metadata
pipeline_tag: sentence-similarity
tags:
- finetuner
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
datasets:
- jinaai/negation-dataset
language: en
license: apache-2.0
model-index:
- name: jina-embedding-s-en-v2
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 69.70149253731343
- type: ap
value: 32.22528779918184
- type: f1
value: 63.66857824618267
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 79.55879999999999
- type: ap
value: 73.97885664972738
- type: f1
value: 79.4849322624122
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 38.69
- type: f1
value: 37.17512734389121
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.684
- type: map_at_10
value: 39.086999999999996
- type: map_at_100
value: 40.222
- type: map_at_1000
value: 40.231
- type: map_at_3
value: 34.282000000000004
- type: map_at_5
value: 36.689
- type: mrr_at_1
value: 23.826
- type: mrr_at_10
value: 39.147
- type: mrr_at_100
value: 40.282000000000004
- type: mrr_at_1000
value: 40.291
- type: mrr_at_3
value: 34.353
- type: mrr_at_5
value: 36.739
- type: ndcg_at_1
value: 23.684
- type: ndcg_at_10
value: 48.081
- type: ndcg_at_100
value: 52.902
- type: ndcg_at_1000
value: 53.111
- type: ndcg_at_3
value: 37.937
- type: ndcg_at_5
value: 42.32
- type: precision_at_1
value: 23.684
- type: precision_at_10
value: 7.703
- type: precision_at_100
value: 0.98
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 16.192999999999998
- type: precision_at_5
value: 11.863
- type: recall_at_1
value: 23.684
- type: recall_at_10
value: 77.027
- type: recall_at_100
value: 98.009
- type: recall_at_1000
value: 99.57300000000001
- type: recall_at_3
value: 48.577999999999996
- type: recall_at_5
value: 59.317
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 44.249612940073035
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 35.39423011105325
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 59.89078304869791
- type: mrr
value: 73.5045948203843
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 82.49373811125967
- type: cos_sim_spearman
value: 81.0446177409314
- type: euclidean_pearson
value: 82.1327844624042
- type: euclidean_spearman
value: 81.0446177409314
- type: manhattan_pearson
value: 81.88575541723692
- type: manhattan_spearman
value: 81.0705219456341
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 78.27272727272728
- type: f1
value: 77.36583416688741
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 36.12447585258704
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 29.305990951348743
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 31.458000000000002
- type: map_at_10
value: 42.132
- type: map_at_100
value: 43.47
- type: map_at_1000
value: 43.612
- type: map_at_3
value: 38.718
- type: map_at_5
value: 40.556
- type: mrr_at_1
value: 38.627
- type: mrr_at_10
value: 47.998000000000005
- type: mrr_at_100
value: 48.726
- type: mrr_at_1000
value: 48.778
- type: mrr_at_3
value: 45.255
- type: mrr_at_5
value: 46.893
- type: ndcg_at_1
value: 38.627
- type: ndcg_at_10
value: 48.229
- type: ndcg_at_100
value: 53.108999999999995
- type: ndcg_at_1000
value: 55.385
- type: ndcg_at_3
value: 43.191
- type: ndcg_at_5
value: 45.385999999999996
- type: precision_at_1
value: 38.627
- type: precision_at_10
value: 9.142
- type: precision_at_100
value: 1.462
- type: precision_at_1000
value: 0.19499999999999998
- type: precision_at_3
value: 20.552999999999997
- type: precision_at_5
value: 14.677999999999999
- type: recall_at_1
value: 31.458000000000002
- type: recall_at_10
value: 59.619
- type: recall_at_100
value: 79.953
- type: recall_at_1000
value: 94.921
- type: recall_at_3
value: 44.744
- type: recall_at_5
value: 51.010999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.762000000000004
- type: map_at_10
value: 35.366
- type: map_at_100
value: 36.481
- type: map_at_1000
value: 36.614999999999995
- type: map_at_3
value: 33.071
- type: map_at_5
value: 34.495
- type: mrr_at_1
value: 33.312000000000005
- type: mrr_at_10
value: 40.841
- type: mrr_at_100
value: 41.54
- type: mrr_at_1000
value: 41.592
- type: mrr_at_3
value: 38.928000000000004
- type: mrr_at_5
value: 40.119
- type: ndcg_at_1
value: 33.312000000000005
- type: ndcg_at_10
value: 40.238
- type: ndcg_at_100
value: 44.647
- type: ndcg_at_1000
value: 47.010999999999996
- type: ndcg_at_3
value: 36.991
- type: ndcg_at_5
value: 38.721
- type: precision_at_1
value: 33.312000000000005
- type: precision_at_10
value: 7.4079999999999995
- type: precision_at_100
value: 1.253
- type: precision_at_1000
value: 0.17500000000000002
- type: precision_at_3
value: 17.898
- type: precision_at_5
value: 12.687999999999999
- type: recall_at_1
value: 26.762000000000004
- type: recall_at_10
value: 48.41
- type: recall_at_100
value: 67.523
- type: recall_at_1000
value: 82.91199999999999
- type: recall_at_3
value: 38.6
- type: recall_at_5
value: 43.477
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 37.578
- type: map_at_10
value: 49.415
- type: map_at_100
value: 50.339
