metadata
tags:
- mteb
model-index:
- name: epoch_0_model
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 77.56716417910448
- type: ap
value: 40.91549063721234
- type: f1
value: 71.51708294746035
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 89.50825
- type: ap
value: 86.00556056390054
- type: f1
value: 89.48068855084334
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 46.82399999999999
- type: f1
value: 46.272112748273315
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.592000000000002
- type: map_at_10
value: 44.37
- type: map_at_100
value: 45.355000000000004
- type: map_at_1000
value: 45.363
- type: map_at_3
value: 39.272
- type: map_at_5
value: 42.405
- type: mrr_at_1
value: 29.445
- type: mrr_at_10
value: 44.668
- type: mrr_at_100
value: 45.646
- type: mrr_at_1000
value: 45.655
- type: mrr_at_3
value: 39.545
- type: mrr_at_5
value: 42.674
- type: ndcg_at_1
value: 28.592000000000002
- type: ndcg_at_10
value: 53.230999999999995
- type: ndcg_at_100
value: 57.188
- type: ndcg_at_1000
value: 57.371
- type: ndcg_at_3
value: 42.842
- type: ndcg_at_5
value: 48.538
- type: precision_at_1
value: 28.592000000000002
- type: precision_at_10
value: 8.151
- type: precision_at_100
value: 0.9820000000000001
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 17.733999999999998
- type: precision_at_5
value: 13.428
- type: recall_at_1
value: 28.592000000000002
- type: recall_at_10
value: 81.50800000000001
- type: recall_at_100
value: 98.222
- type: recall_at_1000
value: 99.57300000000001
- type: recall_at_3
value: 53.201
- type: recall_at_5
value: 67.14099999999999
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 45.83975081280601
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 36.20880276672235
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 60.88591268158169
- type: mrr
value: 75.19709361122104
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 89.65453333525659
- type: cos_sim_spearman
value: 86.84535232424253
- type: euclidean_pearson
value: 88.44638498736246
- type: euclidean_spearman
value: 86.84535232424253
- type: manhattan_pearson
value: 88.73402151565195
- type: manhattan_spearman
value: 87.24415659199119
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 84.7564935064935
- type: f1
value: 84.70138093263196
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 38.272839537742655
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 33.03251777955244
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 30.319000000000003
- type: map_at_10
value: 40.161
- type: map_at_100
value: 41.557
- type: map_at_1000
value: 41.678
- type: map_at_3
value: 37.008
- type: map_at_5
value: 38.592
- type: mrr_at_1
value: 37.053000000000004
- type: mrr_at_10
value: 45.597
- type: mrr_at_100
value: 46.443
- type: mrr_at_1000
value: 46.489000000000004
- type: mrr_at_3
value: 43.085
- type: mrr_at_5
value: 44.43
- type: ndcg_at_1
value: 37.053000000000004
- type: ndcg_at_10
value: 45.948
- type: ndcg_at_100
value: 51.44800000000001
- type: ndcg_at_1000
value: 53.54
- type: ndcg_at_3
value: 41.316
- type: ndcg_at_5
value: 43.15
- type: precision_at_1
value: 37.053000000000004
- type: precision_at_10
value: 8.569
- type: precision_at_100
value: 1.425
- type: precision_at_1000
value: 0.189
- type: precision_at_3
value: 19.695
- type: precision_at_5
value: 13.763
- type: recall_at_1
value: 30.319000000000003
- type: recall_at_10
value: 57.233000000000004
- type: recall_at_100
value: 80.441
- type: recall_at_1000
value: 94.041
- type: recall_at_3
value: 43.028
- type: recall_at_5
value: 48.806
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 31.022
- type: map_at_10
value: 41.305
- type: map_at_100
value: 42.576
- type: map_at_1000
value: 42.707
- type: map_at_3
value: 38.271
- type: map_at_5
value: 40.048
- type: mrr_at_1
value: 39.427
- type: mrr_at_10
value: 47.707
- type: mrr_at_100
value: 48.394
- type: mrr_at_1000
value: 48.439
- type: mrr_at_3
value: 45.552
- type: mrr_at_5
value: 46.823
- type: ndcg_at_1
value: 39.427
- type: ndcg_at_10
value: 47.121
- type: ndcg_at_100
value: 51.458999999999996
- type: ndcg_at_1000
value: 53.461000000000006
- type: ndcg_at_3
value: 43.001
- type: ndcg_at_5
value: 45.025
- type: precision_at_1
value: 39.427
- type: precision_at_10
value: 8.994
- type: precision_at_100
value: 1.456
- type: precision_at_1000
value: 0.192
- type: precision_at_3
value: 20.913
- type: precision_at_5
value: 14.917
- type: recall_at_1
value: 31.022
- type: recall_at_10
value: 56.769999999999996
- type: recall_at_100
value: 75.154
- type: recall_at_1000
value: 87.832
- type: recall_at_3
value: 44.295
- type: recall_at_5
value: 50.041000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 41.021
- type: map_at_10
value: 52.931
- type: map_at_100
value: 53.846000000000004
- type: map_at_1000
value: 53.905
- type: map_at_3
value: 49.952000000000005
- type: map_at_5
value: 51.566
- type: mrr_at_1
value: 46.708
- type: mrr_at_10
value: 56.467999999999996
- type: mrr_at_100
