Hugging Face Space: iwashuman0405/api-rag
Author: iwashuman0405
SDK: docker
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags: feature-extraction
sentence-similarity
mteb
transformers
transformers.js
model-index: name: epoch_0_model
results: task: type: Classification
dataset: type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics: type: accuracy
value: 76.8507462686567
type: ap
value: 40.592189159090495
type: f1
value: 71.01634655512476
task: type: Classification
dataset: type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics: type: accuracy
value: 91.51892500000001
type: ap
value: 88.50346762975335
type: f1
value: 91.50342077459624
task: type: Classification
dataset: type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics: type: accuracy
value: 47.364
type: f1
value: 46.72708080922794
task: type: Retrieval
dataset: type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics: type: map_at_1
value: 25.178
type: map_at_10
value: 40.244
type: map_at_100
value: 41.321999999999996
type: map_at_1000
value: 41.331
type: map_at_3
value: 35.016999999999996
type: map_at_5
value: 37.99
type: mrr_at_1
value: 25.605
type: mrr_at_10
value: 40.422000000000004
type: mrr_at_100
value: 41.507
type: mrr_at_1000
value: 41.516
type: mrr_at_3
value: 35.23
type: mrr_at_5
value: 38.15
type: ndcg_at_1
value: 25.178
type: ndcg_at_10
value: 49.258
type: ndcg_at_100
value: 53.776
type: ndcg_at_1000
value: 53.995000000000005
type: ndcg_at_3
value: 38.429
type: ndcg_at_5
value: 43.803
type: precision_at_1
value: 25.178
type: precision_at_10
value: 7.831
type: precision_at_100
value: 0.979
type: precision_at_1000
value: 0.1
type: precision_at_3
value: 16.121
type: precision_at_5
value: 12.29
type: recall_at_1
value: 25.178
type: recall_at_10
value: 78.307
type: recall_at_100
value: 97.866
type: recall_at_1000
value: 99.57300000000001
type: recall_at_3
value: 48.364000000000004
type: recall_at_5
value: 61.451
task: type: Clustering
dataset: type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics: type: v_measure
value: 45.93034494751465
task: type: Clustering
dataset: type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics: type: v_measure
value: 36.64579480054327
task: type: Reranking
dataset: type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics: type: map
value: 60.601310529222054
type: mrr
value: 75.04484896451656
task: type: STS
dataset: type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics: type: cos_sim_pearson
value: 88.57797718095814
type: cos_sim_spearman
value: 86.47064499110101
type: euclidean_pearson
value: 87.4559602783142
type: euclidean_spearman
value: 86.47064499110101
type: manhattan_pearson
value: 87.7232764230245
type: manhattan_spearman
value: 86.91222131777742
task: type: Classification
dataset: type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics: type: accuracy
value: 84.5422077922078
type: f1
value: 84.47657456950589
task: type: Clustering
dataset: type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics: type: v_measure
value: 38.48953561974464
task: type: Clustering
dataset: type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics: type: v_measure
value: 32.75995857510105
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 30.008000000000003
type: map_at_10
value: 39.51
type: map_at_100
value: 40.841
type: map_at_1000
value: 40.973
type: map_at_3
value: 36.248999999999995
type: map_at_5
value: 38.096999999999994
type: mrr_at_1
value: 36.481
type: mrr_at_10
value: 44.818000000000005
type: mrr_at_100
value: 45.64
type: mrr_at_1000
value: 45.687
type: mrr_at_3
value: 42.036
type: mrr_at_5
value: 43.782
type: ndcg_at_1
value: 36.481
type: ndcg_at_10
value: 45.152
type: ndcg_at_100
value: 50.449
type: ndcg_at_1000
value: 52.76499999999999
type: ndcg_at_3
value: 40.161
type: ndcg_at_5
value: 42.577999999999996
type: precision_at_1
value: 36.481
type: precision_at_10
value: 8.369
type: precision_at_100
value: 1.373
type: precision_at_1000
value: 0.186
type: precision_at_3
value: 18.693
type: precision_at_5
value: 13.533999999999999
type: recall_at_1
value: 30.008000000000003
type: recall_at_10
value: 56.108999999999995
type: recall_at_100
value: 78.55499999999999
type: recall_at_1000
value: 93.659
type: recall_at_3
value: 41.754999999999995
type: recall_at_5
value: 48.296
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 30.262
type: map_at_10
value: 40.139
type: map_at_100
value: 41.394
type: map_at_1000
value: 41.526
type: map_at_3
value: 37.155
type: map_at_5
value: 38.785
type: mrr_at_1
