metadata
tags:
- ts
model-index:
- name: new7
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 90.25373134328359
- type: ap
value: 65.16915484773354
- type: f1
value: 86.23066728099059
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 93.974875
- type: ap
value: 91.14317344009288
- type: f1
value: 93.9685240564202
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 55.77799999999999
- type: f1
value: 55.30626203111084
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.663
- type: map_at_10
value: 43.903
- type: map_at_100
value: 44.779
- type: map_at_1000
value: 44.799
- type: map_at_3
value: 39.486
- type: map_at_5
value: 42.199
- type: mrr_at_1
value: 28.663
- type: mrr_at_10
value: 43.903
- type: mrr_at_100
value: 44.779
- type: mrr_at_1000
value: 44.799
- type: mrr_at_3
value: 39.486
- type: mrr_at_5
value: 42.199
- type: ndcg_at_1
value: 28.663
- type: ndcg_at_10
value: 51.983999999999995
- type: ndcg_at_100
value: 55.981
- type: ndcg_at_1000
value: 56.474000000000004
- type: ndcg_at_3
value: 43.025000000000006
- type: ndcg_at_5
value: 47.916
- type: precision_at_1
value: 28.663
- type: precision_at_10
value: 7.76
- type: precision_at_100
value: 0.9570000000000001
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 17.757
- type: precision_at_5
value: 13.03
- type: recall_at_1
value: 28.663
- type: recall_at_10
value: 77.596
- type: recall_at_100
value: 95.661
- type: recall_at_1000
value: 99.502
- type: recall_at_3
value: 53.272
- type: recall_at_5
value: 65.149
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 41.06284026514476
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 32.96711301401968
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 58.05094332005456
- type: mrr
value: 70.90808160752759
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 93.67415724859552
- type: cos_sim_spearman
value: 93.37019979249912
- type: euclidean_pearson
value: 91.767368542047
- type: euclidean_spearman
value: 92.75874007684216
- type: manhattan_pearson
value: 91.7931347639689
- type: manhattan_spearman
value: 92.94428647331738
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 91.6720779220779
- type: f1
value: 91.68597413806214
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 30.160011542775695
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 24.890267612946595
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.52
- type: map_at_10
value: 31.905
- type: map_at_100
value: 33.146
- type: map_at_1000
value: 33.315
- type: map_at_3
value: 29.567
- type: map_at_5
value: 30.729
- type: mrr_at_1
value: 28.469
- type: mrr_at_10
value: 37.884
- type: mrr_at_100
value: 38.757000000000005
- type: mrr_at_1000
value: 38.827
- type: mrr_at_3
value: 36.004000000000005
- type: mrr_at_5
value: 36.927
- type: ndcg_at_1
value: 28.469
- type: ndcg_at_10
value: 37.436
- type: ndcg_at_100
value: 42.754
- type: ndcg_at_1000
value: 45.744
- type: ndcg_at_3
value: 34.121
- type: ndcg_at_5
value: 35.315000000000005
- type: precision_at_1
value: 28.469
- type: precision_at_10
value: 7.167
- type: precision_at_100
value: 1.24
- type: precision_at_1000
value: 0.184
- type: precision_at_3
value: 17.072000000000003
- type: precision_at_5
value: 11.731
- type: recall_at_1
value: 22.52
- type: recall_at_10
value: 47.61
- type: recall_at_100
value: 70.494
- type: recall_at_1000
value: 90.081
- type: recall_at_3
value: 37.012
- type: recall_at_5
value: 41.053
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.167
- type: map_at_10
value: 29.227999999999998
- type: map_at_100
value: 30.361
- type: map_at_1000
value: 30.483
- type: map_at_3
value: 27.046
- type: map_at_5
value: 28.253
- type: mrr_at_1
value: 27.961999999999996
- type: mrr_at_10
value: 34.474
- type: mrr_at_100
value: 35.257
- type: mrr_at_1000
value: 35.312
- type: mrr_at_3
value: 32.633
- type: mrr_at_5
value: 33.7
- type: ndcg_at_1
value: 27.961999999999996
- type: ndcg_at_10
value: 33.800000000000004
- type: ndcg_at_100
value: 38.435
- type: ndcg_at_1000
value: 40.753
- type: ndcg_at_3
value: 30.584
- type: ndcg_at_5
value: 32.036
- type: precision_at_1
value: 27.961999999999996
- type: precision_at_10
value: 6.338000000000001
- type: precision_at_100
value: 1.127
- type: precision_at_1000
value: 0.159
- type: precision_at_3
value: 14.649999999999999
- type: precision_at_5
value: 10.408000000000001
- type: recall_at_1
value: 22.167
- type: recall_at_10
value: 41.735
- type: recall_at_100
value: 61.612
- type: recall_at_1000
value: 77.046
- type: recall_at_3
value: 31.985000000000003
- type: recall_at_5
value: 36.216
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.88
- type: map_at_10
value: 39.483000000000004
- type: map_at_100
value: 40.65
- type: map_at_1000
value: 40.727000000000004
- type: map_at_3
value: 36.095
- type: map_at_5
value: 38.138
- type: mrr_at_1
value: 33.292
- type: mrr_at_10
value: 42.655
- type: mrr_at_100
value: 43.505
- type: mrr_at_1000
value: 43.555
- type: mrr_at_3