- type: map_at_1000
value: 50.402
- type: map_at_3
value: 46.412
- type: map_at_5
value: 48.183
- type: mrr_at_1
value: 43.072
- type: mrr_at_10
value: 52.82599999999999
- type: mrr_at_100
value: 53.456
- type: mrr_at_1000
value: 53.493
- type: mrr_at_3
value: 50.407999999999994
- type: mrr_at_5
value: 51.922000000000004
- type: ndcg_at_1
value: 43.072
- type: ndcg_at_10
value: 54.949000000000005
- type: ndcg_at_100
value: 58.744
- type: ndcg_at_1000
value: 60.150000000000006
- type: ndcg_at_3
value: 49.864000000000004
- type: ndcg_at_5
value: 52.503
- type: precision_at_1
value: 43.072
- type: precision_at_10
value: 8.734
- type: precision_at_100
value: 1.1520000000000001
- type: precision_at_1000
value: 0.132
- type: precision_at_3
value: 22.131999999999998
- type: precision_at_5
value: 15.21
- type: recall_at_1
value: 37.578
- type: recall_at_10
value: 67.918
- type: recall_at_100
value: 84.373
- type: recall_at_1000
value: 94.529
- type: recall_at_3
value: 54.457
- type: recall_at_5
value: 60.941
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.394000000000002
- type: map_at_10
value: 31.791000000000004
- type: map_at_100
value: 32.64
- type: map_at_1000
value: 32.727000000000004
- type: map_at_3
value: 29.557
- type: map_at_5
value: 30.858999999999998
- type: mrr_at_1
value: 25.085
- type: mrr_at_10
value: 33.721000000000004
- type: mrr_at_100
value: 34.492
- type: mrr_at_1000
value: 34.564
- type: mrr_at_3
value: 31.619999999999997
- type: mrr_at_5
value: 32.896
- type: ndcg_at_1
value: 25.085
- type: ndcg_at_10
value: 36.370000000000005
- type: ndcg_at_100
value: 40.96
- type: ndcg_at_1000
value: 43.171
- type: ndcg_at_3
value: 32.104
- type: ndcg_at_5
value: 34.300000000000004
- type: precision_at_1
value: 25.085
- type: precision_at_10
value: 5.537
- type: precision_at_100
value: 0.8340000000000001
- type: precision_at_1000
value: 0.105
- type: precision_at_3
value: 13.71
- type: precision_at_5
value: 9.514
- type: recall_at_1
value: 23.394000000000002
- type: recall_at_10
value: 48.549
- type: recall_at_100
value: 70.341
- type: recall_at_1000
value: 87.01299999999999
- type: recall_at_3
value: 36.947
- type: recall_at_5
value: 42.365
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 14.818000000000001
- type: map_at_10
value: 21.773999999999997
- type: map_at_100
value: 22.787
- type: map_at_1000
value: 22.915
- type: map_at_3
value: 19.414
- type: map_at_5
value: 20.651
- type: mrr_at_1
value: 18.657
- type: mrr_at_10
value: 25.794
- type: mrr_at_100
value: 26.695999999999998
- type: mrr_at_1000
value: 26.776
- type: mrr_at_3
value: 23.279
- type: mrr_at_5
value: 24.598
- type: ndcg_at_1
value: 18.657
- type: ndcg_at_10
value: 26.511000000000003
- type: ndcg_at_100
value: 31.447999999999997
- type: ndcg_at_1000
value: 34.71
- type: ndcg_at_3
value: 21.92
- type: ndcg_at_5
value: 23.938000000000002
- type: precision_at_1
value: 18.657
- type: precision_at_10
value: 4.9
- type: precision_at_100
value: 0.851
- type: precision_at_1000
value: 0.127
- type: precision_at_3
value: 10.488999999999999
- type: precision_at_5
value: 7.710999999999999
- type: recall_at_1
value: 14.818000000000001
- type: recall_at_10
value: 37.408
- type: recall_at_100
value: 58.81999999999999
- type: recall_at_1000
value: 82.612
- type: recall_at_3
value: 24.561
- type: recall_at_5
value: 29.685
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.332
- type: map_at_10
value: 35.366
- type: map_at_100
value: 36.569
- type: map_at_1000
value: 36.689
- type: map_at_3
value: 32.582
- type: map_at_5
value: 34.184
- type: mrr_at_1
value: 32.05
- type: mrr_at_10
value: 40.902
- type: mrr_at_100
value: 41.754000000000005
- type: mrr_at_1000
value: 41.811
- type: mrr_at_3
value: 38.547
- type: mrr_at_5
value: 40.019
- type: ndcg_at_1
value: 32.05
- type: ndcg_at_10
value: 40.999
- type: ndcg_at_100
value: 46.284
- type: ndcg_at_1000
value: 48.698
- type: ndcg_at_3
value: 36.39
- type: ndcg_at_5
value: 38.699
- type: precision_at_1
value: 32.05
- type: precision_at_10
value: 7.315
- type: precision_at_100
value: 1.172
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 17.036
- type: precision_at_5
value: 12.089
- type: recall_at_1
value: 26.332
- type: recall_at_10
value: 52.410000000000004
- type: recall_at_100
value: 74.763
- type: recall_at_1000
value: 91.03
- type: recall_at_3
value: 39.527
- type: recall_at_5
value: 45.517
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.849
- type: map_at_10
value: 31.502000000000002
- type: map_at_100
value: 32.854
- type: map_at_1000
value: 32.975
- type: map_at_3
value: 28.997
- type: map_at_5
value: 30.508999999999997
- type: mrr_at_1
value: 28.195999999999998
- type: mrr_at_10
value: 36.719
- type: mrr_at_100
value: 37.674
- type: mrr_at_1000
value: 37.743
- type: mrr_at_3
value: 34.532000000000004
- type: mrr_at_5
value: 35.845
- type: ndcg_at_1
value: 28.195999999999998
- type: ndcg_at_10
value: 36.605
- type: ndcg_at_100
value: 42.524
- type: ndcg_at_1000
value: 45.171
- type: ndcg_at_3