value: 57.06400000000001
- type: mrr_at_1000
value: 57.096999999999994
- type: mrr_at_3
value: 54.295
- type: mrr_at_5
value: 55.52
- type: ndcg_at_1
value: 46.708
- type: ndcg_at_10
value: 58.458
- type: ndcg_at_100
value: 62.21
- type: ndcg_at_1000
value: 63.438
- type: ndcg_at_3
value: 53.493
- type: ndcg_at_5
value: 55.824
- type: precision_at_1
value: 46.708
- type: precision_at_10
value: 9.166
- type: precision_at_100
value: 1.199
- type: precision_at_1000
value: 0.135
- type: precision_at_3
value: 23.532
- type: precision_at_5
value: 15.862000000000002
- type: recall_at_1
value: 41.021
- type: recall_at_10
value: 71.25
- type: recall_at_100
value: 87.507
- type: recall_at_1000
value: 96.206
- type: recall_at_3
value: 58.089
- type: recall_at_5
value: 63.82
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.413999999999998
- type: map_at_10
value: 34.404
- type: map_at_100
value: 35.359
- type: map_at_1000
value: 35.435
- type: map_at_3
value: 32.017
- type: map_at_5
value: 33.243
- type: mrr_at_1
value: 28.362
- type: mrr_at_10
value: 36.393
- type: mrr_at_100
value: 37.211
- type: mrr_at_1000
value: 37.273
- type: mrr_at_3
value: 33.992
- type: mrr_at_5
value: 35.309000000000005
- type: ndcg_at_1
value: 28.362
- type: ndcg_at_10
value: 38.964
- type: ndcg_at_100
value: 43.791000000000004
- type: ndcg_at_1000
value: 45.89
- type: ndcg_at_3
value: 34.201
- type: ndcg_at_5
value: 36.334
- type: precision_at_1
value: 28.362
- type: precision_at_10
value: 5.842
- type: precision_at_100
value: 0.868
- type: precision_at_1000
value: 0.109
- type: precision_at_3
value: 14.049
- type: precision_at_5
value: 9.695
- type: recall_at_1
value: 26.413999999999998
- type: recall_at_10
value: 51.017999999999994
- type: recall_at_100
value: 73.551
- type: recall_at_1000
value: 89.51
- type: recall_at_3
value: 38.385000000000005
- type: recall_at_5
value: 43.351
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.721999999999998
- type: map_at_10
value: 24.55
- type: map_at_100
value: 25.586
- type: map_at_1000
value: 25.715
- type: map_at_3
value: 22.445
- type: map_at_5
value: 23.497
- type: mrr_at_1
value: 21.642
- type: mrr_at_10
value: 28.979
- type: mrr_at_100
value: 29.898000000000003
- type: mrr_at_1000
value: 29.981
- type: mrr_at_3
value: 26.886
- type: mrr_at_5
value: 28.055999999999997
- type: ndcg_at_1
value: 21.642
- type: ndcg_at_10
value: 29.158
- type: ndcg_at_100
value: 34.352
- type: ndcg_at_1000
value: 37.456
- type: ndcg_at_3
value: 25.302000000000003
- type: ndcg_at_5
value: 26.916
- type: precision_at_1
value: 21.642
- type: precision_at_10
value: 5.274
- type: precision_at_100
value: 0.907
- type: precision_at_1000
value: 0.131
- type: precision_at_3
value: 12.148
- type: precision_at_5
value: 8.458
- type: recall_at_1
value: 17.721999999999998
- type: recall_at_10
value: 38.926
- type: recall_at_100
value: 61.698
- type: recall_at_1000
value: 83.742
- type: recall_at_3
value: 28.209
- type: recall_at_5
value: 32.462999999999994
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.429
- type: map_at_10
value: 38
- type: map_at_100
value: 39.262
- type: map_at_1000
value: 39.371
- type: map_at_3
value: 35.031
- type: map_at_5
value: 36.935
- type: mrr_at_1
value: 33.782000000000004
- type: mrr_at_10
value: 43.164
- type: mrr_at_100
value: 43.962
- type: mrr_at_1000
value: 44.012
- type: mrr_at_3
value: 40.711999999999996
- type: mrr_at_5
value: 42.32
- type: ndcg_at_1
value: 33.782000000000004
- type: ndcg_at_10
value: 43.574
- type: ndcg_at_100
value: 48.903999999999996
- type: ndcg_at_1000
value: 51.074
- type: ndcg_at_3
value: 38.858
- type: ndcg_at_5
value: 41.581
- type: precision_at_1
value: 33.782000000000004
- type: precision_at_10
value: 7.7
- type: precision_at_100
value: 1.217
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 18.157999999999998
- type: precision_at_5
value: 13.128
- type: recall_at_1
value: 28.429
- type: recall_at_10
value: 54.63
- type: recall_at_100
value: 77.183
- type: recall_at_1000
value: 91.708
- type: recall_at_3
value: 41.81
- type: recall_at_5
value: 48.794
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.579
- type: map_at_10
value: 35.135
- type: map_at_100
value: 36.382999999999996
- type: map_at_1000
value: 36.482
- type: map_at_3
value: 32.25
- type: map_at_5
value: 33.873999999999995
- type: mrr_at_1
value: 31.279
- type: mrr_at_10
value: 40.261
- type: mrr_at_100
value: 41.128
- type: mrr_at_1000
value: 41.175
- type: mrr_at_3
value: 37.823
- type: mrr_at_5
value: 39.245000000000005
- type: ndcg_at_1
value: 31.279
- type: ndcg_at_10
value: 40.64
- type: ndcg_at_100
value: 46.224
- type: ndcg_at_1000
value: 48.392
- type: ndcg_at_3
value: 35.913000000000004
- type: ndcg_at_5
value: 38.086999999999996
- type: precision_at_1
value: 31.279
- type: precision_at_10
value: 7.306
- type: precision_at_100
value: 1.185
- type: precision_at_1000
value: 0.154
- type: precision_at_3
value: 17.009
- type: precision_at_5
value: 12.123000000000001