value: 39.634
- type: mrr_at_5
value: 41.589999999999996
- type: ndcg_at_1
value: 33.292
- type: ndcg_at_10
value: 45.216
- type: ndcg_at_100
value: 50.029999999999994
- type: ndcg_at_1000
value: 51.795
- type: ndcg_at_3
value: 39.184000000000005
- type: ndcg_at_5
value: 42.416
- type: precision_at_1
value: 33.292
- type: precision_at_10
value: 7.661
- type: precision_at_100
value: 1.089
- type: precision_at_1000
value: 0.129
- type: precision_at_3
value: 17.701
- type: precision_at_5
value: 12.878
- type: recall_at_1
value: 28.88
- type: recall_at_10
value: 59.148
- type: recall_at_100
value: 80.10300000000001
- type: recall_at_1000
value: 92.938
- type: recall_at_3
value: 43.262
- type: recall_at_5
value: 51.05800000000001
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.732
- type: map_at_10
value: 24.104999999999997
- type: map_at_100
value: 25.085
- type: map_at_1000
value: 25.180000000000003
- type: map_at_3
value: 21.826999999999998
- type: map_at_5
value: 22.988
- type: mrr_at_1
value: 19.209
- type: mrr_at_10
value: 25.528000000000002
- type: mrr_at_100
value: 26.477
- type: mrr_at_1000
value: 26.56
- type: mrr_at_3
value: 23.315
- type: mrr_at_5
value: 24.427
- type: ndcg_at_1
value: 19.209
- type: ndcg_at_10
value: 28.055000000000003
- type: ndcg_at_100
value: 33.357
- type: ndcg_at_1000
value: 35.996
- type: ndcg_at_3
value: 23.526
- type: ndcg_at_5
value: 25.471
- type: precision_at_1
value: 19.209
- type: precision_at_10
value: 4.463
- type: precision_at_100
value: 0.756
- type: precision_at_1000
value: 0.10200000000000001
- type: precision_at_3
value: 9.981
- type: precision_at_5
value: 7.119000000000001
- type: recall_at_1
value: 17.732
- type: recall_at_10
value: 39.086999999999996
- type: recall_at_100
value: 64.264
- type: recall_at_1000
value: 84.589
- type: recall_at_3
value: 26.668999999999997
- type: recall_at_5
value: 31.361
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 10.99
- type: map_at_10
value: 16.661
- type: map_at_100
value: 17.763
- type: map_at_1000
value: 17.892
- type: map_at_3
value: 14.813
- type: map_at_5
value: 15.678
- type: mrr_at_1
value: 13.930000000000001
- type: mrr_at_10
value: 20.25
- type: mrr_at_100
value: 21.233
- type: mrr_at_1000
value: 21.325
- type: mrr_at_3
value: 18.262999999999998
- type: mrr_at_5
value: 19.177
- type: ndcg_at_1
value: 13.930000000000001
- type: ndcg_at_10
value: 20.558
- type: ndcg_at_100
value: 26.137
- type: ndcg_at_1000
value: 29.54
- type: ndcg_at_3
value: 17.015
- type: ndcg_at_5
value: 18.314
- type: precision_at_1
value: 13.930000000000001
- type: precision_at_10
value: 3.9050000000000002
- type: precision_at_100
value: 0.782
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 8.333
- type: precision_at_5
value: 5.92
- type: recall_at_1
value: 10.99
- type: recall_at_10
value: 29.156
- type: recall_at_100
value: 54.06100000000001
- type: recall_at_1000
value: 78.69699999999999
- type: recall_at_3
value: 19.11
- type: recall_at_5
value: 22.609
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 21.351
- type: map_at_10
value: 29.961
- type: map_at_100
value: 31.214
- type: map_at_1000
value: 31.349
- type: map_at_3
value: 27.283
- type: map_at_5
value: 28.851
- type: mrr_at_1
value: 25.602000000000004
- type: mrr_at_10
value: 34.554
- type: mrr_at_100
value: 35.423
- type: mrr_at_1000
value: 35.492000000000004
- type: mrr_at_3
value: 31.97
- type: mrr_at_5
value: 33.399
- type: ndcg_at_1
value: 25.602000000000004
- type: ndcg_at_10
value: 35.339999999999996
- type: ndcg_at_100
value: 40.89
- type: ndcg_at_1000
value: 43.732
- type: ndcg_at_3
value: 30.657
- type: ndcg_at_5
value: 32.945
- type: precision_at_1
value: 25.602000000000004
- type: precision_at_10
value: 6.574000000000001
- type: precision_at_100
value: 1.095
- type: precision_at_1000
value: 0.153
- type: precision_at_3
value: 14.629
- type: precision_at_5
value: 10.645
- type: recall_at_1
value: 21.351
- type: recall_at_10
value: 46.754
- type: recall_at_100
value: 70.247
- type: recall_at_1000
value: 89.653
- type: recall_at_3
value: 33.894000000000005
- type: recall_at_5
value: 39.667
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.052999999999997
- type: map_at_10
value: 24.291999999999998
- type: map_at_100
value: 25.348
- type: map_at_1000
value: 25.487
- type: map_at_3
value: 21.922
- type: map_at_5
value: 23.256
- type: mrr_at_1
value: 20.776
- type: mrr_at_10
value: 28.17
- type: mrr_at_100
value: 28.99
- type: mrr_at_1000
value: 29.082
- type: mrr_at_3
value: 25.951
- type: mrr_at_5
value: 27.241
- type: ndcg_at_1
value: 20.776
- type: ndcg_at_10
value: 28.909000000000002
- type: ndcg_at_100
value: 33.917
- type: ndcg_at_1000
value: 37.173
- type: ndcg_at_3
value: 24.769
- type: ndcg_at_5
value: 26.698
- type: precision_at_1
value: 20.776
- type: precision_at_10
value: 5.445
- type: precision_at_100
value: 0.943
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 11.985999999999999
- type: precision_at_5
