metadata
pipeline_tag: text-generation
inference: true
license: apache-2.0
datasets:
- GritLM/tulu2
tags:
- mteb
model-index:
- name: GritLM-8x7B
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
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:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
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:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 57.18400000000001
- type: f1
value: 55.945160479400954
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB 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:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 50.720077577006286
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 48.01021098734129
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 65.59672236627206
- type: mrr
value: 78.01191575429802
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
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:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 87.4577922077922
- type: f1
value: 87.38432712848123
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 41.41290357360428
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 38.67213605633667
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- 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
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- 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:
type: climate-fever
name: MTEB ClimateFEVER
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:
type: dbpedia-entity
name: MTEB DBPedia
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
- 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
- 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:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 50.06
- type: f1
value: 44.99375486940016
- task:
type: Retrieval
dataset:
type: fever
name: MTEB 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:
type: fiqa
name: MTEB FiQA2018
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:
type: hotpotqa
name: MTEB 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:
type: mteb/imdb
name: MTEB ImdbClassification
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:
type: msmarco
name: MTEB 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:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 95.29183766529867
- type: f1
value: 95.01282555921513
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 87.07934336525307
- type: f1
value: 69.58693991783085
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 79.71755211835911
- type: f1
value: 77.08207736007755
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 81.08607935440484
- type: f1
value: 80.71191664406739
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 36.5355083590869
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 37.24173539348128
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.84293003435578
- type: mrr
value: 34.09721970493348
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB 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:
type: nq
name: MTEB 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:
type: quora
name: MTEB QuoraRetrieval
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:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 63.005610557842786
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 65.85897055439158
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB 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:
type: mteb/sickr-sts
name: MTEB SICK-R
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:
type: mteb/sts12-sts
name: MTEB STS12
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:
type: mteb/sts13-sts
name: MTEB STS13
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:
type: mteb/sts14-sts
name: MTEB STS14
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:
type: mteb/sts15-sts
name: MTEB STS15
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:
type: mteb/sts16-sts
name: MTEB STS16
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
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:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
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:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 86.43440918697488
- type: mrr
value: 96.3954826945023
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB 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
- 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
- type: recall_at_3
value: 77.644
- type: recall_at_5
value: 85.694
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
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:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 74.40806543281603
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 38.51757703316821
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 54.33475593449746
- type: mrr
value: 55.3374474789916
- task:
type: Summarization
dataset:
type: mteb/summeval
name: 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:
type: trec-covid
name: MTEB TRECCOVID
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
- 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
- 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
- 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
- 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:
type: webis-touche2020
name: MTEB 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
- 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:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
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:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 62.48160724391625
- type: f1
value: 62.76700854121342
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 57.157071531498275
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
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:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
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
- 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 | Mistral 7B finetuned using GRIT |
| GritLM 8x7B | Mixtral 8x7B finetuned using GRIT |
Use
The model usage is documented here.
Citation
@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}
}