- type: recall_at_1
value: 25.579
- type: recall_at_10
value: 52.018
- type: recall_at_100
value: 76.02799999999999
- type: recall_at_1000
value: 90.996
- type: recall_at_3
value: 38.769
- type: recall_at_5
value: 44.417
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.15416666666666
- type: map_at_10
value: 34.64533333333333
- type: map_at_100
value: 35.7715
- type: map_at_1000
value: 35.885333333333335
- type: map_at_3
value: 32.03941666666667
- type: map_at_5
value: 33.47041666666667
- type: mrr_at_1
value: 30.654583333333328
- type: mrr_at_10
value: 38.71783333333333
- type: mrr_at_100
value: 39.52499999999999
- type: mrr_at_1000
value: 39.584250000000004
- type: mrr_at_3
value: 36.42975
- type: mrr_at_5
value: 37.72874999999999
- type: ndcg_at_1
value: 30.654583333333328
- type: ndcg_at_10
value: 39.663583333333335
- type: ndcg_at_100
value: 44.600249999999996
- type: ndcg_at_1000
value: 46.93808333333333
- type: ndcg_at_3
value: 35.2025
- type: ndcg_at_5
value: 37.27008333333333
- type: precision_at_1
value: 30.654583333333328
- type: precision_at_10
value: 6.8140833333333335
- type: precision_at_100
value: 1.1011666666666666
- type: precision_at_1000
value: 0.14883333333333335
- type: precision_at_3
value: 15.982249999999997
- type: precision_at_5
value: 11.254916666666666
- type: recall_at_1
value: 26.15416666666666
- type: recall_at_10
value: 50.44783333333333
- type: recall_at_100
value: 72.172
- type: recall_at_1000
value: 88.49900000000001
- type: recall_at_3
value: 38.030750000000005
- type: recall_at_5
value: 43.37716666666667
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.936
- type: map_at_10
value: 31.274
- type: map_at_100
value: 32.127
- type: map_at_1000
value: 32.218999999999994
- type: map_at_3
value: 29.036
- type: map_at_5
value: 30.128
- type: mrr_at_1
value: 27.454
- type: mrr_at_10
value: 33.973
- type: mrr_at_100
value: 34.75
- type: mrr_at_1000
value: 34.821999999999996
- type: mrr_at_3
value: 31.979000000000003
- type: mrr_at_5
value: 32.975
- type: ndcg_at_1
value: 27.454
- type: ndcg_at_10
value: 35.259
- type: ndcg_at_100
value: 39.513
- type: ndcg_at_1000
value: 41.913
- type: ndcg_at_3
value: 31.184
- type: ndcg_at_5
value: 32.804
- type: precision_at_1
value: 27.454
- type: precision_at_10
value: 5.445
- type: precision_at_100
value: 0.8250000000000001
- type: precision_at_1000
value: 0.109
- type: precision_at_3
value: 12.986
- type: precision_at_5
value: 8.895999999999999
- type: recall_at_1
value: 24.936
- type: recall_at_10
value: 44.807
- type: recall_at_100
value: 64.046
- type: recall_at_1000
value: 81.959
- type: recall_at_3
value: 33.587
- type: recall_at_5
value: 37.665
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.641000000000002
- type: map_at_10
value: 23.794
- type: map_at_100
value: 24.769
- type: map_at_1000
value: 24.898999999999997
- type: map_at_3
value: 21.67
- type: map_at_5
value: 22.933
- type: mrr_at_1
value: 20.061999999999998
- type: mrr_at_10
value: 27.467999999999996
- type: mrr_at_100
value: 28.303
- type: mrr_at_1000
value: 28.387
- type: mrr_at_3
value: 25.361
- type: mrr_at_5
value: 26.676
- type: ndcg_at_1
value: 20.061999999999998
- type: ndcg_at_10
value: 28.218
- type: ndcg_at_100
value: 32.988
- type: ndcg_at_1000
value: 36.083
- type: ndcg_at_3
value: 24.391
- type: ndcg_at_5
value: 26.349
- type: precision_at_1
value: 20.061999999999998
- type: precision_at_10
value: 4.997
- type: precision_at_100
value: 0.8670000000000001
- type: precision_at_1000
value: 0.131
- type: precision_at_3
value: 11.402
- type: precision_at_5
value: 8.273
- type: recall_at_1
value: 16.641000000000002
- type: recall_at_10
value: 37.925
- type: recall_at_100
value: 59.317
- type: recall_at_1000
value: 81.49499999999999
- type: recall_at_3
value: 27.381
- type: recall_at_5
value: 32.323
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.684
- type: map_at_10
value: 33.499
- type: map_at_100
value: 34.533
- type: map_at_1000
value: 34.647
- type: map_at_3
value: 30.908
- type: map_at_5
value: 32.376
- type: mrr_at_1
value: 29.757
- type: mrr_at_10
value: 37.439
- type: mrr_at_100
value: 38.239000000000004
- type: mrr_at_1000
value: 38.307
- type: mrr_at_3
value: 34.997
- type: mrr_at_5
value: 36.359
- type: ndcg_at_1
value: 29.757
- type: ndcg_at_10
value: 38.334
- type: ndcg_at_100
value: 43.171
- type: ndcg_at_1000
value: 45.775
- type: ndcg_at_3
value: 33.611999999999995
- type: ndcg_at_5
value: 35.884
- type: precision_at_1
value: 29.757
- type: precision_at_10
value: 6.361999999999999
- type: precision_at_100
value: 0.98
- type: precision_at_1000
value: 0.133
- type: precision_at_3
value: 14.988000000000001
- type: precision_at_5
value: 10.653
- type: recall_at_1
value: 25.684
- type: recall_at_10
value: 49.059000000000005
- type: recall_at_100
value: 70.339
- type: recall_at_1000
value: 88.567
- type: recall_at_3
value: 36.233
- type: recall_at_5
value: 41.974000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.265
- type: map_at_10