value: 8.699
- type: recall_at_1
value: 17.052999999999997
- type: recall_at_10
value: 38.922000000000004
- type: recall_at_100
value: 60.624
- type: recall_at_1000
value: 83.83
- type: recall_at_3
value: 27.35
- type: recall_at_5
value: 32.513999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.981
- type: map_at_10
value: 24.99583333333333
- type: map_at_100
value: 26.054083333333335
- type: map_at_1000
value: 26.180916666666672
- type: map_at_3
value: 22.802666666666667
- type: map_at_5
value: 24.00508333333333
- type: mrr_at_1
value: 21.373916666666666
- type: mrr_at_10
value: 28.53433333333333
- type: mrr_at_100
value: 29.404000000000003
- type: mrr_at_1000
value: 29.481999999999996
- type: mrr_at_3
value: 26.462999999999997
- type: mrr_at_5
value: 27.596083333333333
- type: ndcg_at_1
value: 21.373916666666666
- type: ndcg_at_10
value: 29.40908333333333
- type: ndcg_at_100
value: 34.43266666666666
- type: ndcg_at_1000
value: 37.334916666666665
- type: ndcg_at_3
value: 25.518250000000002
- type: ndcg_at_5
value: 27.286916666666666
- type: precision_at_1
value: 21.373916666666666
- type: precision_at_10
value: 5.265666666666667
- type: precision_at_100
value: 0.9175833333333334
- type: precision_at_1000
value: 0.13533333333333336
- type: precision_at_3
value: 11.92425
- type: precision_at_5
value: 8.532250000000001
- type: recall_at_1
value: 17.981
- type: recall_at_10
value: 39.14641666666667
- type: recall_at_100
value: 61.65433333333334
- type: recall_at_1000
value: 82.39216666666665
- type: recall_at_3
value: 28.15266666666667
- type: recall_at_5
value: 32.795
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.834
- type: map_at_10
value: 22.046
- type: map_at_100
value: 22.954
- type: map_at_1000
value: 23.051
- type: map_at_3
value: 20.602999999999998
- type: map_at_5
value: 21.387999999999998
- type: mrr_at_1
value: 19.172
- type: mrr_at_10
value: 24.558
- type: mrr_at_100
value: 25.439
- type: mrr_at_1000
value: 25.509999999999998
- type: mrr_at_3
value: 23.185
- type: mrr_at_5
value: 23.852
- type: ndcg_at_1
value: 19.172
- type: ndcg_at_10
value: 25.189
- type: ndcg_at_100
value: 29.918
- type: ndcg_at_1000
value: 32.677
- type: ndcg_at_3
value: 22.496
- type: ndcg_at_5
value: 23.677
- type: precision_at_1
value: 19.172
- type: precision_at_10
value: 3.834
- type: precision_at_100
value: 0.679
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 9.611
- type: precision_at_5
value: 6.4719999999999995
- type: recall_at_1
value: 16.834
- type: recall_at_10
value: 32.554
- type: recall_at_100
value: 54.416
- type: recall_at_1000
value: 75.334
- type: recall_at_3
value: 25.057000000000002
- type: recall_at_5
value: 28.155
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 10.778
- type: map_at_10
value: 15.885
- type: map_at_100
value: 16.716
- type: map_at_1000
value: 16.838
- type: map_at_3
value: 14.283999999999999
- type: map_at_5
value: 15.067
- type: mrr_at_1
value: 13.421
- type: mrr_at_10
value: 19.022
- type: mrr_at_100
value: 19.819
- type: mrr_at_1000
value: 19.912
- type: mrr_at_3
value: 17.366
- type: mrr_at_5
value: 18.18
- type: ndcg_at_1
value: 13.421
- type: ndcg_at_10
value: 19.375
- type: ndcg_at_100
value: 23.733999999999998
- type: ndcg_at_1000
value: 26.878
- type: ndcg_at_3
value: 16.383
- type: ndcg_at_5
value: 17.53
- type: precision_at_1
value: 13.421
- type: precision_at_10
value: 3.637
- type: precision_at_100
value: 0.681
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 7.983
- type: precision_at_5
value: 5.671
- type: recall_at_1
value: 10.778
- type: recall_at_10
value: 26.985999999999997
- type: recall_at_100
value: 47.143
- type: recall_at_1000
value: 69.842
- type: recall_at_3
value: 18.289
- type: recall_at_5
value: 21.459
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.077
- type: map_at_10
value: 23.31
- type: map_at_100
value: 24.351
- type: map_at_1000
value: 24.471
- type: map_at_3
value: 21.272
- type: map_at_5
value: 22.320999999999998
- type: mrr_at_1
value: 19.683
- type: mrr_at_10
value: 26.44
- type: mrr_at_100
value: 27.395000000000003
- type: mrr_at_1000
value: 27.479
- type: mrr_at_3
value: 24.549000000000003
- type: mrr_at_5
value: 25.477
- type: ndcg_at_1
value: 19.683
- type: ndcg_at_10
value: 27.33
- type: ndcg_at_100
value: 32.595
- type: ndcg_at_1000
value: 35.671
- type: ndcg_at_3
value: 23.536
- type: ndcg_at_5
value: 25.09
- type: precision_at_1
value: 19.683
- type: precision_at_10
value: 4.711
- type: precision_at_100
value: 0.84
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 10.697
- type: precision_at_5
value: 7.5
- type: recall_at_1
value: 17.077
- type: recall_at_10
value: 36.532
- type: recall_at_100
value: 59.955999999999996
- type: recall_at_1000
value: 82.536
- type: recall_at_3
value: 25.982
- type: recall_at_5
value: 29.965999999999998
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.137
- type: map_at_10
value: 23.889
- type: map_at_100
value: 25.089
- type: map_at_1000