value: 32.574
- type: ndcg_at_5
value: 34.617
- type: precision_at_1
value: 28.195999999999998
- type: precision_at_10
value: 6.598
- type: precision_at_100
value: 1.121
- type: precision_at_1000
value: 0.153
- type: precision_at_3
value: 15.601
- type: precision_at_5
value: 11.073
- type: recall_at_1
value: 22.849
- type: recall_at_10
value: 46.528000000000006
- type: recall_at_100
value: 72.09
- type: recall_at_1000
value: 90.398
- type: recall_at_3
value: 35.116
- type: recall_at_5
value: 40.778
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.319500000000005
- type: map_at_10
value: 32.530166666666666
- type: map_at_100
value: 33.61566666666667
- type: map_at_1000
value: 33.73808333333333
- type: map_at_3
value: 30.074583333333326
- type: map_at_5
value: 31.429666666666662
- type: mrr_at_1
value: 28.675916666666666
- type: mrr_at_10
value: 36.49308333333334
- type: mrr_at_100
value: 37.310583333333334
- type: mrr_at_1000
value: 37.37616666666666
- type: mrr_at_3
value: 34.283166666666666
- type: mrr_at_5
value: 35.54333333333334
- type: ndcg_at_1
value: 28.675916666666666
- type: ndcg_at_10
value: 37.403416666666665
- type: ndcg_at_100
value: 42.25783333333333
- type: ndcg_at_1000
value: 44.778333333333336
- type: ndcg_at_3
value: 33.17099999999999
- type: ndcg_at_5
value: 35.12666666666667
- type: precision_at_1
value: 28.675916666666666
- type: precision_at_10
value: 6.463083333333334
- type: precision_at_100
value: 1.0585
- type: precision_at_1000
value: 0.14633333333333332
- type: precision_at_3
value: 15.158999999999997
- type: precision_at_5
value: 10.673916666666667
- type: recall_at_1
value: 24.319500000000005
- type: recall_at_10
value: 47.9135
- type: recall_at_100
value: 69.40266666666666
- type: recall_at_1000
value: 87.12566666666666
- type: recall_at_3
value: 36.03149999999999
- type: recall_at_5
value: 41.12791666666668
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.997
- type: map_at_10
value: 28.754999999999995
- type: map_at_100
value: 29.555999999999997
- type: map_at_1000
value: 29.653000000000002
- type: map_at_3
value: 27.069
- type: map_at_5
value: 27.884999999999998
- type: mrr_at_1
value: 25.767
- type: mrr_at_10
value: 31.195
- type: mrr_at_100
value: 31.964
- type: mrr_at_1000
value: 32.039
- type: mrr_at_3
value: 29.601
- type: mrr_at_5
value: 30.345
- type: ndcg_at_1
value: 25.767
- type: ndcg_at_10
value: 32.234
- type: ndcg_at_100
value: 36.461
- type: ndcg_at_1000
value: 39.005
- type: ndcg_at_3
value: 29.052
- type: ndcg_at_5
value: 30.248
- type: precision_at_1
value: 25.767
- type: precision_at_10
value: 4.893
- type: precision_at_100
value: 0.761
- type: precision_at_1000
value: 0.105
- type: precision_at_3
value: 12.219
- type: precision_at_5
value: 8.19
- type: recall_at_1
value: 22.997
- type: recall_at_10
value: 40.652
- type: recall_at_100
value: 60.302
- type: recall_at_1000
value: 79.17999999999999
- type: recall_at_3
value: 31.680999999999997
- type: recall_at_5
value: 34.698
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.3
- type: map_at_10
value: 22.581
- type: map_at_100
value: 23.517
- type: map_at_1000
value: 23.638
- type: map_at_3
value: 20.567
- type: map_at_5
value: 21.688
- type: mrr_at_1
value: 19.683
- type: mrr_at_10
value: 26.185000000000002
- type: mrr_at_100
value: 27.014
- type: mrr_at_1000
value: 27.092
- type: mrr_at_3
value: 24.145
- type: mrr_at_5
value: 25.308999999999997
- type: ndcg_at_1
value: 19.683
- type: ndcg_at_10
value: 26.699
- type: ndcg_at_100
value: 31.35
- type: ndcg_at_1000
value: 34.348
- type: ndcg_at_3
value: 23.026
- type: ndcg_at_5
value: 24.731
- type: precision_at_1
value: 19.683
- type: precision_at_10
value: 4.814
- type: precision_at_100
value: 0.836
- type: precision_at_1000
value: 0.126
- type: precision_at_3
value: 10.782
- type: precision_at_5
value: 7.825
- type: recall_at_1
value: 16.3
- type: recall_at_10
value: 35.521
- type: recall_at_100
value: 56.665
- type: recall_at_1000
value: 78.361
- type: recall_at_3
value: 25.223000000000003
- type: recall_at_5
value: 29.626
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.596999999999998
- type: map_at_10
value: 32.54
- type: map_at_100
value: 33.548
- type: map_at_1000
value: 33.661
- type: map_at_3
value: 30.134
- type: map_at_5
value: 31.468
- type: mrr_at_1
value: 28.825
- type: mrr_at_10
value: 36.495
- type: mrr_at_100
value: 37.329
- type: mrr_at_1000
value: 37.397999999999996
- type: mrr_at_3
value: 34.359
- type: mrr_at_5
value: 35.53
- type: ndcg_at_1
value: 28.825
- type: ndcg_at_10
value: 37.341
- type: ndcg_at_100
value: 42.221
- type: ndcg_at_1000
value: 44.799
- type: ndcg_at_3
value: 33.058
- type: ndcg_at_5
value: 34.961999999999996
- type: precision_at_1
value: 28.825
- type: precision_at_10
value: 6.175
- type: precision_at_100
value: 0.97
- type: precision_at_1000
value: 0.13
- type: precision_at_3
value: 14.924999999999999
- type: precision_at_5
value: 10.392
- type: recall_at_1
value: 24.596999999999998
- type: recall_at_10