value: 31.948
- type: map_at_100
value: 33.558
- type: map_at_1000
value: 33.778999999999996
- type: map_at_3
value: 29.387999999999998
- type: map_at_5
value: 30.711
- type: mrr_at_1
value: 28.854000000000003
- type: mrr_at_10
value: 36.346000000000004
- type: mrr_at_100
value: 37.273
- type: mrr_at_1000
value: 37.336000000000006
- type: mrr_at_3
value: 33.794000000000004
- type: mrr_at_5
value: 35.168
- type: ndcg_at_1
value: 28.854000000000003
- type: ndcg_at_10
value: 37.281
- type: ndcg_at_100
value: 43.125
- type: ndcg_at_1000
value: 45.9
- type: ndcg_at_3
value: 32.637
- type: ndcg_at_5
value: 34.628
- type: precision_at_1
value: 28.854000000000003
- type: precision_at_10
value: 6.957000000000001
- type: precision_at_100
value: 1.455
- type: precision_at_1000
value: 0.231
- type: precision_at_3
value: 14.954
- type: precision_at_5
value: 10.751
- type: recall_at_1
value: 24.265
- type: recall_at_10
value: 47.709
- type: recall_at_100
value: 72.894
- type: recall_at_1000
value: 90.545
- type: recall_at_3
value: 34.618
- type: recall_at_5
value: 39.793
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 21.818
- type: map_at_10
value: 28.743000000000002
- type: map_at_100
value: 29.702
- type: map_at_1000
value: 29.787000000000003
- type: map_at_3
value: 26.497
- type: map_at_5
value: 27.742
- type: mrr_at_1
value: 23.474999999999998
- type: mrr_at_10
value: 30.819000000000003
- type: mrr_at_100
value: 31.635
- type: mrr_at_1000
value: 31.692999999999998
- type: mrr_at_3
value: 28.681
- type: mrr_at_5
value: 29.864
- type: ndcg_at_1
value: 23.474999999999998
- type: ndcg_at_10
value: 33.007999999999996
- type: ndcg_at_100
value: 38.018
- type: ndcg_at_1000
value: 40.335
- type: ndcg_at_3
value: 28.522
- type: ndcg_at_5
value: 30.659
- type: precision_at_1
value: 23.474999999999998
- type: precision_at_10
value: 5.157
- type: precision_at_100
value: 0.83
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 11.953
- type: precision_at_5
value: 8.540000000000001
- type: recall_at_1
value: 21.818
- type: recall_at_10
value: 44.029
- type: recall_at_100
value: 67.906
- type: recall_at_1000
value: 85.387
- type: recall_at_3
value: 31.965
- type: recall_at_5
value: 37.079
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.615
- type: map_at_10
value: 30.302
- type: map_at_100
value: 32.382
- type: map_at_1000
value: 32.573
- type: map_at_3
value: 25.689
- type: map_at_5
value: 28.137
- type: mrr_at_1
value: 40.847
- type: mrr_at_10
value: 53.577
- type: mrr_at_100
value: 54.19199999999999
- type: mrr_at_1000
value: 54.217999999999996
- type: mrr_at_3
value: 50.684
- type: mrr_at_5
value: 52.349000000000004
- type: ndcg_at_1
value: 40.847
- type: ndcg_at_10
value: 40.497
- type: ndcg_at_100
value: 47.575
- type: ndcg_at_1000
value: 50.663000000000004
- type: ndcg_at_3
value: 34.650999999999996
- type: ndcg_at_5
value: 36.503
- type: precision_at_1
value: 40.847
- type: precision_at_10
value: 12.469
- type: precision_at_100
value: 2.012
- type: precision_at_1000
value: 0.259
- type: precision_at_3
value: 26.124000000000002
- type: precision_at_5
value: 19.518
- type: recall_at_1
value: 17.615
- type: recall_at_10
value: 46.163
- type: recall_at_100
value: 69.985
- type: recall_at_1000
value: 87.033
- type: recall_at_3
value: 31.041999999999998
- type: recall_at_5
value: 37.419999999999995
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.616999999999999
- type: map_at_10
value: 20.591
- type: map_at_100
value: 29.738
- type: map_at_1000
value: 31.403
- type: map_at_3
value: 14.549999999999999
- type: map_at_5
value: 17.071
- type: mrr_at_1
value: 71.25
- type: mrr_at_10
value: 77.86699999999999
- type: mrr_at_100
value: 78.154
- type: mrr_at_1000
value: 78.159
- type: mrr_at_3
value: 76.333
- type: mrr_at_5
value: 77.146
- type: ndcg_at_1
value: 59.875
- type: ndcg_at_10
value: 45.233000000000004
- type: ndcg_at_100
value: 49.395
- type: ndcg_at_1000
value: 56.352000000000004
- type: ndcg_at_3
value: 50.171
- type: ndcg_at_5
value: 47.3
- type: precision_at_1
value: 71.25
- type: precision_at_10
value: 35.9
- type: precision_at_100
value: 11.733
- type: precision_at_1000
value: 2.111
- type: precision_at_3
value: 52.917
- type: precision_at_5
value: 45.25
- type: recall_at_1
value: 8.616999999999999
- type: recall_at_10
value: 26.571
- type: recall_at_100
value: 55.289
- type: recall_at_1000
value: 77.66300000000001
- type: recall_at_3
value: 15.823
- type: recall_at_5
value: 19.921
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 48.584999999999994
- type: f1
value: 43.715445937798705
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 72.175
- type: map_at_10
value: 81.659
- type: map_at_100
value: 81.918
- type: map_at_1000
value: 81.931
- type: map_at_3
value: 80.304
- type: map_at_5
value: 81.21199999999999
- type: mrr_at_1
value: 77.333
- type: mrr_at_10
value: 85.26
- type: mrr_at_100
value: 85.37400000000001
- type: mrr_at_1000
value: 85.37599999999999
- type: mrr_at_3
value: 84.378