value: 25.284000000000002
- type: map_at_3
value: 21.844
- type: map_at_5
value: 23.185
- type: mrr_at_1
value: 20.552999999999997
- type: mrr_at_10
value: 27.996
- type: mrr_at_100
value: 28.921000000000003
- type: mrr_at_1000
value: 28.999999999999996
- type: mrr_at_3
value: 25.955000000000002
- type: mrr_at_5
value: 27.269
- type: ndcg_at_1
value: 20.552999999999997
- type: ndcg_at_10
value: 28.555000000000003
- type: ndcg_at_100
value: 34.035
- type: ndcg_at_1000
value: 37.466
- type: ndcg_at_3
value: 25.105
- type: ndcg_at_5
value: 27.13
- type: precision_at_1
value: 20.552999999999997
- type: precision_at_10
value: 5.534
- type: precision_at_100
value: 1.117
- type: precision_at_1000
value: 0.20400000000000001
- type: precision_at_3
value: 12.253
- type: precision_at_5
value: 9.17
- type: recall_at_1
value: 17.137
- type: recall_at_10
value: 37.527
- type: recall_at_100
value: 62.905
- type: recall_at_1000
value: 85.839
- type: recall_at_3
value: 27.262999999999998
- type: recall_at_5
value: 32.735
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 13.253
- type: map_at_10
value: 19.185
- type: map_at_100
value: 19.972
- type: map_at_1000
value: 20.094
- type: map_at_3
value: 17.076
- type: map_at_5
value: 18.207
- type: mrr_at_1
value: 14.418000000000001
- type: mrr_at_10
value: 20.881
- type: mrr_at_100
value: 21.632
- type: mrr_at_1000
value: 21.73
- type: mrr_at_3
value: 18.731
- type: mrr_at_5
value: 19.914
- type: ndcg_at_1
value: 14.418000000000001
- type: ndcg_at_10
value: 23.146
- type: ndcg_at_100
value: 27.389999999999997
- type: ndcg_at_1000
value: 30.593999999999998
- type: ndcg_at_3
value: 18.843
- type: ndcg_at_5
value: 20.821
- type: precision_at_1
value: 14.418000000000001
- type: precision_at_10
value: 3.9190000000000005
- type: precision_at_100
value: 0.662
- type: precision_at_1000
value: 0.101
- type: precision_at_3
value: 8.195
- type: precision_at_5
value: 6.174
- type: recall_at_1
value: 13.253
- type: recall_at_10
value: 33.745999999999995
- type: recall_at_100
value: 54.027
- type: recall_at_1000
value: 78.321
- type: recall_at_3
value: 21.959
- type: recall_at_5
value: 26.747
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 9.446
- type: ndcg_at_3
value: 8.708
- type: ndcg_at_5
value: 9.583
- type: ndcg_at_10
value: 11.324
- type: ndcg_at_100
value: 16.563
- type: ndcg_at_1000
value: 20.402
- type: map_at_1
value: 4.407
- type: map_at_3
value: 6.283999999999999
- type: map_at_5
value: 6.888
- type: map_at_10
value: 7.545
- type: map_at_100
value: 8.502
- type: map_at_1000
value: 8.677
- type: recall_at_1
value: 4.407
- type: recall_at_3
value: 8.341999999999999
- type: recall_at_5
value: 10.609
- type: recall_at_10
value: 14.572
- type: recall_at_100
value: 33.802
- type: recall_at_1000
value: 56.13
- type: precision_at_1
value: 9.446
- type: precision_at_3
value: 6.3839999999999995
- type: precision_at_5
value: 5.029
- type: precision_at_10
value: 3.655
- type: precision_at_100
value: 0.9169999999999999
- type: precision_at_1000
value: 0.159
- type: mrr_at_1
value: 9.446
- type: mrr_at_3
value: 12.975
- type: mrr_at_5
value: 14.102
- type: mrr_at_10
value: 15.223999999999998
- type: mrr_at_100
value: 16.378
- type: mrr_at_1000
value: 16.469
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.3839999999999995
- type: map_at_10
value: 8.92
- type: map_at_100
value: 12.509999999999998
- type: map_at_1000
value: 13.555
- type: map_at_3
value: 6.508
- type: map_at_5
value: 7.521
- type: mrr_at_1
value: 38
- type: mrr_at_10
value: 47.796
- type: mrr_at_100
value: 48.554
- type: mrr_at_1000
value: 48.579
- type: mrr_at_3
value: 44.708
- type: mrr_at_5
value: 46.521
- type: ndcg_at_1
value: 29.125
- type: ndcg_at_10
value: 22.126
- type: ndcg_at_100
value: 26.369999999999997
- type: ndcg_at_1000
value: 33.604
- type: ndcg_at_3
value: 24.102999999999998
- type: ndcg_at_5
value: 22.926
- type: precision_at_1
value: 38
- type: precision_at_10
value: 18.2
- type: precision_at_100
value: 6.208
- type: precision_at_1000
value: 1.3679999999999999
- type: precision_at_3
value: 26.5
- type: precision_at_5
value: 22.900000000000002
- type: recall_at_1
value: 4.3839999999999995
- type: recall_at_10
value: 13.520999999999999
- type: recall_at_100
value: 33.053
- type: recall_at_1000
value: 56.516
- type: recall_at_3
value: 7.515
- type: recall_at_5
value: 9.775
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 90.38999999999999
- type: f1
value: 87.12778738994012
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 70.132
- type: map_at_10
value: 79.527
- type: map_at_100
value: 79.81200000000001
- type: map_at_1000
value: 79.828
- type: map_at_3
value: 78.191
- type: map_at_5
value: 79.092
- type: mrr_at_1
value: 75.563
- type: mrr_at_10
value: 83.80199999999999
- type: mrr_at_100
value: 83.93
- type: mrr_at_1000
value: 83.933
- type: mrr_at_3
value: 82.818
- type: mrr_at_5
value: 83.505
- type: ndcg_at_1
value: 75.563
- type: ndcg_at_10