value: 48.067
- type: recall_at_100
value: 69.736
- type: recall_at_1000
value: 87.855
- type: recall_at_3
value: 36.248999999999995
- type: recall_at_5
value: 41.086
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.224999999999998
- type: map_at_10
value: 31.826
- type: map_at_100
value: 33.366
- type: map_at_1000
value: 33.6
- type: map_at_3
value: 29.353
- type: map_at_5
value: 30.736
- type: mrr_at_1
value: 28.656
- type: mrr_at_10
value: 36.092
- type: mrr_at_100
value: 37.076
- type: mrr_at_1000
value: 37.141999999999996
- type: mrr_at_3
value: 33.86
- type: mrr_at_5
value: 35.144999999999996
- type: ndcg_at_1
value: 28.656
- type: ndcg_at_10
value: 37.025999999999996
- type: ndcg_at_100
value: 42.844
- type: ndcg_at_1000
value: 45.716
- type: ndcg_at_3
value: 32.98
- type: ndcg_at_5
value: 34.922
- type: precision_at_1
value: 28.656
- type: precision_at_10
value: 6.976
- type: precision_at_100
value: 1.48
- type: precision_at_1000
value: 0.23700000000000002
- type: precision_at_3
value: 15.348999999999998
- type: precision_at_5
value: 11.028
- type: recall_at_1
value: 24.224999999999998
- type: recall_at_10
value: 46.589999999999996
- type: recall_at_100
value: 72.331
- type: recall_at_1000
value: 90.891
- type: recall_at_3
value: 34.996
- type: recall_at_5
value: 40.294000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.524
- type: map_at_10
value: 27.314
- type: map_at_100
value: 28.260999999999996
- type: map_at_1000
value: 28.37
- type: map_at_3
value: 25.020999999999997
- type: map_at_5
value: 25.942
- type: mrr_at_1
value: 22.181
- type: mrr_at_10
value: 29.149
- type: mrr_at_100
value: 30.006
- type: mrr_at_1000
value: 30.086000000000002
- type: mrr_at_3
value: 26.863999999999997
- type: mrr_at_5
value: 27.899
- type: ndcg_at_1
value: 22.181
- type: ndcg_at_10
value: 31.64
- type: ndcg_at_100
value: 36.502
- type: ndcg_at_1000
value: 39.176
- type: ndcg_at_3
value: 26.901999999999997
- type: ndcg_at_5
value: 28.493000000000002
- type: precision_at_1
value: 22.181
- type: precision_at_10
value: 5.065
- type: precision_at_100
value: 0.8099999999999999
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 11.214
- type: precision_at_5
value: 7.689
- type: recall_at_1
value: 20.524
- type: recall_at_10
value: 43.29
- type: recall_at_100
value: 65.935
- type: recall_at_1000
value: 85.80600000000001
- type: recall_at_3
value: 30.276999999999997
- type: recall_at_5
value: 34.056999999999995
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 10.488999999999999
- type: map_at_10
value: 17.98
- type: map_at_100
value: 19.581
- type: map_at_1000
value: 19.739
- type: map_at_3
value: 15.054
- type: map_at_5
value: 16.439999999999998
- type: mrr_at_1
value: 23.192
- type: mrr_at_10
value: 33.831
- type: mrr_at_100
value: 34.833
- type: mrr_at_1000
value: 34.881
- type: mrr_at_3
value: 30.793
- type: mrr_at_5
value: 32.535
- type: ndcg_at_1
value: 23.192
- type: ndcg_at_10
value: 25.446
- type: ndcg_at_100
value: 31.948
- type: ndcg_at_1000
value: 35.028
- type: ndcg_at_3
value: 20.744
- type: ndcg_at_5
value: 22.233
- type: precision_at_1
value: 23.192
- type: precision_at_10
value: 8.026
- type: precision_at_100
value: 1.482
- type: precision_at_1000
value: 0.20500000000000002
- type: precision_at_3
value: 15.548
- type: precision_at_5
value: 11.87
- type: recall_at_1
value: 10.488999999999999
- type: recall_at_10
value: 30.865
- type: recall_at_100
value: 53.428
- type: recall_at_1000
value: 70.89
- type: recall_at_3
value: 19.245
- type: recall_at_5
value: 23.657
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 7.123
- type: map_at_10
value: 14.448
- type: map_at_100
value: 19.798
- type: map_at_1000
value: 21.082
- type: map_at_3
value: 10.815
- type: map_at_5
value: 12.422
- type: mrr_at_1
value: 53.5
- type: mrr_at_10
value: 63.117999999999995
- type: mrr_at_100
value: 63.617999999999995
- type: mrr_at_1000
value: 63.63799999999999
- type: mrr_at_3
value: 60.708
- type: mrr_at_5
value: 62.171
- type: ndcg_at_1
value: 42.125
- type: ndcg_at_10
value: 31.703
- type: ndcg_at_100
value: 35.935
- type: ndcg_at_1000
value: 43.173
- type: ndcg_at_3
value: 35.498000000000005
- type: ndcg_at_5
value: 33.645
- type: precision_at_1
value: 53.5
- type: precision_at_10
value: 25.025
- type: precision_at_100
value: 8.19
- type: precision_at_1000
value: 1.806
- type: precision_at_3
value: 39.083
- type: precision_at_5
value: 33.050000000000004
- type: recall_at_1
value: 7.123
- type: recall_at_10
value: 19.581
- type: recall_at_100
value: 42.061
- type: recall_at_1000
value: 65.879
- type: recall_at_3
value: 12.026
- type: recall_at_5
value: 14.846
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 41.24
- type: f1
value: 36.76174115773002
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 47.821999999999996
- type: map_at_10
value: 59.794000000000004
- type: map_at_100
value: 60.316
- type: map_at_1000
value: 60.34
- type: map_at_3
value: 57.202
- type: map_at_5
value: 58.823
- type: mrr_at_1