- type: mrr_at_5
value: 85.001
- type: ndcg_at_1
value: 77.333
- type: ndcg_at_10
value: 85.533
- type: ndcg_at_100
value: 86.483
- type: ndcg_at_1000
value: 86.721
- type: ndcg_at_3
value: 83.434
- type: ndcg_at_5
value: 84.71
- type: precision_at_1
value: 77.333
- type: precision_at_10
value: 10.485999999999999
- type: precision_at_100
value: 1.121
- type: precision_at_1000
value: 0.116
- type: precision_at_3
value: 32.198
- type: precision_at_5
value: 20.222
- type: recall_at_1
value: 72.175
- type: recall_at_10
value: 93.633
- type: recall_at_100
value: 97.42699999999999
- type: recall_at_1000
value: 98.94
- type: recall_at_3
value: 88.07199999999999
- type: recall_at_5
value: 91.223
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.287000000000003
- type: map_at_10
value: 31.136000000000003
- type: map_at_100
value: 32.827
- type: map_at_1000
value: 33.011
- type: map_at_3
value: 27.150999999999996
- type: map_at_5
value: 29.459999999999997
- type: mrr_at_1
value: 37.963
- type: mrr_at_10
value: 46.449
- type: mrr_at_100
value: 47.353
- type: mrr_at_1000
value: 47.39
- type: mrr_at_3
value: 44.11
- type: mrr_at_5
value: 45.391
- type: ndcg_at_1
value: 37.963
- type: ndcg_at_10
value: 38.644
- type: ndcg_at_100
value: 44.923
- type: ndcg_at_1000
value: 48.059000000000005
- type: ndcg_at_3
value: 35.141
- type: ndcg_at_5
value: 36.335
- type: precision_at_1
value: 37.963
- type: precision_at_10
value: 10.494
- type: precision_at_100
value: 1.691
- type: precision_at_1000
value: 0.22699999999999998
- type: precision_at_3
value: 23.405
- type: precision_at_5
value: 17.16
- type: recall_at_1
value: 19.287000000000003
- type: recall_at_10
value: 45.558
- type: recall_at_100
value: 68.508
- type: recall_at_1000
value: 87.10900000000001
- type: recall_at_3
value: 31.991000000000003
- type: recall_at_5
value: 38.044
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 40.088
- type: map_at_10
value: 66.891
- type: map_at_100
value: 67.697
- type: map_at_1000
value: 67.75
- type: map_at_3
value: 63.517999999999994
- type: map_at_5
value: 65.667
- type: mrr_at_1
value: 80.176
- type: mrr_at_10
value: 85.662
- type: mrr_at_100
value: 85.827
- type: mrr_at_1000
value: 85.833
- type: mrr_at_3
value: 84.80799999999999
- type: mrr_at_5
value: 85.349
- type: ndcg_at_1
value: 80.176
- type: ndcg_at_10
value: 74.349
- type: ndcg_at_100
value: 77.10000000000001
- type: ndcg_at_1000
value: 78.084
- type: ndcg_at_3
value: 69.647
- type: ndcg_at_5
value: 72.312
- type: precision_at_1
value: 80.176
- type: precision_at_10
value: 15.629999999999999
- type: precision_at_100
value: 1.7760000000000002
- type: precision_at_1000
value: 0.191
- type: precision_at_3
value: 45.186
- type: precision_at_5
value: 29.215000000000003
- type: recall_at_1
value: 40.088
- type: recall_at_10
value: 78.14999999999999
- type: recall_at_100
value: 88.818
- type: recall_at_1000
value: 95.273
- type: recall_at_3
value: 67.779
- type: recall_at_5
value: 73.038
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 83.81960000000002
- type: ap
value: 78.83196561301477
- type: f1
value: 83.75970806716482
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 23.318
- type: map_at_10
value: 35.988
- type: map_at_100
value: 37.172
- type: map_at_1000
value: 37.217
- type: map_at_3
value: 32.193
- type: map_at_5
value: 34.467
- type: mrr_at_1
value: 23.982999999999997
- type: mrr_at_10
value: 36.588
- type: mrr_at_100
value: 37.714999999999996
- type: mrr_at_1000
value: 37.754
- type: mrr_at_3
value: 32.844
- type: mrr_at_5
value: 35.106
- type: ndcg_at_1
value: 23.982999999999997
- type: ndcg_at_10
value: 42.870000000000005
- type: ndcg_at_100
value: 48.433
- type: ndcg_at_1000
value: 49.559
- type: ndcg_at_3
value: 35.211
- type: ndcg_at_5
value: 39.273
- type: precision_at_1
value: 23.982999999999997
- type: precision_at_10
value: 6.678000000000001
- type: precision_at_100
value: 0.9440000000000001
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 14.981
- type: precision_at_5
value: 11.046
- type: recall_at_1
value: 23.318
- type: recall_at_10
value: 63.934999999999995
- type: recall_at_100
value: 89.335
- type: recall_at_1000
value: 97.966
- type: recall_at_3
value: 43.283
- type: recall_at_5
value: 53.041000000000004
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 93.57045143638851
- type: f1
value: 93.27721271351861
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 75.33971728226174
- type: f1
value: 57.738940854439825
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 73.05985205110962
- type: f1
value: 71.13355537275797
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 77.38063214525891
- type: f1
value: 77.50780716460197
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 32.74942819235406
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 30.696610712314364
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 28.7236836309487
- type: mrr
value: 29.45527326120238
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.838