value: 83.692
- type: ndcg_at_100
value: 84.706
- type: ndcg_at_1000
value: 85.001
- type: ndcg_at_3
value: 81.51
- type: ndcg_at_5
value: 82.832
- type: precision_at_1
value: 75.563
- type: precision_at_10
value: 10.245
- type: precision_at_100
value: 1.0959999999999999
- type: precision_at_1000
value: 0.11399999999999999
- type: precision_at_3
value: 31.518
- type: precision_at_5
value: 19.772000000000002
- type: recall_at_1
value: 70.132
- type: recall_at_10
value: 92.204
- type: recall_at_100
value: 96.261
- type: recall_at_1000
value: 98.17399999999999
- type: recall_at_3
value: 86.288
- type: recall_at_5
value: 89.63799999999999
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 7.688000000000001
- type: map_at_10
value: 13.839000000000002
- type: map_at_100
value: 15.082999999999998
- type: map_at_1000
value: 15.276
- type: map_at_3
value: 11.662
- type: map_at_5
value: 12.827
- type: mrr_at_1
value: 15.741
- type: mrr_at_10
value: 23.304
- type: mrr_at_100
value: 24.239
- type: mrr_at_1000
value: 24.319
- type: mrr_at_3
value: 20.962
- type: mrr_at_5
value: 22.243
- type: ndcg_at_1
value: 15.741
- type: ndcg_at_10
value: 18.914
- type: ndcg_at_100
value: 24.742
- type: ndcg_at_1000
value: 28.938000000000002
- type: ndcg_at_3
value: 16.181
- type: ndcg_at_5
value: 17.078
- type: precision_at_1
value: 15.741
- type: precision_at_10
value: 5.7410000000000005
- type: precision_at_100
value: 1.168
- type: precision_at_1000
value: 0.19
- type: precision_at_3
value: 11.368
- type: precision_at_5
value: 8.735
- type: recall_at_1
value: 7.688000000000001
- type: recall_at_10
value: 24.442
- type: recall_at_100
value: 47.288999999999994
- type: recall_at_1000
value: 73.49900000000001
- type: recall_at_3
value: 15.15
- type: recall_at_5
value: 18.858
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 40.412
- type: map_at_10
value: 66.376
- type: map_at_100
value: 67.217
- type: map_at_1000
value: 67.271
- type: map_at_3
value: 62.741
- type: map_at_5
value: 65.069
- type: mrr_at_1
value: 80.824
- type: mrr_at_10
value: 86.53
- type: mrr_at_100
value: 86.67399999999999
- type: mrr_at_1000
value: 86.678
- type: mrr_at_3
value: 85.676
- type: mrr_at_5
value: 86.256
- type: ndcg_at_1
value: 80.824
- type: ndcg_at_10
value: 74.332
- type: ndcg_at_100
value: 77.154
- type: ndcg_at_1000
value: 78.12400000000001
- type: ndcg_at_3
value: 69.353
- type: ndcg_at_5
value: 72.234
- type: precision_at_1
value: 80.824
- type: precision_at_10
value: 15.652
- type: precision_at_100
value: 1.7840000000000003
- type: precision_at_1000
value: 0.191
- type: precision_at_3
value: 44.911
- type: precision_at_5
value: 29.221000000000004
- type: recall_at_1
value: 40.412
- type: recall_at_10
value: 78.25800000000001
- type: recall_at_100
value: 89.196
- type: recall_at_1000
value: 95.544
- type: recall_at_3
value: 67.367
- type: recall_at_5
value: 73.05199999999999
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 88.8228
- type: ap
value: 84.52103126779862
- type: f1
value: 88.797782219813
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 8.461
- type: map_at_10
value: 14.979999999999999
- type: map_at_100
value: 16.032
- type: map_at_1000
value: 16.128
- type: map_at_3
value: 12.64
- type: map_at_5
value: 13.914000000000001
- type: mrr_at_1
value: 8.681999999999999
- type: mrr_at_10
value: 15.341
- type: mrr_at_100
value: 16.377
- type: mrr_at_1000
value: 16.469
- type: mrr_at_3
value: 12.963
- type: mrr_at_5
value: 14.262
- type: ndcg_at_1
value: 8.681999999999999
- type: ndcg_at_10
value: 19.045
- type: ndcg_at_100
value: 24.735
- type: ndcg_at_1000
value: 27.556000000000004
- type: ndcg_at_3
value: 14.154
- type: ndcg_at_5
value: 16.448
- type: precision_at_1
value: 8.681999999999999
- type: precision_at_10
value: 3.292
- type: precision_at_100
value: 0.623
- type: precision_at_1000
value: 0.087
- type: precision_at_3
value: 6.275
- type: precision_at_5
value: 4.92
- type: recall_at_1
value: 8.461
- type: recall_at_10
value: 31.729000000000003
- type: recall_at_100
value: 59.367000000000004
- type: recall_at_1000
value: 81.86
- type: recall_at_3
value: 18.234
- type: recall_at_5
value: 23.74
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 98.1623347013224
- type: f1
value: 97.95934123221338
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 93.0141358869129
- type: f1
value: 77.42161481798763
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 77.20242098184264
- type: f1
value: 73.64580701123289
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 88.38264963012777
- type: f1
value: 87.6445935642575
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 28.982276213044095
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 26.08731318128303
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 29.680164236394784
- type: mrr
value: 30.60242075910688
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.35
- type: map_at_10
value: 10.03
- type: map_at_100
value: 12.61
- type: map_at_1000
