transformers pytorch safetensors mixtral text-generation mteb conversational custom_code dataset:GritLM/tulu2 arxiv:2402.09906 license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
datasets:
- GritLM/tulu2
license: apache-2.0
pipeline_tag: text-generation
tags:
- mteb
inference: true
model-index:
- name: GritLM-8x7B
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 80.47761194029852
    - type: ap
      value: 44.38751347932197
    - type: f1
      value: 74.33580162208256
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 96.32155000000002
    - type: ap
      value: 94.8026654593679
    - type: f1
      value: 96.3209869463974
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 57.18400000000001
    - type: f1
      value: 55.945160479400954
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 34.353
    - type: map_at_10
      value: 50.773
    - type: map_at_100
      value: 51.515
    - type: map_at_1000
      value: 51.517
    - type: map_at_3
      value: 46.29
    - type: map_at_5
      value: 48.914
    - type: mrr_at_1
      value: 35.135
    - type: mrr_at_10
      value: 51.036
    - type: mrr_at_100
      value: 51.785000000000004
    - type: mrr_at_1000
      value: 51.787000000000006
    - type: mrr_at_3
      value: 46.562
    - type: mrr_at_5
      value: 49.183
    - type: ndcg_at_1
      value: 34.353
    - type: ndcg_at_10
      value: 59.492
    - type: ndcg_at_100
      value: 62.395999999999994
    - type: ndcg_at_1000
      value: 62.44499999999999
    - type: ndcg_at_3
      value: 50.217
    - type: ndcg_at_5
      value: 54.98499999999999
    - type: precision_at_1
      value: 34.353
    - type: precision_at_10
      value: 8.72
    - type: precision_at_100
      value: 0.993
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 20.531
    - type: precision_at_5
      value: 14.651
    - type: recall_at_1
      value: 34.353
    - type: recall_at_10
      value: 87.198
    - type: recall_at_100
      value: 99.289
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 61.592999999999996
    - type: recall_at_5
      value: 73.257
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 50.720077577006286
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 48.01021098734129
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 65.59672236627206
    - type: mrr
      value: 78.01191575429802
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 89.52452252271826
    - type: cos_sim_spearman
      value: 87.34415887061094
    - type: euclidean_pearson
      value: 87.46187616533932
    - type: euclidean_spearman
      value: 85.44712769366146
    - type: manhattan_pearson
      value: 87.56696679505373
    - type: manhattan_spearman
      value: 86.01581535039067
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 87.4577922077922
    - type: f1
      value: 87.38432712848123
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 41.41290357360428
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 38.67213605633667
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 37.545
    - type: map_at_10
      value: 50.015
    - type: map_at_100
      value: 51.763999999999996
    - type: map_at_1000
      value: 51.870000000000005
    - type: map_at_3
      value: 46.129999999999995
    - type: map_at_5
      value: 48.473
    - type: mrr_at_1
      value: 47.638999999999996
    - type: mrr_at_10
      value: 56.913000000000004
    - type: mrr_at_100
      value: 57.619
    - type: mrr_at_1000
      value: 57.648999999999994
    - type: mrr_at_3
      value: 54.435
    - type: mrr_at_5
      value: 56.059000000000005
    - type: ndcg_at_1
      value: 47.638999999999996
    - type: ndcg_at_10
      value: 56.664
    - type: ndcg_at_100
      value: 62.089000000000006
    - type: ndcg_at_1000
      value: 63.415
    - type: ndcg_at_3
      value: 51.842999999999996
    - type: ndcg_at_5
      value: 54.30199999999999
    - type: precision_at_1
      value: 47.638999999999996
    - type: precision_at_10
      value: 10.886999999999999
    - type: precision_at_100
      value: 1.722
    - type: precision_at_1000
      value: 0.212
    - type: precision_at_3
      value: 25.179000000000002
    - type: precision_at_5
      value: 18.226
    - type: recall_at_1
      value: 37.545
    - type: recall_at_10
      value: 68.118
    - type: recall_at_100
      value: 90.381
    - type: recall_at_1000
      value: 98.556
    - type: recall_at_3
      value: 53.319
    - type: recall_at_5
      value: 60.574
    - type: map_at_1
      value: 37.066
    - type: map_at_10
      value: 49.464000000000006
    - type: map_at_100
      value: 50.79900000000001
    - type: map_at_1000
      value: 50.928
    - type: map_at_3
      value: 46.133
    - type: map_at_5
      value: 47.941
    - type: mrr_at_1
      value: 48.025
    - type: mrr_at_10
      value: 56.16100000000001
    - type: mrr_at_100
      value: 56.725
    - type: mrr_at_1000
      value: 56.757000000000005
    - type: mrr_at_3
      value: 54.31
    - type: mrr_at_5
      value: 55.285
    - type: ndcg_at_1
      value: 48.025
    - type: ndcg_at_10
      value: 55.467
    - type: ndcg_at_100
      value: 59.391000000000005
    - type: ndcg_at_1000
      value: 61.086
    - type: ndcg_at_3
      value: 51.733
    - type: ndcg_at_5
      value: 53.223
    - type: precision_at_1
      value: 48.025
    - type: precision_at_10
      value: 10.656
    - type: precision_at_100
      value: 1.6070000000000002
    - type: precision_at_1000
      value: 0.20600000000000002
    - type: precision_at_3
      value: 25.499
    - type: precision_at_5
      value: 17.771
    - type: recall_at_1
      value: 37.066
    - type: recall_at_10
      value: 65.062
    - type: recall_at_100
      value: 81.662
    - type: recall_at_1000
      value: 91.913
    - type: recall_at_3
      value: 52.734
    - type: recall_at_5
      value: 57.696999999999996
    - type: map_at_1
      value: 46.099000000000004
    - type: map_at_10
      value: 59.721999999999994
    - type: map_at_100
      value: 60.675000000000004
    - type: map_at_1000
      value: 60.708
    - type: map_at_3
      value: 55.852000000000004
    - type: map_at_5
      value: 58.426
    - type: mrr_at_1
      value: 53.417