value: 51.485
- type: mrr_at_10
value: 63.709
- type: mrr_at_100
value: 64.144
- type: mrr_at_1000
value: 64.158
- type: mrr_at_3
value: 61.251
- type: mrr_at_5
value: 62.818
- type: ndcg_at_1
value: 51.485
- type: ndcg_at_10
value: 66.097
- type: ndcg_at_100
value: 68.37
- type: ndcg_at_1000
value: 68.916
- type: ndcg_at_3
value: 61.12800000000001
- type: ndcg_at_5
value: 63.885000000000005
- type: precision_at_1
value: 51.485
- type: precision_at_10
value: 8.956999999999999
- type: precision_at_100
value: 1.02
- type: precision_at_1000
value: 0.108
- type: precision_at_3
value: 24.807000000000002
- type: precision_at_5
value: 16.387999999999998
- type: recall_at_1
value: 47.821999999999996
- type: recall_at_10
value: 81.773
- type: recall_at_100
value: 91.731
- type: recall_at_1000
value: 95.649
- type: recall_at_3
value: 68.349
- type: recall_at_5
value: 75.093
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 15.662999999999998
- type: map_at_10
value: 25.726
- type: map_at_100
value: 27.581
- type: map_at_1000
value: 27.772000000000002
- type: map_at_3
value: 21.859
- type: map_at_5
value: 24.058
- type: mrr_at_1
value: 30.247
- type: mrr_at_10
value: 39.581
- type: mrr_at_100
value: 40.594
- type: mrr_at_1000
value: 40.647
- type: mrr_at_3
value: 37.166
- type: mrr_at_5
value: 38.585
- type: ndcg_at_1
value: 30.247
- type: ndcg_at_10
value: 32.934999999999995
- type: ndcg_at_100
value: 40.062999999999995
- type: ndcg_at_1000
value: 43.492
- type: ndcg_at_3
value: 28.871000000000002
- type: ndcg_at_5
value: 30.492
- type: precision_at_1
value: 30.247
- type: precision_at_10
value: 9.522
- type: precision_at_100
value: 1.645
- type: precision_at_1000
value: 0.22499999999999998
- type: precision_at_3
value: 19.136
- type: precision_at_5
value: 14.753
- type: recall_at_1
value: 15.662999999999998
- type: recall_at_10
value: 39.595
- type: recall_at_100
value: 66.49199999999999
- type: recall_at_1000
value: 87.19
- type: recall_at_3
value: 26.346999999999998
- type: recall_at_5
value: 32.423
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 30.176
- type: map_at_10
value: 42.684
- type: map_at_100
value: 43.582
- type: map_at_1000
value: 43.668
- type: map_at_3
value: 39.964
- type: map_at_5
value: 41.589
- type: mrr_at_1
value: 60.351
- type: mrr_at_10
value: 67.669
- type: mrr_at_100
value: 68.089
- type: mrr_at_1000
value: 68.111
- type: mrr_at_3
value: 66.144
- type: mrr_at_5
value: 67.125
- type: ndcg_at_1
value: 60.351
- type: ndcg_at_10
value: 51.602000000000004
- type: ndcg_at_100
value: 55.186
- type: ndcg_at_1000
value: 56.96
- type: ndcg_at_3
value: 47.251
- type: ndcg_at_5
value: 49.584
- type: precision_at_1
value: 60.351
- type: precision_at_10
value: 10.804
- type: precision_at_100
value: 1.3639999999999999
- type: precision_at_1000
value: 0.16
- type: precision_at_3
value: 29.561
- type: precision_at_5
value: 19.581
- type: recall_at_1
value: 30.176
- type: recall_at_10
value: 54.018
- type: recall_at_100
value: 68.22399999999999
- type: recall_at_1000
value: 79.97999999999999
- type: recall_at_3
value: 44.342
- type: recall_at_5
value: 48.953
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 71.28320000000001
- type: ap
value: 65.20730065157146
- type: f1
value: 71.19193683354304
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 19.686
- type: map_at_10
value: 31.189
- type: map_at_100
value: 32.368
- type: map_at_1000
value: 32.43
- type: map_at_3
value: 27.577
- type: map_at_5
value: 29.603
- type: mrr_at_1
value: 20.201
- type: mrr_at_10
value: 31.762
- type: mrr_at_100
value: 32.882
- type: mrr_at_1000
value: 32.937
- type: mrr_at_3
value: 28.177999999999997
- type: mrr_at_5
value: 30.212
- type: ndcg_at_1
value: 20.215
- type: ndcg_at_10
value: 37.730999999999995
- type: ndcg_at_100
value: 43.501
- type: ndcg_at_1000
value: 45.031
- type: ndcg_at_3
value: 30.336000000000002
- type: ndcg_at_5
value: 33.961000000000006
- type: precision_at_1
value: 20.215
- type: precision_at_10
value: 6.036
- type: precision_at_100
value: 0.895
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 13.028
- type: precision_at_5
value: 9.633
- type: recall_at_1
value: 19.686
- type: recall_at_10
value: 57.867999999999995
- type: recall_at_100
value: 84.758
- type: recall_at_1000
value: 96.44500000000001
- type: recall_at_3
value: 37.726
- type: recall_at_5
value: 46.415
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 89.76972184222525
- type: f1
value: 89.11949030406099
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 55.57455540355677
- type: f1
value: 39.344920096224506
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 63.772696704774724
- type: f1
value: 60.70041499812703
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 69.16274377942166
- type: f1
value: 68.06744012208019
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 31.822626760555522
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 27.98469036402807
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 30.911144124209166