value: 38.153
type: mrr_at_10
value: 46.369
type: mrr_at_100
value: 47.072
type: mrr_at_1000
value: 47.111999999999995
type: mrr_at_3
value: 44.268
type: mrr_at_5
value: 45.389
type: ndcg_at_1
value: 38.153
type: ndcg_at_10
value: 45.925
type: ndcg_at_100
value: 50.394000000000005
type: ndcg_at_1000
value: 52.37500000000001
type: ndcg_at_3
value: 41.754000000000005
type: ndcg_at_5
value: 43.574
type: precision_at_1
value: 38.153
type: precision_at_10
value: 8.796
type: precision_at_100
value: 1.432
type: precision_at_1000
value: 0.189
type: precision_at_3
value: 20.318
type: precision_at_5
value: 14.395
type: recall_at_1
value: 30.262
type: recall_at_10
value: 55.72200000000001
type: recall_at_100
value: 74.97500000000001
type: recall_at_1000
value: 87.342
type: recall_at_3
value: 43.129
type: recall_at_5
value: 48.336
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 39.951
type: map_at_10
value: 51.248000000000005
type: map_at_100
value: 52.188
type: map_at_1000
value: 52.247
type: map_at_3
value: 48.211
type: map_at_5
value: 49.797000000000004
type: mrr_at_1
value: 45.329
type: mrr_at_10
value: 54.749
type: mrr_at_100
value: 55.367999999999995
type: mrr_at_1000
value: 55.400000000000006
type: mrr_at_3
value: 52.382
type: mrr_at_5
value: 53.649
type: ndcg_at_1
value: 45.329
type: ndcg_at_10
value: 56.847
type: ndcg_at_100
value: 60.738
type: ndcg_at_1000
value: 61.976
type: ndcg_at_3
value: 51.59
type: ndcg_at_5
value: 53.915
type: precision_at_1
value: 45.329
type: precision_at_10
value: 8.959
type: precision_at_100
value: 1.187
type: precision_at_1000
value: 0.134
type: precision_at_3
value: 22.612
type: precision_at_5
value: 15.273
type: recall_at_1
value: 39.951
type: recall_at_10
value: 70.053
type: recall_at_100
value: 86.996
type: recall_at_1000
value: 95.707
type: recall_at_3
value: 56.032000000000004
type: recall_at_5
value: 61.629999999999995
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 25.566
type: map_at_10
value: 33.207
type: map_at_100
value: 34.166000000000004
type: map_at_1000
value: 34.245
type: map_at_3
value: 30.94
type: map_at_5
value: 32.01
type: mrr_at_1
value: 27.345000000000002
type: mrr_at_10
value: 35.193000000000005
type: mrr_at_100
value: 35.965
type: mrr_at_1000
value: 36.028999999999996
type: mrr_at_3
value: 32.806000000000004
type: mrr_at_5
value: 34.021
type: ndcg_at_1
value: 27.345000000000002
type: ndcg_at_10
value: 37.891999999999996
type: ndcg_at_100
value: 42.664
type: ndcg_at_1000
value: 44.757000000000005
type: ndcg_at_3
value: 33.123000000000005
type: ndcg_at_5
value: 35.035
type: precision_at_1
value: 27.345000000000002
type: precision_at_10
value: 5.763
type: precision_at_100
value: 0.859
type: precision_at_1000
value: 0.108
type: precision_at_3
value: 13.71
type: precision_at_5
value: 9.401
type: recall_at_1
value: 25.566
type: recall_at_10
value: 50.563
type: recall_at_100
value: 72.86399999999999
type: recall_at_1000
value: 88.68599999999999
type: recall_at_3
value: 37.43
type: recall_at_5
value: 41.894999999999996
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 16.663
type: map_at_10
value: 23.552
type: map_at_100
value: 24.538
type: map_at_1000
value: 24.661
type: map_at_3
value: 21.085
type: map_at_5
value: 22.391
type: mrr_at_1
value: 20.025000000000002
type: mrr_at_10
value: 27.643
type: mrr_at_100
value: 28.499999999999996
type: mrr_at_1000
value: 28.582
type: mrr_at_3
value: 25.083
type: mrr_at_5
value: 26.544
type: ndcg_at_1
value: 20.025000000000002
type: ndcg_at_10
value: 28.272000000000002
type: ndcg_at_100
value: 33.353
type: ndcg_at_1000
value: 36.454
type: ndcg_at_3
value: 23.579
type: ndcg_at_5
value: 25.685000000000002
type: precision_at_1
value: 20.025000000000002
type: precision_at_10
value: 5.187
type: precision_at_100
value: 0.897
type: precision_at_1000
value: 0.13
type: precision_at_3
value: 10.987
type: precision_at_5
value: 8.06
type: recall_at_1
value: 16.663
type: recall_at_10
value: 38.808
type: recall_at_100
value: 61.305
type: recall_at_1000
value: 83.571
type: recall_at_3
value: 25.907999999999998
type: recall_at_5
value: 31.214
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 27.695999999999998
type: map_at_10
value: 37.018
type: map_at_100
value: 38.263000000000005
type: map_at_1000
value: 38.371
type: map_at_3
value: 34.226
type: map_at_5
value: 35.809999999999995
type: mrr_at_1
value: 32.916000000000004
type: mrr_at_10
value: 42.067
type: mrr_at_100
value: 42.925000000000004
type: mrr_at_1000
value: 42.978
type: mrr_at_3
value: 39.637
type: mrr_at_5