    - type: mrr_at_10
      value: 63.597
    - type: mrr_at_100
      value: 64.12299999999999
    - type: mrr_at_1000
      value: 64.13799999999999
    - type: mrr_at_3
      value: 61.149
    - type: mrr_at_5
      value: 62.800999999999995
    - type: ndcg_at_1
      value: 53.417
    - type: ndcg_at_10
      value: 65.90899999999999
    - type: ndcg_at_100
      value: 69.312
    - type: ndcg_at_1000
      value: 69.89
    - type: ndcg_at_3
      value: 60.089999999999996
    - type: ndcg_at_5
      value: 63.575
    - type: precision_at_1
      value: 53.417
    - type: precision_at_10
      value: 10.533
    - type: precision_at_100
      value: 1.313
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 26.667
    - type: precision_at_5
      value: 18.671
    - type: recall_at_1
      value: 46.099000000000004
    - type: recall_at_10
      value: 80.134
    - type: recall_at_100
      value: 94.536
    - type: recall_at_1000
      value: 98.543
    - type: recall_at_3
      value: 65.026
    - type: recall_at_5
      value: 73.462
    - type: map_at_1
      value: 28.261999999999997
    - type: map_at_10
      value: 38.012
    - type: map_at_100
      value: 39.104
    - type: map_at_1000
      value: 39.177
    - type: map_at_3
      value: 35.068
    - type: map_at_5
      value: 36.620000000000005
    - type: mrr_at_1
      value: 30.847
    - type: mrr_at_10
      value: 40.251999999999995
    - type: mrr_at_100
      value: 41.174
    - type: mrr_at_1000
      value: 41.227999999999994
    - type: mrr_at_3
      value: 37.74
    - type: mrr_at_5
      value: 38.972
    - type: ndcg_at_1
      value: 30.847
    - type: ndcg_at_10
      value: 43.513000000000005
    - type: ndcg_at_100
      value: 48.771
    - type: ndcg_at_1000
      value: 50.501
    - type: ndcg_at_3
      value: 37.861
    - type: ndcg_at_5
      value: 40.366
    - type: precision_at_1
      value: 30.847
    - type: precision_at_10
      value: 6.7909999999999995
    - type: precision_at_100
      value: 0.992
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 16.234
    - type: precision_at_5
      value: 11.254
    - type: recall_at_1
      value: 28.261999999999997
    - type: recall_at_10
      value: 58.292
    - type: recall_at_100
      value: 82.24000000000001
    - type: recall_at_1000
      value: 95.042
    - type: recall_at_3
      value: 42.955
    - type: recall_at_5
      value: 48.973
    - type: map_at_1
      value: 18.281
    - type: map_at_10
      value: 27.687
    - type: map_at_100
      value: 28.9
    - type: map_at_1000
      value: 29.019000000000002
    - type: map_at_3
      value: 24.773
    - type: map_at_5
      value: 26.180999999999997
    - type: mrr_at_1
      value: 23.01
    - type: mrr_at_10
      value: 32.225
    - type: mrr_at_100
      value: 33.054
    - type: mrr_at_1000
      value: 33.119
    - type: mrr_at_3
      value: 29.353
    - type: mrr_at_5
      value: 30.846
    - type: ndcg_at_1
      value: 23.01
    - type: ndcg_at_10
      value: 33.422000000000004
    - type: ndcg_at_100
      value: 39.108
    - type: ndcg_at_1000
      value: 41.699999999999996
    - type: ndcg_at_3
      value: 28.083999999999996
    - type: ndcg_at_5
      value: 30.164
    - type: precision_at_1
      value: 23.01
    - type: precision_at_10
      value: 6.493
    - type: precision_at_100
      value: 1.077
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 13.930000000000001
    - type: precision_at_5
      value: 10.075000000000001
    - type: recall_at_1
      value: 18.281
    - type: recall_at_10
      value: 46.318
    - type: recall_at_100
      value: 71.327
    - type: recall_at_1000
      value: 89.716
    - type: recall_at_3
      value: 31.517
    - type: recall_at_5
      value: 36.821
    - type: map_at_1
      value: 36.575
    - type: map_at_10
      value: 49.235
    - type: map_at_100
      value: 50.723
    - type: map_at_1000
      value: 50.809000000000005
    - type: map_at_3
      value: 45.696999999999996
    - type: map_at_5
      value: 47.588
    - type: mrr_at_1
      value: 45.525
    - type: mrr_at_10
      value: 55.334
    - type: mrr_at_100
      value: 56.092
    - type: mrr_at_1000
      value: 56.118
    - type: mrr_at_3
      value: 53.032000000000004
    - type: mrr_at_5
      value: 54.19199999999999
    - type: ndcg_at_1
      value: 45.525
    - type: ndcg_at_10
      value: 55.542
    - type: ndcg_at_100
      value: 60.879000000000005
    - type: ndcg_at_1000
      value: 62.224999999999994
    - type: ndcg_at_3
      value: 50.688
    - type: ndcg_at_5
      value: 52.76499999999999
    - type: precision_at_1
      value: 45.525
    - type: precision_at_10
      value: 10.067
    - type: precision_at_100
      value: 1.471
    - type: precision_at_1000
      value: 0.173
    - type: precision_at_3
      value: 24.382
    - type: precision_at_5
      value: 16.919999999999998
    - type: recall_at_1
      value: 36.575
    - type: recall_at_10
      value: 67.903
    - type: recall_at_100
      value: 89.464
    - type: recall_at_1000
      value: 97.799
    - type: recall_at_3
      value: 53.493
    - type: recall_at_5
      value: 59.372
    - type: map_at_1
      value: 29.099000000000004
    - type: map_at_10
      value: 42.147
    - type: map_at_100
      value: 43.522
    - type: map_at_1000
      value: 43.624
    - type: map_at_3
      value: 38.104
    - type: map_at_5
      value: 40.435
    - type: mrr_at_1
      value: 36.416
    - type: mrr_at_10
      value: 47.922
    - type: mrr_at_100
      value: 48.664
    - type: mrr_at_1000
      value: 48.709
    - type: mrr_at_3
      value: 44.977000000000004
    - type: mrr_at_5
      value: 46.838
    - type: ndcg_at_1
      value: 36.416
    - type: ndcg_at_10
      value: 49.307
    - type: ndcg_at_100
      value: 54.332
    - type: ndcg_at_1000
      value: 56.145
    - type: ndcg_at_3
      value: 42.994
    - type: ndcg_at_5
      value: 46.119
    - type: precision_at_1
      value: 36.416
    - type: precision_at_10
      value: 9.452
    - type: precision_at_100
      value: 1.4080000000000001
    - type: precision_at_1000
      value: 0.172
    - type: precision_at_3
      value: 21.081
    - type: precision_at_5
      value: 15.501999999999999