- type: map_at_10
value: 13.492999999999999
- type: map_at_100
value: 16.598
- type: map_at_1000
value: 17.937
- type: map_at_3
value: 10.119
- type: map_at_5
value: 11.666
- type: mrr_at_1
value: 45.201
- type: mrr_at_10
value: 54.391
- type: mrr_at_100
value: 54.913000000000004
- type: mrr_at_1000
value: 54.952
- type: mrr_at_3
value: 52.012
- type: mrr_at_5
value: 53.715
- type: ndcg_at_1
value: 43.498
- type: ndcg_at_10
value: 35.631
- type: ndcg_at_100
value: 31.522
- type: ndcg_at_1000
value: 39.967000000000006
- type: ndcg_at_3
value: 41.258
- type: ndcg_at_5
value: 39.007
- type: precision_at_1
value: 44.891999999999996
- type: precision_at_10
value: 26.409
- type: precision_at_100
value: 7.799
- type: precision_at_1000
value: 2.044
- type: precision_at_3
value: 39.216
- type: precision_at_5
value: 34.056
- type: recall_at_1
value: 5.838
- type: recall_at_10
value: 17.314
- type: recall_at_100
value: 30.653000000000002
- type: recall_at_1000
value: 61.092
- type: recall_at_3
value: 11.299
- type: recall_at_5
value: 13.689000000000002
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 37.08
- type: map_at_10
value: 52.493
- type: map_at_100
value: 53.39699999999999
- type: map_at_1000
value: 53.422000000000004
- type: map_at_3
value: 48.504000000000005
- type: map_at_5
value: 50.878
- type: mrr_at_1
value: 41.425
- type: mrr_at_10
value: 55.001999999999995
- type: mrr_at_100
value: 55.665
- type: mrr_at_1000
value: 55.681999999999995
- type: mrr_at_3
value: 51.873000000000005
- type: mrr_at_5
value: 53.801
- type: ndcg_at_1
value: 41.396
- type: ndcg_at_10
value: 59.77400000000001
- type: ndcg_at_100
value: 63.476
- type: ndcg_at_1000
value: 64.011
- type: ndcg_at_3
value: 52.504
- type: ndcg_at_5
value: 56.379000000000005
- type: precision_at_1
value: 41.396
- type: precision_at_10
value: 9.429
- type: precision_at_100
value: 1.1520000000000001
- type: precision_at_1000
value: 0.12
- type: precision_at_3
value: 23.445
- type: precision_at_5
value: 16.333000000000002
- type: recall_at_1
value: 37.08
- type: recall_at_10
value: 79.22
- type: recall_at_100
value: 95.013
- type: recall_at_1000
value: 98.921
- type: recall_at_3
value: 60.702
- type: recall_at_5
value: 69.539
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 70.218
- type: map_at_10
value: 83.871
- type: map_at_100
value: 84.494
- type: map_at_1000
value: 84.514
- type: map_at_3
value: 80.95
- type: map_at_5
value: 82.783
- type: mrr_at_1
value: 80.9
- type: mrr_at_10
value: 87.176
- type: mrr_at_100
value: 87.283
- type: mrr_at_1000
value: 87.28399999999999
- type: mrr_at_3
value: 86.173
- type: mrr_at_5
value: 86.872
- type: ndcg_at_1
value: 80.92
- type: ndcg_at_10
value: 87.76899999999999
- type: ndcg_at_100
value: 89.017
- type: ndcg_at_1000
value: 89.154
- type: ndcg_at_3
value: 84.87
- type: ndcg_at_5
value: 86.469
- type: precision_at_1
value: 80.92
- type: precision_at_10
value: 13.272
- type: precision_at_100
value: 1.5150000000000001
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 37.03
- type: precision_at_5
value: 24.336
- type: recall_at_1
value: 70.218
- type: recall_at_10
value: 95.027
- type: recall_at_100
value: 99.29599999999999
- type: recall_at_1000
value: 99.936
- type: recall_at_3
value: 86.64
- type: recall_at_5
value: 91.23
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 56.98075987853009
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 62.50448653901921
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.303
- type: map_at_10
value: 10.918999999999999
- type: map_at_100
value: 12.709999999999999
- type: map_at_1000
value: 12.985
- type: map_at_3
value: 7.924
- type: map_at_5
value: 9.299
- type: mrr_at_1
value: 21.2
- type: mrr_at_10
value: 31.732
- type: mrr_at_100
value: 32.716
- type: mrr_at_1000
value: 32.775999999999996
- type: mrr_at_3
value: 28.549999999999997
- type: mrr_at_5
value: 30.064999999999998
- type: ndcg_at_1
value: 21.2
- type: ndcg_at_10
value: 18.576999999999998
- type: ndcg_at_100
value: 25.648
- type: ndcg_at_1000
value: 30.733
- type: ndcg_at_3
value: 17.718999999999998
- type: ndcg_at_5
value: 15.123000000000001
- type: precision_at_1
value: 21.2
- type: precision_at_10
value: 9.71
- type: precision_at_100
value: 1.992
- type: precision_at_1000
value: 0.322
- type: precision_at_3
value: 16.7
- type: precision_at_5
value: 13.18
- type: recall_at_1
value: 4.303
- type: recall_at_10
value: 19.688
- type: recall_at_100
value: 40.453
- type: recall_at_1000
value: 65.348
- type: recall_at_3
value: 10.148
- type: recall_at_5
value: 13.347999999999999
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 82.1158093156676
- type: cos_sim_spearman
value: 78.04442753931265
- type: euclidean_pearson
value: 79.96880352884281
- type: euclidean_spearman
value: 78.04442519916647
- type: manhattan_pearson
value: 79.95975401430859
- type: manhattan_spearman
value: 78.03343142853139
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 83.79721434783521
- type: cos_sim_spearman
