 52.400000000000006
    - type: ndcg_at_10
      value: 61.329
    - type: ndcg_at_100
      value: 64.264
    - type: ndcg_at_1000
      value: 65.669
    - type: ndcg_at_3
      value: 58.256
    - type: ndcg_at_5
      value: 59.813
    - type: precision_at_1
      value: 52.400000000000006
    - type: precision_at_10
      value: 7.07
    - type: precision_at_100
      value: 0.851
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 20.732999999999997
    - type: precision_at_5
      value: 13.200000000000001
    - type: recall_at_1
      value: 52.400000000000006
    - type: recall_at_10
      value: 70.7
    - type: recall_at_100
      value: 85.1
    - type: recall_at_1000
      value: 96.39999999999999
    - type: recall_at_3
      value: 62.2
    - type: recall_at_5
      value: 66.0
  - task:
      type: Classification
    dataset:
      name: MTEB MultilingualSentiment
      type: C-MTEB/MultilingualSentiment-classification
      config: default
      split: validation
      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
    metrics:
    - type: accuracy
      value: 77.42333333333333
    - type: f1
      value: 77.24849313989888
  - task:
      type: PairClassification
    dataset:
      name: MTEB Ocnli
      type: C-MTEB/OCNLI
      config: default
      split: validation
      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
    metrics:
    - type: cos_sim_accuracy
      value: 80.12994044396319
    - type: cos_sim_ap
      value: 85.21793541189636
    - type: cos_sim_f1
      value: 81.91489361702128
    - type: cos_sim_precision
      value: 75.55753791257806
    - type: cos_sim_recall
      value: 89.44033790918691
    - type: dot_accuracy
      value: 80.12994044396319
    - type: dot_ap
      value: 85.22568672443236
    - type: dot_f1
      value: 81.91489361702128
    - type: dot_precision
      value: 75.55753791257806
    - type: dot_recall
      value: 89.44033790918691
    - type: euclidean_accuracy
      value: 80.12994044396319
    - type: euclidean_ap
      value: 85.21643342357407
    - type: euclidean_f1
      value: 81.8830242510699
    - type: euclidean_precision
      value: 74.48096885813149
    - type: euclidean_recall
      value: 90.91869060190075
    - type: manhattan_accuracy
      value: 80.5630752571738
    - type: manhattan_ap
      value: 85.27682975032671
    - type: manhattan_f1
      value: 82.03883495145631
    - type: manhattan_precision
      value: 75.92093441150045
    - type: manhattan_recall
      value: 89.22914466737065
    - type: max_accuracy
      value: 80.5630752571738
    - type: max_ap
      value: 85.27682975032671
    - type: max_f1
      value: 82.03883495145631
  - task:
      type: Classification
    dataset:
      name: MTEB OnlineShopping
      type: C-MTEB/OnlineShopping-classification
      config: default
      split: test
      revision: e610f2ebd179a8fda30ae534c3878750a96db120
    metrics:
    - type: accuracy
      value: 94.47999999999999
    - type: ap
      value: 92.81177660844013
    - type: f1
      value: 94.47045470502114
  - task:
      type: STS
    dataset:
      name: MTEB PAWSX
      type: C-MTEB/PAWSX
      config: default
      split: test
      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
    metrics:
    - type: cos_sim_pearson
      value: 46.13154582182421
    - type: cos_sim_spearman
      value: 50.21718723757444
    - type: euclidean_pearson
      value: 49.41535243569054
    - type: euclidean_spearman
      value: 50.21831909208907
    - type: manhattan_pearson
      value: 49.50756578601167
    - type: manhattan_spearman
      value: 50.229118655684566
  - task:
      type: STS
    dataset:
      name: MTEB QBQTC
      type: C-MTEB/QBQTC
      config: default
      split: test
      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
    metrics:
    - type: cos_sim_pearson
      value: 30.787794367421956
    - type: cos_sim_spearman
      value: 31.81774306987836
    - type: euclidean_pearson
      value: 29.809436608089495
    - type: euclidean_spearman
      value: 31.817379098812165
    - type: manhattan_pearson
      value: 30.377027186607787
    - type: manhattan_spearman
      value: 32.42286865176827
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh)
      type: mteb/sts22-crosslingual-sts
      config: zh
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 61.29839896616376
    - type: cos_sim_spearman
      value: 67.36328213286453
    - type: euclidean_pearson
      value: 64.33899267794008
    - type: euclidean_spearman
      value: 67.36552580196211
    - type: manhattan_pearson
      value: 65.20010308796022
    - type: manhattan_spearman
      value: 67.50982972902
  - task:
      type: STS
    dataset:
      name: MTEB STSB
      type: C-MTEB/STSB
      config: default
      split: test
      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
    metrics:
    - type: cos_sim_pearson
      value: 81.23278996774297
    - type: cos_sim_spearman
      value: 81.369375466486
    - type: euclidean_pearson
      value: 79.91030863727944
    - type: euclidean_spearman
      value: 81.36824495466793
    - type: manhattan_pearson
      value: 79.88047052896854
    - type: manhattan_spearman
      value: 81.3369604332008
  - task:
      type: Reranking
    dataset:
      name: MTEB T2Reranking
      type: C-MTEB/T2Reranking
      config: default
      split: dev
      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
    metrics:
    - type: map