    - type: recall_at_1
      value: 29.099000000000004
    - type: recall_at_10
      value: 64.485
    - type: recall_at_100
      value: 84.753
    - type: recall_at_1000
      value: 96.875
    - type: recall_at_3
      value: 47.06
    - type: recall_at_5
      value: 55.077
    - type: map_at_1
      value: 30.69458333333333
    - type: map_at_10
      value: 41.65291666666666
    - type: map_at_100
      value: 42.95775
    - type: map_at_1000
      value: 43.06258333333333
    - type: map_at_3
      value: 38.335750000000004
    - type: map_at_5
      value: 40.20941666666666
    - type: mrr_at_1
      value: 37.013000000000005
    - type: mrr_at_10
      value: 46.30600000000001
    - type: mrr_at_100
      value: 47.094666666666676
    - type: mrr_at_1000
      value: 47.139583333333334
    - type: mrr_at_3
      value: 43.805749999999996
    - type: mrr_at_5
      value: 45.22366666666666
    - type: ndcg_at_1
      value: 37.013000000000005
    - type: ndcg_at_10
      value: 47.63491666666667
    - type: ndcg_at_100
      value: 52.71083333333334
    - type: ndcg_at_1000
      value: 54.493583333333326
    - type: ndcg_at_3
      value: 42.43616666666666
    - type: ndcg_at_5
      value: 44.87583333333334
    - type: precision_at_1
      value: 37.013000000000005
    - type: precision_at_10
      value: 8.481583333333333
    - type: precision_at_100
      value: 1.3073333333333337
    - type: precision_at_1000
      value: 0.16341666666666668
    - type: precision_at_3
      value: 19.811833333333333
    - type: precision_at_5
      value: 14.07691666666667
    - type: recall_at_1
      value: 30.69458333333333
    - type: recall_at_10
      value: 60.462083333333325
    - type: recall_at_100
      value: 82.42325000000001
    - type: recall_at_1000
      value: 94.53291666666667
    - type: recall_at_3
      value: 45.7405
    - type: recall_at_5
      value: 52.14025
    - type: map_at_1
      value: 27.833000000000002
    - type: map_at_10
      value: 36.55
    - type: map_at_100
      value: 37.524
    - type: map_at_1000
      value: 37.613
    - type: map_at_3
      value: 33.552
    - type: map_at_5
      value: 35.173
    - type: mrr_at_1
      value: 31.135
    - type: mrr_at_10
      value: 39.637
    - type: mrr_at_100
      value: 40.361000000000004
    - type: mrr_at_1000
      value: 40.422000000000004
    - type: mrr_at_3
      value: 36.887
    - type: mrr_at_5
      value: 38.428000000000004
    - type: ndcg_at_1
      value: 31.135
    - type: ndcg_at_10
      value: 42.007
    - type: ndcg_at_100
      value: 46.531
    - type: ndcg_at_1000
      value: 48.643
    - type: ndcg_at_3
      value: 36.437999999999995
    - type: ndcg_at_5
      value: 39.021
    - type: precision_at_1
      value: 31.135
    - type: precision_at_10
      value: 6.856
    - type: precision_at_100
      value: 0.988
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 15.9
    - type: precision_at_5
      value: 11.227
    - type: recall_at_1
      value: 27.833000000000002
    - type: recall_at_10
      value: 55.711
    - type: recall_at_100
      value: 76.255
    - type: recall_at_1000
      value: 91.51899999999999
    - type: recall_at_3
      value: 40.22
    - type: recall_at_5
      value: 46.69
    - type: map_at_1
      value: 21.274
    - type: map_at_10
      value: 29.925
    - type: map_at_100
      value: 31.171
    - type: map_at_1000
      value: 31.296000000000003
    - type: map_at_3
      value: 27.209
    - type: map_at_5
      value: 28.707
    - type: mrr_at_1
      value: 26.462000000000003
    - type: mrr_at_10
      value: 34.604
    - type: mrr_at_100
      value: 35.554
    - type: mrr_at_1000
      value: 35.622
    - type: mrr_at_3
      value: 32.295
    - type: mrr_at_5
      value: 33.598
    - type: ndcg_at_1
      value: 26.462000000000003
    - type: ndcg_at_10
      value: 35.193000000000005
    - type: ndcg_at_100
      value: 40.876000000000005
    - type: ndcg_at_1000
      value: 43.442
    - type: ndcg_at_3
      value: 30.724
    - type: ndcg_at_5
      value: 32.735
    - type: precision_at_1
      value: 26.462000000000003
    - type: precision_at_10
      value: 6.438000000000001
    - type: precision_at_100
      value: 1.093
    - type: precision_at_1000
      value: 0.15
    - type: precision_at_3
      value: 14.636
    - type: precision_at_5
      value: 10.496
    - type: recall_at_1
      value: 21.274
    - type: recall_at_10
      value: 46.322
    - type: recall_at_100
      value: 71.702
    - type: recall_at_1000
      value: 89.405
    - type: recall_at_3
      value: 33.444
    - type: recall_at_5
      value: 38.83
    - type: map_at_1
      value: 31.174000000000003
    - type: map_at_10
      value: 42.798
    - type: map_at_100
      value: 43.996
    - type: map_at_1000
      value: 44.088
    - type: map_at_3
      value: 39.255
    - type: map_at_5
      value: 41.336
    - type: mrr_at_1
      value: 37.22
    - type: mrr_at_10
      value: 47.035
    - type: mrr_at_100
      value: 47.833999999999996
    - type: mrr_at_1000
      value: 47.88
    - type: mrr_at_3
      value: 44.248
    - type: mrr_at_5
      value: 45.815
    - type: ndcg_at_1
      value: 37.22
    - type: ndcg_at_10
      value: 48.931999999999995
    - type: ndcg_at_100
      value: 53.991
    - type: ndcg_at_1000
      value: 55.825
    - type: ndcg_at_3
      value: 43.144
    - type: ndcg_at_5
      value: 45.964
    - type: precision_at_1
      value: 37.22
    - type: precision_at_10
      value: 8.451
    - type: precision_at_100
      value: 1.2189999999999999
    - type: precision_at_1000
      value: 0.149
    - type: precision_at_3
      value: 20.087
    - type: precision_at_5
      value: 14.235000000000001
    - type: recall_at_1
      value: 31.174000000000003
    - type: recall_at_10
      value: 63.232
    - type: recall_at_100
      value: 84.747
    - type: recall_at_1000
      value: 97.006
    - type: recall_at_3
      value: 47.087
    - type: recall_at_5
      value: 54.493
    - type: map_at_1
      value: 29.628
    - type: map_at_10
      value: 39.995999999999995
    - type: map_at_100
      value: 41.899
    - type: map_at_1000
      value: 42.125
    - type: map_at_3