value: 13.916999999999998
- type: map_at_3
value: 7.428
- type: map_at_5
value: 8.625
- type: mrr_at_1
value: 39.009
- type: mrr_at_10
value: 47.63
- type: mrr_at_100
value: 48.259
- type: mrr_at_1000
value: 48.302
- type: mrr_at_3
value: 45.408
- type: mrr_at_5
value: 46.971000000000004
- type: ndcg_at_1
value: 36.997
- type: ndcg_at_10
value: 28.781000000000002
- type: ndcg_at_100
value: 26.644000000000002
- type: ndcg_at_1000
value: 35.812
- type: ndcg_at_3
value: 34.056
- type: ndcg_at_5
value: 31.804
- type: precision_at_1
value: 38.080000000000005
- type: precision_at_10
value: 20.96
- type: precision_at_100
value: 6.808
- type: precision_at_1000
value: 1.991
- type: precision_at_3
value: 32.095
- type: precision_at_5
value: 27.43
- type: recall_at_1
value: 4.35
- type: recall_at_10
value: 14.396
- type: recall_at_100
value: 28.126
- type: recall_at_1000
value: 60.785
- type: recall_at_3
value: 9.001000000000001
- type: recall_at_5
value: 11.197
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.408
- type: map_at_10
value: 17.247
- type: map_at_100
value: 18.578
- type: map_at_1000
value: 18.683
- type: map_at_3
value: 14.424999999999999
- type: map_at_5
value: 15.967999999999998
- type: mrr_at_1
value: 10.718
- type: mrr_at_10
value: 18.974
- type: mrr_at_100
value: 20.153
- type: mrr_at_1000
value: 20.238
- type: mrr_at_3
value: 16.087
- type: mrr_at_5
value: 17.685000000000002
- type: ndcg_at_1
value: 10.718
- type: ndcg_at_10
value: 22.313
- type: ndcg_at_100
value: 28.810999999999996
- type: ndcg_at_1000
value: 31.495
- type: ndcg_at_3
value: 16.487
- type: ndcg_at_5
value: 19.252
- type: precision_at_1
value: 10.718
- type: precision_at_10
value: 4.256
- type: precision_at_100
value: 0.7979999999999999
- type: precision_at_1000
value: 0.105
- type: precision_at_3
value: 7.976
- type: precision_at_5
value: 6.3149999999999995
- type: recall_at_1
value: 9.408
- type: recall_at_10
value: 36.364999999999995
- type: recall_at_100
value: 66.16499999999999
- type: recall_at_1000
value: 86.47399999999999
- type: recall_at_3
value: 20.829
- type: recall_at_5
value: 27.296
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 65.499
- type: map_at_10
value: 78.432
- type: map_at_100
value: 79.169
- type: map_at_1000
value: 79.199
- type: map_at_3
value: 75.476
- type: map_at_5
value: 77.28399999999999
- type: mrr_at_1
value: 75.55
- type: mrr_at_10
value: 82.16499999999999
- type: mrr_at_100
value: 82.37
- type: mrr_at_1000
value: 82.375
- type: mrr_at_3
value: 80.925
- type: mrr_at_5
value: 81.748
- type: ndcg_at_1
value: 75.58
- type: ndcg_at_10
value: 82.663
- type: ndcg_at_100
value: 84.526
- type: ndcg_at_1000
value: 84.843
- type: ndcg_at_3
value: 79.38300000000001
- type: ndcg_at_5
value: 81.133
- type: precision_at_1
value: 75.58
- type: precision_at_10
value: 12.562000000000001
- type: precision_at_100
value: 1.48
- type: precision_at_1000
value: 0.155
- type: precision_at_3
value: 34.583000000000006
- type: precision_at_5
value: 22.858
- type: recall_at_1
value: 65.499
- type: recall_at_10
value: 90.71000000000001
- type: recall_at_100
value: 97.717
- type: recall_at_1000
value: 99.551
- type: recall_at_3
value: 81.273
- type: recall_at_5
value: 86.172
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 43.28689524907211
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 54.41734813535957
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.305
- type: map_at_10
value: 8.502
- type: map_at_100
value: 10.288
- type: map_at_1000
value: 10.599
- type: map_at_3
value: 6.146
- type: map_at_5
value: 7.207
- type: mrr_at_1
value: 16.400000000000002
- type: mrr_at_10
value: 26.054
- type: mrr_at_100
value: 27.319
- type: mrr_at_1000
value: 27.400000000000002
- type: mrr_at_3
value: 22.967000000000002
- type: mrr_at_5
value: 24.542
- type: ndcg_at_1
value: 16.400000000000002
- type: ndcg_at_10
value: 14.943000000000001
- type: ndcg_at_100
value: 22.596
- type: ndcg_at_1000
value: 28.345
- type: ndcg_at_3
value: 14.011000000000001
- type: ndcg_at_5
value: 12.065
- type: precision_at_1
value: 16.400000000000002
- type: precision_at_10
value: 7.93
- type: precision_at_100
value: 1.902
- type: precision_at_1000
value: 0.328
- type: precision_at_3
value: 13.233
- type: precision_at_5
value: 10.620000000000001
- type: recall_at_1
value: 3.305
- type: recall_at_10
value: 16.07
- type: recall_at_100
value: 38.592999999999996
- type: recall_at_1000
value: 66.678
- type: recall_at_3
value: 8.025
- type: recall_at_5
value: 10.743
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 94.03602783680165
- type: cos_sim_spearman
value: 91.93466287712853
- type: euclidean_pearson
value: 91.5804659261222
- type: euclidean_spearman
value: 91.84239224991634
- type: manhattan_pearson
value: 91.57789872896991
- type: manhattan_spearman
value: 91.82031929038708
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 97.2530615783017
- type: cos_sim_spearman
value: 95.61025838976805