value: 78.25975096999896
- type: euclidean_pearson
value: 79.1424902310369
- type: euclidean_spearman
value: 78.25975658297341
- type: manhattan_pearson
value: 79.18358724961024
- type: manhattan_spearman
value: 78.25842688776181
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 83.01380419796578
- type: cos_sim_spearman
value: 84.25947132331721
- type: euclidean_pearson
value: 83.60092535471402
- type: euclidean_spearman
value: 84.25947132331721
- type: manhattan_pearson
value: 83.58567994241997
- type: manhattan_spearman
value: 84.26967070369717
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 81.21721151989871
- type: cos_sim_spearman
value: 80.54270694465328
- type: euclidean_pearson
value: 80.59816986031214
- type: euclidean_spearman
value: 80.54271664913747
- type: manhattan_pearson
value: 80.5726582983618
- type: manhattan_spearman
value: 80.5337273819897
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 85.37279580582026
- type: cos_sim_spearman
value: 86.49650639126628
- type: euclidean_pearson
value: 86.16280095909306
- type: euclidean_spearman
value: 86.49650639126628
- type: manhattan_pearson
value: 86.10906620664134
- type: manhattan_spearman
value: 86.43874476942065
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 83.25909618059293
- type: cos_sim_spearman
value: 85.13586725576114
- type: euclidean_pearson
value: 84.23420740305912
- type: euclidean_spearman
value: 85.13586725576114
- type: manhattan_pearson
value: 84.31272025462884
- type: manhattan_spearman
value: 85.21734270533285
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 86.36016115914764
- type: cos_sim_spearman
value: 86.50087120712864
- type: euclidean_pearson
value: 87.43563849261436
- type: euclidean_spearman
value: 86.50087120712864
- type: manhattan_pearson
value: 87.3340358043399
- type: manhattan_spearman
value: 86.48887803473512
- 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: 65.4382473357056
- type: cos_sim_spearman
value: 65.02380140355883
- type: euclidean_pearson
value: 66.29732592598693
- type: euclidean_spearman
value: 65.02380140355883
- type: manhattan_pearson
value: 66.60136092354136
- type: manhattan_spearman
value: 65.21766397453412
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 84.10229648323359
- type: cos_sim_spearman
value: 84.81137203891447
- type: euclidean_pearson
value: 84.30614386139715
- type: euclidean_spearman
value: 84.81137203891447
- type: manhattan_pearson
value: 84.34828274644255
- type: manhattan_spearman
value: 84.8268824733233
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 81.0838765555117
- type: mrr
value: 94.65012928248223
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 57.760999999999996
- type: map_at_10
value: 67.12
- type: map_at_100
value: 67.69
- type: map_at_1000
value: 67.716
- type: map_at_3
value: 64.846
- type: map_at_5
value: 66.148
- type: mrr_at_1
value: 60.667
- type: mrr_at_10
value: 68.497
- type: mrr_at_100
value: 68.92200000000001
- type: mrr_at_1000
value: 68.944
- type: mrr_at_3
value: 66.889
- type: mrr_at_5
value: 67.839
- type: ndcg_at_1
value: 60.667
- type: ndcg_at_10
value: 71.429
- type: ndcg_at_100
value: 73.821
- type: ndcg_at_1000
value: 74.524
- type: ndcg_at_3
value: 67.57600000000001
- type: ndcg_at_5
value: 69.44500000000001
- type: precision_at_1
value: 60.667
- type: precision_at_10
value: 9.333
- type: precision_at_100
value: 1.0630000000000002
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 26.333000000000002
- type: precision_at_5
value: 17.133000000000003
- type: recall_at_1
value: 57.760999999999996
- type: recall_at_10
value: 83.122
- type: recall_at_100
value: 93.767
- type: recall_at_1000
value: 99.333
- type: recall_at_3
value: 72.64399999999999
- type: recall_at_5
value: 77.378
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.8108910891089
- type: cos_sim_ap
value: 95.09566660724403
- type: cos_sim_f1
value: 90.20408163265306
- type: cos_sim_precision
value: 92.08333333333333
- type: cos_sim_recall
value: 88.4
- type: dot_accuracy
value: 99.8108910891089
- type: dot_ap
value: 95.09566660724403
- type: dot_f1
value: 90.20408163265306
- type: dot_precision
value: 92.08333333333333
- type: dot_recall
value: 88.4
- type: euclidean_accuracy
value: 99.8108910891089
- type: euclidean_ap
value: 95.09566660724404
- type: euclidean_f1
value: 90.20408163265306
- type: euclidean_precision
value: 92.08333333333333
- type: euclidean_recall
value: 88.4
- type: manhattan_accuracy
value: 99.8108910891089
- type: manhattan_ap
value: 95.05229326105041
- type: manhattan_f1
value: 90.30948756976154
- type: manhattan_precision
value: 91.65808444902163
- type: manhattan_recall
value: 89
- type: max_accuracy
value: 99.8108910891089
- type: max_ap
value: 95.09566660724404
- type: max_f1
value: 90.30948756976154
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 63.716387449356304
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 33.57171985530598
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 50.31022782714341