      value: 36.345
    - type: map_at_5
      value: 38.474000000000004
    - type: mrr_at_1
      value: 36.364000000000004
    - type: mrr_at_10
      value: 45.293
    - type: mrr_at_100
      value: 46.278999999999996
    - type: mrr_at_1000
      value: 46.318
    - type: mrr_at_3
      value: 42.522999999999996
    - type: mrr_at_5
      value: 44.104
    - type: ndcg_at_1
      value: 36.364000000000004
    - type: ndcg_at_10
      value: 46.622
    - type: ndcg_at_100
      value: 52.617000000000004
    - type: ndcg_at_1000
      value: 54.529
    - type: ndcg_at_3
      value: 40.971999999999994
    - type: ndcg_at_5
      value: 43.738
    - type: precision_at_1
      value: 36.364000000000004
    - type: precision_at_10
      value: 9.110999999999999
    - type: precision_at_100
      value: 1.846
    - type: precision_at_1000
      value: 0.256
    - type: precision_at_3
      value: 19.236
    - type: precision_at_5
      value: 14.269000000000002
    - type: recall_at_1
      value: 29.628
    - type: recall_at_10
      value: 58.706
    - type: recall_at_100
      value: 85.116
    - type: recall_at_1000
      value: 97.258
    - type: recall_at_3
      value: 42.655
    - type: recall_at_5
      value: 49.909
    - type: map_at_1
      value: 25.499
    - type: map_at_10
      value: 34.284
    - type: map_at_100
      value: 35.416
    - type: map_at_1000
      value: 35.494
    - type: map_at_3
      value: 31.911
    - type: map_at_5
      value: 33.159
    - type: mrr_at_1
      value: 28.096
    - type: mrr_at_10
      value: 36.699
    - type: mrr_at_100
      value: 37.657000000000004
    - type: mrr_at_1000
      value: 37.714999999999996
    - type: mrr_at_3
      value: 34.72
    - type: mrr_at_5
      value: 35.746
    - type: ndcg_at_1
      value: 28.096
    - type: ndcg_at_10
      value: 39.041
    - type: ndcg_at_100
      value: 44.633
    - type: ndcg_at_1000
      value: 46.522000000000006
    - type: ndcg_at_3
      value: 34.663
    - type: ndcg_at_5
      value: 36.538
    - type: precision_at_1
      value: 28.096
    - type: precision_at_10
      value: 6.0440000000000005
    - type: precision_at_100
      value: 0.9520000000000001
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 14.911
    - type: precision_at_5
      value: 10.277
    - type: recall_at_1
      value: 25.499
    - type: recall_at_10
      value: 51.26199999999999
    - type: recall_at_100
      value: 76.896
    - type: recall_at_1000
      value: 90.763
    - type: recall_at_3
      value: 39.376
    - type: recall_at_5
      value: 43.785000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 10.532
    - type: map_at_10
      value: 19.911
    - type: map_at_100
      value: 21.926000000000002
    - type: map_at_1000
      value: 22.113
    - type: map_at_3
      value: 16.118
    - type: map_at_5
      value: 18.043
    - type: mrr_at_1
      value: 23.909
    - type: mrr_at_10
      value: 37.029
    - type: mrr_at_100
      value: 38.015
    - type: mrr_at_1000
      value: 38.054
    - type: mrr_at_3
      value: 33.29
    - type: mrr_at_5
      value: 35.446
    - type: ndcg_at_1
      value: 23.909
    - type: ndcg_at_10
      value: 28.691
    - type: ndcg_at_100
      value: 36.341
    - type: ndcg_at_1000
      value: 39.644
    - type: ndcg_at_3
      value: 22.561
    - type: ndcg_at_5
      value: 24.779999999999998
    - type: precision_at_1
      value: 23.909
    - type: precision_at_10
      value: 9.433
    - type: precision_at_100
      value: 1.763
    - type: precision_at_1000
      value: 0.23800000000000002
    - type: precision_at_3
      value: 17.438000000000002
    - type: precision_at_5
      value: 13.758999999999999
    - type: recall_at_1
      value: 10.532
    - type: recall_at_10
      value: 36.079
    - type: recall_at_100
      value: 62.156
    - type: recall_at_1000
      value: 80.53099999999999
    - type: recall_at_3
      value: 21.384
    - type: recall_at_5
      value: 27.29
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.483
    - type: map_at_10
      value: 21.986
    - type: map_at_100
      value: 31.319000000000003
    - type: map_at_1000
      value: 33.231
    - type: map_at_3
      value: 15.193000000000001
    - type: map_at_5
      value: 18.116
    - type: mrr_at_1
      value: 74.0
    - type: mrr_at_10
      value: 80.047
    - type: mrr_at_100
      value: 80.406
    - type: mrr_at_1000
      value: 80.414
    - type: mrr_at_3
      value: 78.667
    - type: mrr_at_5
      value: 79.467
    - type: ndcg_at_1
      value: 61.875
    - type: ndcg_at_10
      value: 46.544999999999995
    - type: ndcg_at_100
      value: 51.097
    - type: ndcg_at_1000
      value: 58.331999999999994
    - type: ndcg_at_3
      value: 51.622
    - type: ndcg_at_5
      value: 49.016
    - type: precision_at_1
      value: 74.0
    - type: precision_at_10
      value: 37.325
    - type: precision_at_100
      value: 11.743
    - type: precision_at_1000
      value: 2.423
    - type: precision_at_3
      value: 54.75
    - type: precision_at_5
      value: 47.699999999999996
    - type: recall_at_1
      value: 9.483
    - type: recall_at_10
      value: 27.477
    - type: recall_at_100
      value: 57.099999999999994
    - type: recall_at_1000
      value: 80.56
    - type: recall_at_3
      value: 16.543
    - type: recall_at_5
      value: 20.830000000000002
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 50.06
    - type: f1
      value: 44.99375486940016
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 70.94
    - type: map_at_10
      value: 80.854
    - type: map_at_100
      value: 81.096
    - type: map_at_1000
      value: 81.109
    - type: map_at_3
      value: 79.589
    - type: map_at_5
      value: 80.431
    - type: mrr_at_1
      value: 76.44800000000001
    - type: mrr_at_10
      value: 85.07000000000001
    - type: mrr_at_100
      value: 85.168
    - type: mrr_at_1000
      value: 85.17
    - type: mrr_at_3
      value: 84.221
    - type: mrr_at_5
      value: 84.832
    - type: ndcg_at_1
      value: 76.44800000000001
    - type: ndcg_at_10
      value: 85.019
    - type: ndcg_at_100
      value: 85.886
    - type: ndcg_at_1000
      value: 86.09400000000001
    - type: ndcg_at_3