      value: 68.109205221286
    - type: mrr
      value: 78.40703619520477
  - task:
      type: Retrieval
    dataset:
      name: MTEB T2Retrieval
      type: C-MTEB/T2Retrieval
      config: default
      split: dev
      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
    metrics:
    - type: map_at_1
      value: 26.704
    - type: map_at_10
      value: 75.739
    - type: map_at_100
      value: 79.606
    - type: map_at_1000
      value: 79.666
    - type: map_at_3
      value: 52.803
    - type: map_at_5
      value: 65.068
    - type: mrr_at_1
      value: 88.48899999999999
    - type: mrr_at_10
      value: 91.377
    - type: mrr_at_100
      value: 91.474
    - type: mrr_at_1000
      value: 91.47800000000001
    - type: mrr_at_3
      value: 90.846
    - type: mrr_at_5
      value: 91.18
    - type: ndcg_at_1
      value: 88.48899999999999
    - type: ndcg_at_10
      value: 83.581
    - type: ndcg_at_100
      value: 87.502
    - type: ndcg_at_1000
      value: 88.1
    - type: ndcg_at_3
      value: 84.433
    - type: ndcg_at_5
      value: 83.174
    - type: precision_at_1
      value: 88.48899999999999
    - type: precision_at_10
      value: 41.857
    - type: precision_at_100
      value: 5.039
    - type: precision_at_1000
      value: 0.517
    - type: precision_at_3
      value: 73.938
    - type: precision_at_5
      value: 62.163000000000004
    - type: recall_at_1
      value: 26.704
    - type: recall_at_10
      value: 83.092
    - type: recall_at_100
      value: 95.659
    - type: recall_at_1000
      value: 98.779
    - type: recall_at_3
      value: 54.678000000000004
    - type: recall_at_5
      value: 68.843
  - task:
      type: Classification
    dataset:
      name: MTEB TNews
      type: C-MTEB/TNews-classification
      config: default
      split: validation
      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
    metrics:
    - type: accuracy
      value: 51.235
    - type: f1
      value: 48.14373844331604
  - task:
      type: Clustering
    dataset:
      name: MTEB ThuNewsClusteringP2P
      type: C-MTEB/ThuNewsClusteringP2P
      config: default
      split: test
      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
    metrics:
    - type: v_measure
      value: 87.42930040493792
  - task:
      type: Clustering
    dataset:
      name: MTEB ThuNewsClusteringS2S
      type: C-MTEB/ThuNewsClusteringS2S
      config: default
      split: test
      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
    metrics:
    - type: v_measure
      value: 87.90254094650042
  - task:
      type: Retrieval
    dataset:
      name: MTEB VideoRetrieval
      type: C-MTEB/VideoRetrieval
      config: default
      split: dev
      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
    metrics:
    - type: map_at_1
      value: 54.900000000000006
    - type: map_at_10
      value: 64.92
    - type: map_at_100
      value: 65.424
    - type: map_at_1000
      value: 65.43900000000001
    - type: map_at_3
      value: 63.132999999999996
    - type: map_at_5
      value: 64.208
    - type: mrr_at_1
      value: 54.900000000000006
    - type: mrr_at_10
      value: 64.92
    - type: mrr_at_100
      value: 65.424
    - type: mrr_at_1000
      value: 65.43900000000001
    - type: mrr_at_3
      value: 63.132999999999996
    - type: mrr_at_5
      value: 64.208
    - type: ndcg_at_1
      value: 54.900000000000006
    - type: ndcg_at_10
      value: 69.41199999999999
    - type: ndcg_at_100
      value: 71.824
    - type: ndcg_at_1000
      value: 72.301
    - type: ndcg_at_3
      value: 65.79700000000001
    - type: ndcg_at_5
      value: 67.713
    - type: precision_at_1
      value: 54.900000000000006
    - type: precision_at_10
      value: 8.33
    - type: precision_at_100
      value: 0.9450000000000001
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 24.5
    - type: precision_at_5
      value: 15.620000000000001
    - type: recall_at_1
      value: 54.900000000000006
    - type: recall_at_10
      value: 83.3
    - type: recall_at_100
      value: 94.5
    - type: recall_at_1000
      value: 98.4
    - type: recall_at_3
      value: 73.5
    - type: recall_at_5
      value: 78.10000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB Waimai
      type: C-MTEB/waimai-classification
      config: default
      split: test
      revision: 339287def212450dcaa9df8c22bf93e9980c7023
    metrics:
    - type: accuracy
      value: 88.63
    - type: ap
      value: 73.78658340897097
    - type: f1
      value: 87.16764294033919
---

# agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF
This model was converted to GGUF format from [`Alibaba-NLP/gte-Qwen1.5-7B-instruct`](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) for more details on the model.
## Use with llama.cpp
Install llama.cpp through brew.
```bash
brew install ggerganov/ggerganov/llama.cpp
```
Invoke the llama.cpp server or the CLI.
CLI:
```bash
llama-cli --hf-repo agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF --model gte-qwen1.5-7b-instruct-q5_k_m.gguf -p "The meaning to life and the universe is"
```
Server:
```bash
llama-server --hf-repo agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF --model gte-qwen1.5-7b-instruct-q5_k_m.gguf -c 2048
```
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
```
git clone https://github.com/ggerganov/llama.cpp && \
cd llama.cpp && \
make && \
./main -m gte-qwen1.5-7b-instruct-q5_k_m.gguf -n 128
```