- type: mrr
value: 31.950116175672292
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.157
- type: map_at_10
value: 11.086
- type: map_at_100
value: 13.927
- type: map_at_1000
value: 15.226999999999999
- type: map_at_3
value: 8.525
- type: map_at_5
value: 9.767000000000001
- type: mrr_at_1
value: 43.344
- type: mrr_at_10
value: 51.646
- type: mrr_at_100
value: 52.212
- type: mrr_at_1000
value: 52.263999999999996
- type: mrr_at_3
value: 50.052
- type: mrr_at_5
value: 51.166
- type: ndcg_at_1
value: 41.949999999999996
- type: ndcg_at_10
value: 30.552
- type: ndcg_at_100
value: 28.409000000000002
- type: ndcg_at_1000
value: 37.328
- type: ndcg_at_3
value: 37.114000000000004
- type: ndcg_at_5
value: 34.117999999999995
- type: precision_at_1
value: 43.344
- type: precision_at_10
value: 22.198
- type: precision_at_100
value: 7.234999999999999
- type: precision_at_1000
value: 2.013
- type: precision_at_3
value: 34.675
- type: precision_at_5
value: 29.04
- type: recall_at_1
value: 5.157
- type: recall_at_10
value: 13.999
- type: recall_at_100
value: 28.796
- type: recall_at_1000
value: 60.84
- type: recall_at_3
value: 9.603
- type: recall_at_5
value: 11.638
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 33.024
- type: map_at_10
value: 47.229
- type: map_at_100
value: 48.195
- type: map_at_1000
value: 48.229
- type: map_at_3
value: 43.356
- type: map_at_5
value: 45.857
- type: mrr_at_1
value: 36.848
- type: mrr_at_10
value: 49.801
- type: mrr_at_100
value: 50.532999999999994
- type: mrr_at_1000
value: 50.556
- type: mrr_at_3
value: 46.605999999999995
- type: mrr_at_5
value: 48.735
- type: ndcg_at_1
value: 36.848
- type: ndcg_at_10
value: 54.202
- type: ndcg_at_100
value: 58.436
- type: ndcg_at_1000
value: 59.252
- type: ndcg_at_3
value: 47.082
- type: ndcg_at_5
value: 51.254
- type: precision_at_1
value: 36.848
- type: precision_at_10
value: 8.636000000000001
- type: precision_at_100
value: 1.105
- type: precision_at_1000
value: 0.11800000000000001
- type: precision_at_3
value: 21.08
- type: precision_at_5
value: 15.07
- type: recall_at_1
value: 33.024
- type: recall_at_10
value: 72.699
- type: recall_at_100
value: 91.387
- type: recall_at_1000
value: 97.482
- type: recall_at_3
value: 54.604
- type: recall_at_5
value: 64.224
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 69.742
- type: map_at_10
value: 83.43
- type: map_at_100
value: 84.09400000000001
- type: map_at_1000
value: 84.113
- type: map_at_3
value: 80.464
- type: map_at_5
value: 82.356
- type: mrr_at_1
value: 80.31
- type: mrr_at_10
value: 86.629
- type: mrr_at_100
value: 86.753
- type: mrr_at_1000
value: 86.75399999999999
- type: mrr_at_3
value: 85.59
- type: mrr_at_5
value: 86.346
- type: ndcg_at_1
value: 80.28999999999999
- type: ndcg_at_10
value: 87.323
- type: ndcg_at_100
value: 88.682
- type: ndcg_at_1000
value: 88.812
- type: ndcg_at_3
value: 84.373
- type: ndcg_at_5
value: 86.065
- type: precision_at_1
value: 80.28999999999999
- type: precision_at_10
value: 13.239999999999998
- type: precision_at_100
value: 1.521
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 36.827
- type: precision_at_5
value: 24.272
- type: recall_at_1
value: 69.742
- type: recall_at_10
value: 94.645
- type: recall_at_100
value: 99.375
- type: recall_at_1000
value: 99.97200000000001
- type: recall_at_3
value: 86.18400000000001
- type: recall_at_5
value: 90.958
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 50.52987829115787
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 56.73289360025561
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.473
- type: map_at_10
value: 10.953
- type: map_at_100
value: 12.842
- type: map_at_1000
value: 13.122
- type: map_at_3
value: 7.863
- type: map_at_5
value: 9.376
- type: mrr_at_1
value: 22
- type: mrr_at_10
value: 32.639
- type: mrr_at_100
value: 33.658
- type: mrr_at_1000
value: 33.727000000000004
- type: mrr_at_3
value: 29.232999999999997
- type: mrr_at_5
value: 31.373
- type: ndcg_at_1
value: 22
- type: ndcg_at_10
value: 18.736
- type: ndcg_at_100
value: 26.209
- type: ndcg_at_1000
value: 31.427
- type: ndcg_at_3
value: 17.740000000000002
- type: ndcg_at_5
value: 15.625
- type: precision_at_1
value: 22
- type: precision_at_10
value: 9.700000000000001
- type: precision_at_100
value: 2.052
- type: precision_at_1000
value: 0.331
- type: precision_at_3
value: 16.533
- type: precision_at_5
value: 13.74
- type: recall_at_1
value: 4.473
- type: recall_at_10
value: 19.627
- type: recall_at_100
value: 41.63
- type: recall_at_1000
value: 67.173
- type: recall_at_3
value: 10.067
- type: recall_at_5
value: 13.927
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 83.27314719076216
- type: cos_sim_spearman
value: 76.39295628838427
- type: euclidean_pearson
value: 80.38849931283136
- type: euclidean_spearman
value: 76.39295685543406
- type: manhattan_pearson
value: 80.28382869912794
- type: manhattan_spearman
value: 76.28362123227473
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 82.36858074786585