      value: 83.023
    - type: ndcg_at_5
      value: 84.223
    - type: precision_at_1
      value: 76.44800000000001
    - type: precision_at_10
      value: 10.405000000000001
    - type: precision_at_100
      value: 1.105
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 32.208
    - type: precision_at_5
      value: 20.122999999999998
    - type: recall_at_1
      value: 70.94
    - type: recall_at_10
      value: 93.508
    - type: recall_at_100
      value: 96.962
    - type: recall_at_1000
      value: 98.24300000000001
    - type: recall_at_3
      value: 88.17099999999999
    - type: recall_at_5
      value: 91.191
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 23.844
    - type: map_at_10
      value: 41.629
    - type: map_at_100
      value: 43.766
    - type: map_at_1000
      value: 43.916
    - type: map_at_3
      value: 35.992000000000004
    - type: map_at_5
      value: 39.302
    - type: mrr_at_1
      value: 45.988
    - type: mrr_at_10
      value: 56.050999999999995
    - type: mrr_at_100
      value: 56.741
    - type: mrr_at_1000
      value: 56.767999999999994
    - type: mrr_at_3
      value: 53.498000000000005
    - type: mrr_at_5
      value: 55.071999999999996
    - type: ndcg_at_1
      value: 45.988
    - type: ndcg_at_10
      value: 49.891999999999996
    - type: ndcg_at_100
      value: 56.727000000000004
    - type: ndcg_at_1000
      value: 58.952000000000005
    - type: ndcg_at_3
      value: 45.09
    - type: ndcg_at_5
      value: 46.943
    - type: precision_at_1
      value: 45.988
    - type: precision_at_10
      value: 13.980999999999998
    - type: precision_at_100
      value: 2.136
    - type: precision_at_1000
      value: 0.252
    - type: precision_at_3
      value: 30.556
    - type: precision_at_5
      value: 22.778000000000002
    - type: recall_at_1
      value: 23.844
    - type: recall_at_10
      value: 58.46
    - type: recall_at_100
      value: 82.811
    - type: recall_at_1000
      value: 96.084
    - type: recall_at_3
      value: 41.636
    - type: recall_at_5
      value: 49.271
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 40.108
    - type: map_at_10
      value: 65.846
    - type: map_at_100
      value: 66.691
    - type: map_at_1000
      value: 66.743
    - type: map_at_3
      value: 62.09
    - type: map_at_5
      value: 64.412
    - type: mrr_at_1
      value: 80.216
    - type: mrr_at_10
      value: 85.768
    - type: mrr_at_100
      value: 85.92699999999999
    - type: mrr_at_1000
      value: 85.932
    - type: mrr_at_3
      value: 85.012
    - type: mrr_at_5
      value: 85.495
    - type: ndcg_at_1
      value: 80.216
    - type: ndcg_at_10
      value: 73.833
    - type: ndcg_at_100
      value: 76.68
    - type: ndcg_at_1000
      value: 77.639
    - type: ndcg_at_3
      value: 68.7
    - type: ndcg_at_5
      value: 71.514
    - type: precision_at_1
      value: 80.216
    - type: precision_at_10
      value: 15.616
    - type: precision_at_100
      value: 1.783
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_3
      value: 44.483
    - type: precision_at_5
      value: 28.904999999999998
    - type: recall_at_1
      value: 40.108
    - type: recall_at_10
      value: 78.082
    - type: recall_at_100
      value: 89.129
    - type: recall_at_1000
      value: 95.381
    - type: recall_at_3
      value: 66.725
    - type: recall_at_5
      value: 72.262
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 94.3208
    - type: ap
      value: 91.64852216825692
    - type: f1
      value: 94.31672442494217
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 16.954
    - type: map_at_10
      value: 28.605000000000004
    - type: map_at_100
      value: 29.875
    - type: map_at_1000
      value: 29.934
    - type: map_at_3
      value: 24.57
    - type: map_at_5
      value: 26.845000000000002
    - type: mrr_at_1
      value: 17.407
    - type: mrr_at_10
      value: 29.082
    - type: mrr_at_100
      value: 30.309
    - type: mrr_at_1000
      value: 30.361
    - type: mrr_at_3
      value: 25.112000000000002
    - type: mrr_at_5
      value: 27.37
    - type: ndcg_at_1
      value: 17.407
    - type: ndcg_at_10
      value: 35.555
    - type: ndcg_at_100
      value: 41.808
    - type: ndcg_at_1000
      value: 43.277
    - type: ndcg_at_3
      value: 27.291999999999998
    - type: ndcg_at_5
      value: 31.369999999999997
    - type: precision_at_1
      value: 17.407
    - type: precision_at_10
      value: 5.9670000000000005
    - type: precision_at_100
      value: 0.9119999999999999
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 11.939
    - type: precision_at_5
      value: 9.223
    - type: recall_at_1
      value: 16.954
    - type: recall_at_10
      value: 57.216
    - type: recall_at_100
      value: 86.384
    - type: recall_at_1000
      value: 97.64
    - type: recall_at_3
      value: 34.660999999999994
    - type: recall_at_5
      value: 44.484
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 95.29183766529867
    - type: f1
      value: 95.01282555921513
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 87.07934336525307
    - type: f1
      value: 69.58693991783085
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 79.71755211835911
    - type: f1
      value: 77.08207736007755
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 81.08607935440484
    - type: f1
      value: 80.71191664406739
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 36.5355083590869
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 37.24173539348128
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 32.84293003435578
    - type: mrr
      value: 34.09721970493348
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 6.369
    - type: map_at_10
      value: 14.892
    - type: map_at_100
      value: 18.884999999999998
    - type: map_at_1000
      value: 20.43
    - type: map_at_3
      value: 10.735999999999999
    - type: map_at_5
      value: 12.703000000000001
    - type: mrr_at_1
      value: 50.15500000000001
    - type: mrr_at_10
      value: 59.948
    - type: mrr_at_100
      value: 60.422
    - type: mrr_at_1000
      value: 60.455999999999996
    - type: mrr_at_3
      value: 58.204
    - type: mrr_at_5