- type: euclidean_pearson
value: 95.41071037458771
- type: euclidean_spearman
value: 95.6207550803838
- type: manhattan_pearson
value: 95.39723545188045
- type: manhattan_spearman
value: 95.61540593501014
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 95.27491458980685
- type: cos_sim_spearman
value: 95.1521844663505
- type: euclidean_pearson
value: 94.63883752108002
- type: euclidean_spearman
value: 94.85954995945424
- type: manhattan_pearson
value: 94.59749433419627
- type: manhattan_spearman
value: 94.80626857571967
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 97.10518525877228
- type: cos_sim_spearman
value: 96.85836209648471
- type: euclidean_pearson
value: 95.8019730340664
- type: euclidean_spearman
value: 96.78892865690494
- type: manhattan_pearson
value: 95.79265816494754
- type: manhattan_spearman
value: 96.7712534155723
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 96.66550105336606
- type: cos_sim_spearman
value: 96.73134982392861
- type: euclidean_pearson
value: 95.50375963201927
- type: euclidean_spearman
value: 96.46785996403956
- type: manhattan_pearson
value: 95.47555707089327
- type: manhattan_spearman
value: 96.40825860300748
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 96.07365154052914
- type: cos_sim_spearman
value: 96.1720485037732
- type: euclidean_pearson
value: 95.58880196128803
- type: euclidean_spearman
value: 96.02102007396296
- type: manhattan_pearson
value: 95.60295336628664
- type: manhattan_spearman
value: 96.03461694944212
- 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: 96.14907313714893
- type: cos_sim_spearman
value: 96.14822520805113
- type: euclidean_pearson
value: 95.62140726773103
- type: euclidean_spearman
value: 96.01818385482282
- type: manhattan_pearson
value: 95.60795162280982
- type: manhattan_spearman
value: 96.00703635484169
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 66.35513203366195
- type: cos_sim_spearman
value: 64.92002333937089
- type: euclidean_pearson
value: 67.06304516009153
- type: euclidean_spearman
value: 65.3504536039936
- type: manhattan_pearson
value: 67.22016756598737
- type: manhattan_spearman
value: 65.64455991383844
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 96.59372149477922
- type: cos_sim_spearman
value: 96.97247348665515
- type: euclidean_pearson
value: 95.64890160850817
- type: euclidean_spearman
value: 96.84619618958573
- type: manhattan_pearson
value: 95.65581449537562
- type: manhattan_spearman
value: 96.853383309355
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 79.9991957697061
- type: mrr
value: 93.85864317236866
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 42.25
- type: map_at_10
value: 51.257
- type: map_at_100
value: 52.261
- type: map_at_1000
value: 52.309000000000005
- type: map_at_3
value: 48.759
- type: map_at_5
value: 50.413
- type: mrr_at_1
value: 44
- type: mrr_at_10
value: 52.367
- type: mrr_at_100
value: 53.181999999999995
- type: mrr_at_1000
value: 53.223
- type: mrr_at_3
value: 50.222
- type: mrr_at_5
value: 51.656
- type: ndcg_at_1
value: 44
- type: ndcg_at_10
value: 55.672
- type: ndcg_at_100
value: 59.779
- type: ndcg_at_1000
value: 61.114999999999995
- type: ndcg_at_3
value: 51.136
- type: ndcg_at_5
value: 53.822
- type: precision_at_1
value: 44
- type: precision_at_10
value: 7.6
- type: precision_at_100
value: 0.9730000000000001
- type: precision_at_1000
value: 0.109
- type: precision_at_3
value: 20.111
- type: precision_at_5
value: 13.733
- type: recall_at_1
value: 42.25
- type: recall_at_10
value: 67.989
- type: recall_at_100
value: 85.56700000000001
- type: recall_at_1000
value: 96.267
- type: recall_at_3
value: 56.27799999999999
- type: recall_at_5
value: 62.678
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.75346534653465
- type: cos_sim_ap
value: 92.92934020206276
- type: cos_sim_f1
value: 87.37373737373737
- type: cos_sim_precision
value: 88.26530612244898
- type: cos_sim_recall
value: 86.5
- type: dot_accuracy
value: 99.7
- type: dot_ap
value: 90.30253078505329
- type: dot_f1
value: 84.55696202531644
- type: dot_precision
value: 85.64102564102564
- type: dot_recall
value: 83.5
- type: euclidean_accuracy
value: 99.75742574257426
- type: euclidean_ap
value: 92.97542565802068
- type: euclidean_f1
value: 87.48083801737351
- type: euclidean_precision
value: 89.44618599791013
- type: euclidean_recall
value: 85.6
- type: manhattan_accuracy
value: 99.75643564356436
- type: manhattan_ap
value: 92.92733519229752
- type: manhattan_f1
value: 87.41044012282498
- type: manhattan_precision
value: 89.51781970649894
- type: manhattan_recall
value: 85.39999999999999
- type: max_accuracy
value: 99.75742574257426
- type: max_ap
value: 92.97542565802068
- type: max_f1
value: 87.48083801737351
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 46.968629347107225
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 31.76101811464947
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 47.838618465936364