- type: cos_sim_spearman
value: 72.81528838052759
- type: euclidean_pearson
value: 78.83576324502302
- type: euclidean_spearman
value: 72.8152880167174
- type: manhattan_pearson
value: 78.81284819385367
- type: manhattan_spearman
value: 72.76091465928633
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 81.08132718998489
- type: cos_sim_spearman
value: 82.00988939015869
- type: euclidean_pearson
value: 81.02243847451692
- type: euclidean_spearman
value: 82.00992010206836
- type: manhattan_pearson
value: 80.97749306075134
- type: manhattan_spearman
value: 81.97800195109437
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 80.83442047735284
- type: cos_sim_spearman
value: 77.50930325127395
- type: euclidean_pearson
value: 79.34941050260747
- type: euclidean_spearman
value: 77.50930324686452
- type: manhattan_pearson
value: 79.28081079289419
- type: manhattan_spearman
value: 77.42311420628891
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 85.70132781546333
- type: cos_sim_spearman
value: 86.58415907086527
- type: euclidean_pearson
value: 85.63892869817083
- type: euclidean_spearman
value: 86.58415907086527
- type: manhattan_pearson
value: 85.56054168116064
- type: manhattan_spearman
value: 86.50292824173809
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 81.48780971731246
- type: cos_sim_spearman
value: 82.79818891852887
- type: euclidean_pearson
value: 81.93990926192305
- type: euclidean_spearman
value: 82.79818891852887
- type: manhattan_pearson
value: 81.97538189750966
- type: manhattan_spearman
value: 82.88761825524075
- 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: 88.4989925729811
- type: cos_sim_spearman
value: 88.47370962620529
- type: euclidean_pearson
value: 88.2312980339956
- type: euclidean_spearman
value: 88.47370962620529
- type: manhattan_pearson
value: 88.15570940509707
- type: manhattan_spearman
value: 88.36900000569275
- 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: 63.90740805015967
- type: cos_sim_spearman
value: 63.968359064784444
- type: euclidean_pearson
value: 64.67928113832794
- type: euclidean_spearman
value: 63.968359064784444
- type: manhattan_pearson
value: 63.92597430517486
- type: manhattan_spearman
value: 63.31372007361158
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 82.56902991447632
- type: cos_sim_spearman
value: 83.16262853325924
- type: euclidean_pearson
value: 83.47693312869555
- type: euclidean_spearman
value: 83.16266829656969
- type: manhattan_pearson
value: 83.51067558632968
- type: manhattan_spearman
value: 83.25136388306153
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 80.1518040851234
- type: mrr
value: 94.49083052024228
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 50.661
- type: map_at_10
value: 59.816
- type: map_at_100
value: 60.412
- type: map_at_1000
value: 60.446999999999996
- type: map_at_3
value: 56.567
- type: map_at_5
value: 58.45
- type: mrr_at_1
value: 53.667
- type: mrr_at_10
value: 61.342
- type: mrr_at_100
value: 61.8
- type: mrr_at_1000
value: 61.836
- type: mrr_at_3
value: 59.111000000000004
- type: mrr_at_5
value: 60.411
- type: ndcg_at_1
value: 53.667
- type: ndcg_at_10
value: 64.488
- type: ndcg_at_100
value: 67.291
- type: ndcg_at_1000
value: 68.338
- type: ndcg_at_3
value: 59.101000000000006
- type: ndcg_at_5
value: 61.812999999999995
- type: precision_at_1
value: 53.667
- type: precision_at_10
value: 8.799999999999999
- type: precision_at_100
value: 1.0330000000000001
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 23
- type: precision_at_5
value: 15.6
- type: recall_at_1
value: 50.661
- type: recall_at_10
value: 77.422
- type: recall_at_100
value: 90.667
- type: recall_at_1000
value: 99
- type: recall_at_3
value: 63.144
- type: recall_at_5
value: 69.817
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.81287128712871
- type: cos_sim_ap
value: 94.91998708151321
- type: cos_sim_f1
value: 90.36206017338093
- type: cos_sim_precision
value: 92.19562955254943
- type: cos_sim_recall
value: 88.6
- type: dot_accuracy
value: 99.81287128712871
- type: dot_ap
value: 94.91998708151321
- type: dot_f1
value: 90.36206017338093
- type: dot_precision
value: 92.19562955254943
- type: dot_recall
value: 88.6
- type: euclidean_accuracy
value: 99.81287128712871
- type: euclidean_ap
value: 94.9199944407842
- type: euclidean_f1
value: 90.36206017338093
- type: euclidean_precision
value: 92.19562955254943
- type: euclidean_recall
value: 88.6
- type: manhattan_accuracy
value: 99.8108910891089
- type: manhattan_ap
value: 94.83783896670839
- type: manhattan_f1
value: 90.27989821882952
- type: manhattan_precision
value: 91.91709844559585
- type: manhattan_recall
value: 88.7
- type: max_accuracy
value: 99.81287128712871
- type: max_ap
value: 94.9199944407842
- type: max_f1
value: 90.36206017338093
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 56.165546412944714
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 34.19894321136813
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 50.02944308369115