      value: 59.35
    - type: ndcg_at_1
      value: 47.678
    - type: ndcg_at_10
      value: 39.050000000000004
    - type: ndcg_at_100
      value: 35.905
    - type: ndcg_at_1000
      value: 44.662
    - type: ndcg_at_3
      value: 44.781
    - type: ndcg_at_5
      value: 42.549
    - type: precision_at_1
      value: 49.226
    - type: precision_at_10
      value: 28.762
    - type: precision_at_100
      value: 8.767999999999999
    - type: precision_at_1000
      value: 2.169
    - type: precision_at_3
      value: 41.796
    - type: precision_at_5
      value: 37.09
    - type: recall_at_1
      value: 6.369
    - type: recall_at_10
      value: 19.842000000000002
    - type: recall_at_100
      value: 37.017
    - type: recall_at_1000
      value: 68.444
    - type: recall_at_3
      value: 12.446
    - type: recall_at_5
      value: 15.525
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 39.663
    - type: map_at_10
      value: 56.252
    - type: map_at_100
      value: 57.018
    - type: map_at_1000
      value: 57.031
    - type: map_at_3
      value: 52.020999999999994
    - type: map_at_5
      value: 54.626
    - type: mrr_at_1
      value: 44.699
    - type: mrr_at_10
      value: 58.819
    - type: mrr_at_100
      value: 59.351
    - type: mrr_at_1000
      value: 59.358
    - type: mrr_at_3
      value: 55.615
    - type: mrr_at_5
      value: 57.598000000000006
    - type: ndcg_at_1
      value: 44.699
    - type: ndcg_at_10
      value: 63.873999999999995
    - type: ndcg_at_100
      value: 66.973
    - type: ndcg_at_1000
      value: 67.23700000000001
    - type: ndcg_at_3
      value: 56.25599999999999
    - type: ndcg_at_5
      value: 60.44199999999999
    - type: precision_at_1
      value: 44.699
    - type: precision_at_10
      value: 10.075000000000001
    - type: precision_at_100
      value: 1.185
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 25.202999999999996
    - type: precision_at_5
      value: 17.584
    - type: recall_at_1
      value: 39.663
    - type: recall_at_10
      value: 84.313
    - type: recall_at_100
      value: 97.56700000000001
    - type: recall_at_1000
      value: 99.44
    - type: recall_at_3
      value: 64.938
    - type: recall_at_5
      value: 74.515
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 69.708
    - type: map_at_10
      value: 83.86099999999999
    - type: map_at_100
      value: 84.513
    - type: map_at_1000
      value: 84.53
    - type: map_at_3
      value: 80.854
    - type: map_at_5
      value: 82.757
    - type: mrr_at_1
      value: 80.15
    - type: mrr_at_10
      value: 86.70400000000001
    - type: mrr_at_100
      value: 86.81400000000001
    - type: mrr_at_1000
      value: 86.815
    - type: mrr_at_3
      value: 85.658
    - type: mrr_at_5
      value: 86.37599999999999
    - type: ndcg_at_1
      value: 80.17
    - type: ndcg_at_10
      value: 87.7
    - type: ndcg_at_100
      value: 88.979
    - type: ndcg_at_1000
      value: 89.079
    - type: ndcg_at_3
      value: 84.71600000000001
    - type: ndcg_at_5
      value: 86.385
    - type: precision_at_1
      value: 80.17
    - type: precision_at_10
      value: 13.369
    - type: precision_at_100
      value: 1.53
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 37.123
    - type: precision_at_5
      value: 24.498
    - type: recall_at_1
      value: 69.708
    - type: recall_at_10
      value: 95.17099999999999
    - type: recall_at_100
      value: 99.529
    - type: recall_at_1000
      value: 99.97500000000001
    - type: recall_at_3
      value: 86.761
    - type: recall_at_5
      value: 91.34
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 63.005610557842786
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 65.85897055439158
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.388
    - type: map_at_10
      value: 14.087
    - type: map_at_100
      value: 16.618
    - type: map_at_1000
      value: 16.967
    - type: map_at_3
      value: 9.8
    - type: map_at_5
      value: 11.907
    - type: mrr_at_1
      value: 26.5
    - type: mrr_at_10
      value: 37.905
    - type: mrr_at_100
      value: 39.053
    - type: mrr_at_1000
      value: 39.091
    - type: mrr_at_3
      value: 34.567
    - type: mrr_at_5
      value: 36.307
    - type: ndcg_at_1
      value: 26.5
    - type: ndcg_at_10
      value: 23.06
    - type: ndcg_at_100
      value: 32.164
    - type: ndcg_at_1000
      value: 37.574000000000005
    - type: ndcg_at_3
      value: 21.623
    - type: ndcg_at_5
      value: 18.95
    - type: precision_at_1
      value: 26.5
    - type: precision_at_10
      value: 12.030000000000001
    - type: precision_at_100
      value: 2.5020000000000002
    - type: precision_at_1000
      value: 0.379
    - type: precision_at_3
      value: 20.200000000000003
    - type: precision_at_5
      value: 16.64
    - type: recall_at_1
      value: 5.388
    - type: recall_at_10
      value: 24.375
    - type: recall_at_100
      value: 50.818
    - type: recall_at_1000
      value: 76.86699999999999
    - type: recall_at_3
      value: 12.273
    - type: recall_at_5
      value: 16.858
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 85.09465497223438
    - type: cos_sim_spearman
      value: 80.55601111843897
    - type: euclidean_pearson
      value: 82.40135168520864
    - type: euclidean_spearman
      value: 80.05606361845396
    - type: manhattan_pearson
      value: 82.24092291787754
    - type: manhattan_spearman
      value: 79.89739846820373
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 81.14210597635189
    - type: cos_sim_spearman
      value: 73.69447481152118
    - type: euclidean_pearson
      value: 75.08507068029972
    - type: euclidean_spearman
      value: 71.04077458564372
    - type: manhattan_pearson
      value: 75.64918699307383
    - type: manhattan_spearman
      value: 71.61677355593945
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 85.41396417076866
    - type: cos_sim_spearman
      value: 85.82245898186092
    - type: euclidean_pearson
      value: 85.58527168297935
    - type: euclidean_spearman
      value: 85.94613250938504
    - type: manhattan_pearson
      value: 85.88114899068759
    - type: manhattan_spearman