- type: mrr
value: 51.005100903997956
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.55380844566254
- type: cos_sim_spearman
value: 30.694665194755576
- type: dot_pearson
value: 30.553807051946595
- type: dot_spearman
value: 30.694665194755576
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.231
- type: map_at_10
value: 2.097
- type: map_at_100
value: 11.899999999999999
- type: map_at_1000
value: 27.965
- type: map_at_3
value: 0.7040000000000001
- type: map_at_5
value: 1.13
- type: mrr_at_1
value: 88
- type: mrr_at_10
value: 94
- type: mrr_at_100
value: 94
- type: mrr_at_1000
value: 94
- type: mrr_at_3
value: 94
- type: mrr_at_5
value: 94
- type: ndcg_at_1
value: 82
- type: ndcg_at_10
value: 79.72
- type: ndcg_at_100
value: 60.731
- type: ndcg_at_1000
value: 52.528
- type: ndcg_at_3
value: 84.776
- type: ndcg_at_5
value: 83.977
- type: precision_at_1
value: 88
- type: precision_at_10
value: 84.8
- type: precision_at_100
value: 62.46000000000001
- type: precision_at_1000
value: 23.336000000000002
- type: precision_at_3
value: 91.333
- type: precision_at_5
value: 89.60000000000001
- type: recall_at_1
value: 0.231
- type: recall_at_10
value: 2.242
- type: recall_at_100
value: 14.629
- type: recall_at_1000
value: 48.937999999999995
- type: recall_at_3
value: 0.733
- type: recall_at_5
value: 1.187
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.326
- type: map_at_10
value: 11.613
- type: map_at_100
value: 17.999000000000002
- type: map_at_1000
value: 19.579
- type: map_at_3
value: 5.5280000000000005
- type: map_at_5
value: 8.235000000000001
- type: mrr_at_1
value: 28.571
- type: mrr_at_10
value: 47.865
- type: mrr_at_100
value: 48.638999999999996
- type: mrr_at_1000
value: 48.638999999999996
- type: mrr_at_3
value: 42.516999999999996
- type: mrr_at_5
value: 46.293
- type: ndcg_at_1
value: 25.509999999999998
- type: ndcg_at_10
value: 28.663
- type: ndcg_at_100
value: 39.208
- type: ndcg_at_1000
value: 50.32
- type: ndcg_at_3
value: 28.636
- type: ndcg_at_5
value: 28.819
- type: precision_at_1
value: 28.571
- type: precision_at_10
value: 27.143
- type: precision_at_100
value: 8.082
- type: precision_at_1000
value: 1.543
- type: precision_at_3
value: 31.293
- type: precision_at_5
value: 31.019999999999996
- type: recall_at_1
value: 2.326
- type: recall_at_10
value: 19.12
- type: recall_at_100
value: 49.721
- type: recall_at_1000
value: 83.123
- type: recall_at_3
value: 6.783
- type: recall_at_5
value: 11.472999999999999
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 70.39139999999999
- type: ap
value: 14.323066144268354
- type: f1
value: 54.37688697193885
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 59.81890209394454
- type: f1
value: 60.116654203584496
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 49.5398447532487
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 85.62317458425225
- type: cos_sim_ap
value: 72.58795996654061
- type: cos_sim_f1
value: 66.74816625916871
- type: cos_sim_precision
value: 62.1867881548975
- type: cos_sim_recall
value: 72.0316622691293
- type: dot_accuracy
value: 85.62317458425225
- type: dot_ap
value: 72.58796057492127
- type: dot_f1
value: 66.74816625916871
- type: dot_precision
value: 62.1867881548975
- type: dot_recall
value: 72.0316622691293
- type: euclidean_accuracy
value: 85.62317458425225
- type: euclidean_ap
value: 72.58798058258095
- type: euclidean_f1
value: 66.74816625916871
- type: euclidean_precision
value: 62.1867881548975
- type: euclidean_recall
value: 72.0316622691293
- type: manhattan_accuracy
value: 85.5754902545151
- type: manhattan_ap
value: 72.5765018516196
- type: manhattan_f1
value: 66.70611906734524
- type: manhattan_precision
value: 60.485082635758744
- type: manhattan_recall
value: 74.35356200527704
- type: max_accuracy
value: 85.62317458425225
- type: max_ap
value: 72.58798058258095
- type: max_f1
value: 66.74816625916871
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 89.03830480847596
- type: cos_sim_ap
value: 86.09219791618496
- type: cos_sim_f1
value: 78.19673991150107
- type: cos_sim_precision
value: 76.84531331301568
- type: cos_sim_recall
value: 79.59655066214968
- type: dot_accuracy
value: 89.03830480847596
- type: dot_ap
value: 86.09219596898019
- type: dot_f1
value: 78.19673991150107
- type: dot_precision
value: 76.84531331301568
- type: dot_recall
value: 79.59655066214968
- type: euclidean_accuracy
value: 89.03830480847596
- type: euclidean_ap
value: 86.09219836933755
- type: euclidean_f1
value: 78.19673991150107
- type: euclidean_precision
value: 76.84531331301568
- type: euclidean_recall
value: 79.59655066214968
- type: manhattan_accuracy
value: 89.04024527496411
- type: manhattan_ap
value: 86.07752622427454
- type: manhattan_f1
value: 78.17774911808216
- type: manhattan_precision
value: 77.04672897196262
- type: manhattan_recall
value: 79.3424699722821
- type: max_accuracy
value: 89.04024527496411
- type: max_ap
value: 86.09219836933755
- type: max_f1
value: 78.19673991150107