- type: mrr
value: 50.63055714710127
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.3377433394579
- type: cos_sim_spearman
value: 30.877807383527983
- type: dot_pearson
value: 31.337752376327405
- type: dot_spearman
value: 30.877807383527983
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.20500000000000002
- type: map_at_10
value: 1.6099999999999999
- type: map_at_100
value: 8.635
- type: map_at_1000
value: 20.419999999999998
- type: map_at_3
value: 0.59
- type: map_at_5
value: 0.9249999999999999
- type: mrr_at_1
value: 80
- type: mrr_at_10
value: 88.452
- type: mrr_at_100
value: 88.452
- type: mrr_at_1000
value: 88.452
- type: mrr_at_3
value: 87.667
- type: mrr_at_5
value: 88.167
- type: ndcg_at_1
value: 77
- type: ndcg_at_10
value: 67.079
- type: ndcg_at_100
value: 49.937
- type: ndcg_at_1000
value: 44.031
- type: ndcg_at_3
value: 73.123
- type: ndcg_at_5
value: 70.435
- type: precision_at_1
value: 80
- type: precision_at_10
value: 70.39999999999999
- type: precision_at_100
value: 51.25999999999999
- type: precision_at_1000
value: 19.698
- type: precision_at_3
value: 78
- type: precision_at_5
value: 75.2
- type: recall_at_1
value: 0.20500000000000002
- type: recall_at_10
value: 1.8399999999999999
- type: recall_at_100
value: 11.971
- type: recall_at_1000
value: 41.042
- type: recall_at_3
value: 0.632
- type: recall_at_5
value: 1.008
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.183
- type: map_at_10
value: 9.58
- type: map_at_100
value: 16.27
- type: map_at_1000
value: 17.977999999999998
- type: map_at_3
value: 4.521
- type: map_at_5
value: 6.567
- type: mrr_at_1
value: 12.245000000000001
- type: mrr_at_10
value: 33.486
- type: mrr_at_100
value: 34.989
- type: mrr_at_1000
value: 34.989
- type: mrr_at_3
value: 28.231
- type: mrr_at_5
value: 31.701
- type: ndcg_at_1
value: 9.184000000000001
- type: ndcg_at_10
value: 22.133
- type: ndcg_at_100
value: 36.882
- type: ndcg_at_1000
value: 48.487
- type: ndcg_at_3
value: 18.971
- type: ndcg_at_5
value: 20.107
- type: precision_at_1
value: 12.245000000000001
- type: precision_at_10
value: 21.837
- type: precision_at_100
value: 8.265
- type: precision_at_1000
value: 1.606
- type: precision_at_3
value: 22.448999999999998
- type: precision_at_5
value: 23.265
- type: recall_at_1
value: 1.183
- type: recall_at_10
value: 17.01
- type: recall_at_100
value: 51.666000000000004
- type: recall_at_1000
value: 87.56
- type: recall_at_3
value: 6.0280000000000005
- type: recall_at_5
value: 9.937999999999999
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 70.6812
- type: ap
value: 13.776718216594006
- type: f1
value: 54.14269849375851
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 57.3372948500283
- type: f1
value: 57.39381291375
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 41.49681931876514
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 84.65756690707516
- type: cos_sim_ap
value: 70.06190309300052
- type: cos_sim_f1
value: 65.49254432311848
- type: cos_sim_precision
value: 59.00148085466469
- type: cos_sim_recall
value: 73.58839050131925
- type: dot_accuracy
value: 84.65756690707516
- type: dot_ap
value: 70.06187157356817
- type: dot_f1
value: 65.49254432311848
- type: dot_precision
value: 59.00148085466469
- type: dot_recall
value: 73.58839050131925
- type: euclidean_accuracy
value: 84.65756690707516
- type: euclidean_ap
value: 70.06190439203068
- type: euclidean_f1
value: 65.49254432311848
- type: euclidean_precision
value: 59.00148085466469
- type: euclidean_recall
value: 73.58839050131925
- type: manhattan_accuracy
value: 84.58604041246946
- type: manhattan_ap
value: 69.93103436414437
- type: manhattan_f1
value: 65.48780487804878
- type: manhattan_precision
value: 60.8843537414966
- type: manhattan_recall
value: 70.84432717678101
- type: max_accuracy
value: 84.65756690707516
- type: max_ap
value: 70.06190439203068
- type: max_f1
value: 65.49254432311848
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.78410369852912
- type: cos_sim_ap
value: 85.45825760499459
- type: cos_sim_f1
value: 77.73455035163849
- type: cos_sim_precision
value: 75.5966239813737
- type: cos_sim_recall
value: 79.9969202340622
- type: dot_accuracy
value: 88.78410369852912
- type: dot_ap
value: 85.45825790635979
- type: dot_f1
value: 77.73455035163849
- type: dot_precision
value: 75.5966239813737
- type: dot_recall
value: 79.9969202340622
- type: euclidean_accuracy
value: 88.78410369852912
- type: euclidean_ap
value: 85.45826341243391
- type: euclidean_f1
value: 77.73455035163849
- type: euclidean_precision
value: 75.5966239813737
- type: euclidean_recall
value: 79.9969202340622
- type: manhattan_accuracy
value: 88.7026041060271
- type: manhattan_ap
value: 85.43182830781821
- type: manhattan_f1
value: 77.61487303506651
- type: manhattan_precision
value: 76.20955773226477
- type: manhattan_recall
value: 79.07299045272559
- type: max_accuracy
value: 88.78410369852912
- type: max_ap
value: 85.45826341243391
- type: max_f1
value: 77.73455035163849