      value: 86.42494392145366
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 83.7431948980468
    - type: cos_sim_spearman
      value: 82.05114289801895
    - type: euclidean_pearson
      value: 83.06116666914892
    - type: euclidean_spearman
      value: 81.82060562251957
    - type: manhattan_pearson
      value: 83.1858437025367
    - type: manhattan_spearman
      value: 82.09604293088852
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 88.455985912287
    - type: cos_sim_spearman
      value: 88.8044343107975
    - type: euclidean_pearson
      value: 87.155336804123
    - type: euclidean_spearman
      value: 87.79371420531842
    - type: manhattan_pearson
      value: 87.5784376507174
    - type: manhattan_spearman
      value: 88.429877987816
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 85.1631000795076
    - type: cos_sim_spearman
      value: 86.20042158061408
    - type: euclidean_pearson
      value: 84.88605965960737
    - type: euclidean_spearman
      value: 85.45926745772432
    - type: manhattan_pearson
      value: 85.18333987666729
    - type: manhattan_spearman
      value: 85.86048911387192
  - 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: 91.51301667439836
    - type: cos_sim_spearman
      value: 91.46469919011143
    - type: euclidean_pearson
      value: 91.15157693133415
    - type: euclidean_spearman
      value: 91.02656400119739
    - type: manhattan_pearson
      value: 91.08411259466446
    - type: manhattan_spearman
      value: 90.84339904461068
  - 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: 69.08993728439704
    - type: cos_sim_spearman
      value: 69.20885645170797
    - type: euclidean_pearson
      value: 69.65638507632245
    - type: euclidean_spearman
      value: 68.69831912688514
    - type: manhattan_pearson
      value: 69.86621764969294
    - type: manhattan_spearman
      value: 69.05446631856769
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 86.96149243197495
    - type: cos_sim_spearman
      value: 87.43145597912833
    - type: euclidean_pearson
      value: 86.6762329641158
    - type: euclidean_spearman
      value: 86.67085254401809
    - type: manhattan_pearson
      value: 87.06412701458164
    - type: manhattan_spearman
      value: 87.10197412769807
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 86.43440918697488
    - type: mrr
      value: 96.3954826945023
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 60.494
    - type: map_at_10
      value: 72.074
    - type: map_at_100
      value: 72.475
    - type: map_at_1000
      value: 72.483
    - type: map_at_3
      value: 68.983
    - type: map_at_5
      value: 71.161
    - type: mrr_at_1
      value: 63.666999999999994
    - type: mrr_at_10
      value: 73.31299999999999
    - type: mrr_at_100
      value: 73.566
    - type: mrr_at_1000
      value: 73.574
    - type: mrr_at_3
      value: 71.111
    - type: mrr_at_5
      value: 72.72800000000001
    - type: ndcg_at_1
      value: 63.666999999999994
    - type: ndcg_at_10
      value: 77.024
    - type: ndcg_at_100
      value: 78.524
    - type: ndcg_at_1000
      value: 78.842
    - type: ndcg_at_3
      value: 72.019
    - type: ndcg_at_5
      value: 75.22999999999999
    - type: precision_at_1
      value: 63.666999999999994
    - type: precision_at_10
      value: 10.2
    - type: precision_at_100
      value: 1.103
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 28.111000000000004
    - type: precision_at_5
      value: 19.0
    - type: recall_at_1
      value: 60.494
    - type: recall_at_10
      value: 90.8
    - type: recall_at_100
      value: 97.333
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_3
      value: 77.644
    - type: recall_at_5
      value: 85.694
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.68415841584158
    - type: cos_sim_ap
      value: 91.23713949701548
    - type: cos_sim_f1
      value: 83.70221327967808
    - type: cos_sim_precision
      value: 84.21052631578947
    - type: cos_sim_recall
      value: 83.2
    - type: dot_accuracy
      value: 99.5
    - type: dot_ap
      value: 79.46312132270363
    - type: dot_f1
      value: 72.75320970042794
    - type: dot_precision
      value: 69.35630099728014
    - type: dot_recall
      value: 76.5
    - type: euclidean_accuracy
      value: 99.69108910891089
    - type: euclidean_ap
      value: 90.9016163254649
    - type: euclidean_f1
      value: 83.91752577319586
    - type: euclidean_precision
      value: 86.59574468085106
    - type: euclidean_recall
      value: 81.39999999999999
    - type: manhattan_accuracy
      value: 99.7039603960396
    - type: manhattan_ap
      value: 91.5593806619311
    - type: manhattan_f1
      value: 85.08124076809453
    - type: manhattan_precision
      value: 83.80213385063045
    - type: manhattan_recall
      value: 86.4
    - type: max_accuracy
      value: 99.7039603960396
    - type: max_ap
      value: 91.5593806619311
    - type: max_f1
      value: 85.08124076809453
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 74.40806543281603
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 38.51757703316821
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 54.33475593449746
    - type: mrr
      value: 55.3374474789916
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.249926396023596
    - type: cos_sim_spearman
      value: 29.820375700458158
    - type: dot_pearson
      value: 28.820307635930355
    - type: dot_spearman
      value: 28.824273052746825
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.233
    - type: map_at_10
      value: 2.061
    - type: map_at_100
      value: 12.607
    - type: map_at_1000
      value: 30.031000000000002
    - type: map_at_3
      value: 0.6669999999999999
    - type: map_at_5
      value: 1.091
    - type: mrr_at_1
      value: 88.0
    - type: mrr_at_10
      value: 93.067
    - type: mrr_at_100
      value: 93.067
    - type: mrr_at_1000
      value: 93.067
    - type: mrr_at_3
      value: 92.667
    - type: mrr_at_5
      value: 93.067
    - type: ndcg_at_1
      value: 84.0
    - type: ndcg_at_10
      value: 81.072
    - type: ndcg_at_100
      value: 62.875
    - type: ndcg_at_1000
      value: 55.641
    - type: ndcg_at_3
      value: 85.296