- type: mrr
value: 48.51134772090654
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.101149949190837
- type: cos_sim_spearman
value: 30.99886288816569
- type: dot_pearson
value: 28.905040829977978
- type: dot_spearman
value: 28.101690957830428
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.129
- type: map_at_10
value: 0.6930000000000001
- type: map_at_100
value: 2.408
- type: map_at_1000
value: 4.731
- type: map_at_3
value: 0.314
- type: map_at_5
value: 0.43
- type: mrr_at_1
value: 44
- type: mrr_at_10
value: 55.132999999999996
- type: mrr_at_100
value: 56.455
- type: mrr_at_1000
value: 56.474000000000004
- type: mrr_at_3
value: 53.333
- type: mrr_at_5
value: 55.132999999999996
- type: ndcg_at_1
value: 40
- type: ndcg_at_10
value: 33.283
- type: ndcg_at_100
value: 18.892
- type: ndcg_at_1000
value: 17.457
- type: ndcg_at_3
value: 39.073
- type: ndcg_at_5
value: 35.609
- type: precision_at_1
value: 44
- type: precision_at_10
value: 33.800000000000004
- type: precision_at_100
value: 17.44
- type: precision_at_1000
value: 7.04
- type: precision_at_3
value: 40.666999999999994
- type: precision_at_5
value: 36.4
- type: recall_at_1
value: 0.129
- type: recall_at_10
value: 0.91
- type: recall_at_100
value: 4.449
- type: recall_at_1000
value: 16.091
- type: recall_at_3
value: 0.349
- type: recall_at_5
value: 0.518
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.189
- type: map_at_10
value: 5.196
- type: map_at_100
value: 8.984
- type: map_at_1000
value: 10.333
- type: map_at_3
value: 2.513
- type: map_at_5
value: 3.8089999999999997
- type: mrr_at_1
value: 14.285999999999998
- type: mrr_at_10
value: 26.295
- type: mrr_at_100
value: 28.285
- type: mrr_at_1000
value: 28.303
- type: mrr_at_3
value: 22.109
- type: mrr_at_5
value: 24.864
- type: ndcg_at_1
value: 12.245000000000001
- type: ndcg_at_10
value: 13.196
- type: ndcg_at_100
value: 24.189
- type: ndcg_at_1000
value: 36.015
- type: ndcg_at_3
value: 12.153
- type: ndcg_at_5
value: 13.459999999999999
- type: precision_at_1
value: 14.285999999999998
- type: precision_at_10
value: 12.653
- type: precision_at_100
value: 5.673
- type: precision_at_1000
value: 1.32
- type: precision_at_3
value: 12.925
- type: precision_at_5
value: 15.101999999999999
- type: recall_at_1
value: 1.189
- type: recall_at_10
value: 9.478
- type: recall_at_100
value: 36.076
- type: recall_at_1000
value: 71.88900000000001
- type: recall_at_3
value: 3.1710000000000003
- type: recall_at_5
value: 5.944
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 81.1632
- type: ap
value: 21.801031224655016
- type: f1
value: 63.93057804886679
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 68.15789473684211
- type: f1
value: 68.55744497973521
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 53.77313771942972
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 85.79603027954938
- type: cos_sim_ap
value: 73.19931192854375
- type: cos_sim_f1
value: 66.7699457784663
- type: cos_sim_precision
value: 65.3690596562184
- type: cos_sim_recall
value: 68.23218997361478
- type: dot_accuracy
value: 84.72313286046374
- type: dot_ap
value: 69.84066382008972
- type: dot_f1
value: 64.42618869803336
- type: dot_precision
value: 60.98020735155514
- type: dot_recall
value: 68.28496042216359
- type: euclidean_accuracy
value: 85.81391190320082
- type: euclidean_ap
value: 73.4051677083228
- type: euclidean_f1
value: 67.35092864125122
- type: euclidean_precision
value: 62.721893491124256
- type: euclidean_recall
value: 72.71767810026385
- type: manhattan_accuracy
value: 85.81391190320082
- type: manhattan_ap
value: 73.33759860950396
- type: manhattan_f1
value: 67.32576589771757
- type: manhattan_precision
value: 62.63910969793323
- type: manhattan_recall
value: 72.77044854881267
- type: max_accuracy
value: 85.81391190320082
- type: max_ap
value: 73.4051677083228
- type: max_f1
value: 67.35092864125122
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.17479722125199
- type: cos_sim_ap
value: 84.37486145048878
- type: cos_sim_f1
value: 76.65294717365856
- type: cos_sim_precision
value: 75.21304186735827
- type: cos_sim_recall
value: 78.14906067138897
- type: dot_accuracy
value: 87.72460899600264
- type: dot_ap
value: 83.01188676406672
- type: dot_f1
value: 75.8810775054206
- type: dot_precision
value: 72.58665541728186
- type: dot_recall
value: 79.48875885432707
- type: euclidean_accuracy
value: 88.16315442232313
- type: euclidean_ap
value: 84.32021529803454
- type: euclidean_f1
value: 76.60147856804691
- type: euclidean_precision
value: 72.67638725727316
- type: euclidean_recall
value: 80.97474591931014
- type: manhattan_accuracy
value: 88.19226141964528
- type: manhattan_ap
value: 84.30111334073442
- type: manhattan_f1
value: 76.48944401459048
- type: manhattan_precision
value: 73.34134105843285
- type: manhattan_recall
value: 79.91992608561749
- type: max_accuracy
value: 88.19226141964528
- type: max_ap
value: 84.37486145048878
- type: max_f1
value: 76.65294717365856