    - type: ndcg_at_5
      value: 84.10499999999999
    - type: precision_at_1
      value: 88.0
    - type: precision_at_10
      value: 83.39999999999999
    - type: precision_at_100
      value: 63.7
    - type: precision_at_1000
      value: 24.622
    - type: precision_at_3
      value: 88.0
    - type: precision_at_5
      value: 87.2
    - type: recall_at_1
      value: 0.233
    - type: recall_at_10
      value: 2.188
    - type: recall_at_100
      value: 15.52
    - type: recall_at_1000
      value: 52.05499999999999
    - type: recall_at_3
      value: 0.6859999999999999
    - type: recall_at_5
      value: 1.1440000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 3.19
    - type: map_at_10
      value: 11.491999999999999
    - type: map_at_100
      value: 17.251
    - type: map_at_1000
      value: 18.795
    - type: map_at_3
      value: 6.146
    - type: map_at_5
      value: 8.113
    - type: mrr_at_1
      value: 44.897999999999996
    - type: mrr_at_10
      value: 56.57
    - type: mrr_at_100
      value: 57.348
    - type: mrr_at_1000
      value: 57.357
    - type: mrr_at_3
      value: 52.041000000000004
    - type: mrr_at_5
      value: 55.408
    - type: ndcg_at_1
      value: 40.816
    - type: ndcg_at_10
      value: 27.968
    - type: ndcg_at_100
      value: 39.0
    - type: ndcg_at_1000
      value: 50.292
    - type: ndcg_at_3
      value: 31.256
    - type: ndcg_at_5
      value: 28.855999999999998
    - type: precision_at_1
      value: 44.897999999999996
    - type: precision_at_10
      value: 24.285999999999998
    - type: precision_at_100
      value: 7.898
    - type: precision_at_1000
      value: 1.541
    - type: precision_at_3
      value: 30.612000000000002
    - type: precision_at_5
      value: 27.346999999999998
    - type: recall_at_1
      value: 3.19
    - type: recall_at_10
      value: 17.954
    - type: recall_at_100
      value: 48.793
    - type: recall_at_1000
      value: 83.357
    - type: recall_at_3
      value: 6.973999999999999
    - type: recall_at_5
      value: 10.391
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.89139999999999
    - type: ap
      value: 15.562539739828049
    - type: f1
      value: 55.38685639741247
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 62.48160724391625
    - type: f1
      value: 62.76700854121342
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 57.157071531498275
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 87.15503367705789
    - type: cos_sim_ap
      value: 77.20584529783206
    - type: cos_sim_f1
      value: 71.3558088770313
    - type: cos_sim_precision
      value: 66.02333931777379
    - type: cos_sim_recall
      value: 77.62532981530343
    - type: dot_accuracy
      value: 83.10186564940096
    - type: dot_ap
      value: 64.34160146443133
    - type: dot_f1
      value: 63.23048153342683
    - type: dot_precision
      value: 56.75618967687789
    - type: dot_recall
      value: 71.37203166226914
    - type: euclidean_accuracy
      value: 86.94045419324074
    - type: euclidean_ap
      value: 76.08471767931738
    - type: euclidean_f1
      value: 71.41248592518455
    - type: euclidean_precision
      value: 67.90387818225078
    - type: euclidean_recall
      value: 75.30343007915567
    - type: manhattan_accuracy
      value: 86.80932228646361
    - type: manhattan_ap
      value: 76.03862870753638
    - type: manhattan_f1
      value: 71.2660917385327
    - type: manhattan_precision
      value: 67.70363334124912
    - type: manhattan_recall
      value: 75.22427440633246
    - type: max_accuracy
      value: 87.15503367705789
    - type: max_ap
      value: 77.20584529783206
    - type: max_f1
      value: 71.41248592518455
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.42639810610471
    - type: cos_sim_ap
      value: 86.45196525133669
    - type: cos_sim_f1
      value: 79.25172592977508
    - type: cos_sim_precision
      value: 76.50852802063925
    - type: cos_sim_recall
      value: 82.19895287958116
    - type: dot_accuracy
      value: 87.03768385919976
    - type: dot_ap
      value: 80.86465404774172
    - type: dot_f1
      value: 74.50351637940457
    - type: dot_precision
      value: 70.72293324109305
    - type: dot_recall
      value: 78.71111795503542
    - type: euclidean_accuracy
      value: 89.29056545193464
    - type: euclidean_ap
      value: 86.25102188096191
    - type: euclidean_f1
      value: 79.05038057267126
    - type: euclidean_precision
      value: 74.681550472538
    - type: euclidean_recall
      value: 83.9621188789652
    - type: manhattan_accuracy
      value: 89.34877944657896
    - type: manhattan_ap
      value: 86.35336214205911
    - type: manhattan_f1
      value: 79.20192588269623
    - type: manhattan_precision
      value: 75.24951483227058
    - type: manhattan_recall
      value: 83.59254696643055
    - type: max_accuracy
      value: 89.42639810610471
    - type: max_ap
      value: 86.45196525133669
    - type: max_f1
      value: 79.25172592977508
---

# Model Summary

> GritLM is a generative representational instruction tuned language model. It unifies text representation (embedding) and text generation into a single model achieving state-of-the-art performance on both types of tasks.

- **Repository:** [ContextualAI/gritlm](https://github.com/ContextualAI/gritlm)
- **Paper:** https://arxiv.org/abs/2402.09906
- **Logs:** https://wandb.ai/muennighoff/gritlm/runs/id130s1m/overview
- **Script:** https://github.com/ContextualAI/gritlm/blob/main/scripts/training/train_gritlm_8x7b.sh

| Model | Description |
|-------|-------------|
| [GritLM 7B](https://hf.co/GritLM/GritLM-7B) | Mistral 7B finetuned using GRIT |
| [GritLM 8x7B](https://hf.co/GritLM/GritLM-8x7B) | Mixtral 8x7B finetuned using GRIT |

# Use

The model usage is documented [here](https://github.com/ContextualAI/gritlm?tab=readme-ov-file#inference).

# Citation

```bibtex
@misc{muennighoff2024generative,
      title={Generative Representational Instruction Tuning}, 
      author={Niklas Muennighoff and Hongjin Su and Liang Wang and Nan Yang and Furu Wei and Tao Yu and Amanpreet Singh and Douwe Kiela},
      year={2024},
      eprint={2402.09906},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```