value: 41.134
type: ndcg_at_1
value: 32.916000000000004
type: ndcg_at_10
value: 42.539
type: ndcg_at_100
value: 47.873
type: ndcg_at_1000
value: 50.08200000000001
type: ndcg_at_3
value: 37.852999999999994
type: ndcg_at_5
value: 40.201
type: precision_at_1
value: 32.916000000000004
type: precision_at_10
value: 7.5840000000000005
type: precision_at_100
value: 1.199
type: precision_at_1000
value: 0.155
type: precision_at_3
value: 17.485
type: precision_at_5
value: 12.512
type: recall_at_1
value: 27.695999999999998
type: recall_at_10
value: 53.638
type: recall_at_100
value: 76.116
type: recall_at_1000
value: 91.069
type: recall_at_3
value: 41.13
type: recall_at_5
value: 46.872
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 24.108
type: map_at_10
value: 33.372
type: map_at_100
value: 34.656
type: map_at_1000
value: 34.768
type: map_at_3
value: 30.830999999999996
type: map_at_5
value: 32.204
type: mrr_at_1
value: 29.110000000000003
type: mrr_at_10
value: 37.979
type: mrr_at_100
value: 38.933
type: mrr_at_1000
value: 38.988
type: mrr_at_3
value: 35.731
type: mrr_at_5
value: 36.963
type: ndcg_at_1
value: 29.110000000000003
type: ndcg_at_10
value: 38.635000000000005
type: ndcg_at_100
value: 44.324999999999996
type: ndcg_at_1000
value: 46.747
type: ndcg_at_3
value: 34.37
type: ndcg_at_5
value: 36.228
type: precision_at_1
value: 29.110000000000003
type: precision_at_10
value: 6.963
type: precision_at_100
value: 1.146
type: precision_at_1000
value: 0.152
type: precision_at_3
value: 16.400000000000002
type: precision_at_5
value: 11.552999999999999
type: recall_at_1
value: 24.108
type: recall_at_10
value: 49.597
type: recall_at_100
value: 73.88900000000001
type: recall_at_1000
value: 90.62400000000001
type: recall_at_3
value: 37.662
type: recall_at_5
value: 42.565
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 25.00791666666667
type: map_at_10
value: 33.287749999999996
type: map_at_100
value: 34.41141666666667
type: map_at_1000
value: 34.52583333333333
type: map_at_3
value: 30.734416666666668
type: map_at_5
value: 32.137166666666666
type: mrr_at_1
value: 29.305666666666664
type: mrr_at_10
value: 37.22966666666666
type: mrr_at_100
value: 38.066583333333334
type: mrr_at_1000
value: 38.12616666666667
type: mrr_at_3
value: 34.92275
type: mrr_at_5
value: 36.23333333333334
type: ndcg_at_1
value: 29.305666666666664
type: ndcg_at_10
value: 38.25533333333333
type: ndcg_at_100
value: 43.25266666666666
type: ndcg_at_1000
value: 45.63583333333334
type: ndcg_at_3
value: 33.777166666666666
type: ndcg_at_5
value: 35.85
type: precision_at_1
value: 29.305666666666664
type: precision_at_10
value: 6.596416666666667
type: precision_at_100
value: 1.0784166666666668
type: precision_at_1000
value: 0.14666666666666664
type: precision_at_3
value: 15.31075
type: precision_at_5
value: 10.830916666666667
type: recall_at_1
value: 25.00791666666667
type: recall_at_10
value: 49.10933333333333
type: recall_at_100
value: 71.09216666666667
type: recall_at_1000
value: 87.77725000000001
type: recall_at_3
value: 36.660916666666665
type: recall_at_5
value: 41.94149999999999
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 23.521
type: map_at_10
value: 30.043
type: map_at_100
value: 30.936000000000003
type: map_at_1000
value: 31.022
type: map_at_3
value: 27.926000000000002
type: map_at_5
value: 29.076999999999998
type: mrr_at_1
value: 26.227
type: mrr_at_10
value: 32.822
type: mrr_at_100
value: 33.61
type: mrr_at_1000
value: 33.672000000000004
type: mrr_at_3
value: 30.776999999999997
type: mrr_at_5
value: 31.866
type: ndcg_at_1
value: 26.227
type: ndcg_at_10
value: 34.041
type: ndcg_at_100
value: 38.394
type: ndcg_at_1000
value: 40.732
type: ndcg_at_3
value: 30.037999999999997
type: ndcg_at_5
value: 31.845000000000002
type: precision_at_1
value: 26.227
type: precision_at_10
value: 5.244999999999999
type: precision_at_100
value: 0.808
type: precision_at_1000
value: 0.107
type: precision_at_3
value: 12.679000000000002
type: precision_at_5
value: 8.773
type: recall_at_1
value: 23.521
type: recall_at_10
value: 43.633
type: recall_at_100
value: 63.126000000000005
type: recall_at_1000
value: 80.765
type: recall_at_3
value: 32.614
type: recall_at_5
value: 37.15
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 16.236
type: map_at_10
value: 22.898
type: map_at_100
value: 23.878
type: map_at_1000
value: 24.009
type: map_at_3
value: 20.87
type: map_at_5
value: 22.025
type: mrr_at_1
value: 19.339000000000002
type: mrr_at_10
value: 26.382
type: mrr_at_100
value: 27.245
type: mrr_at_1000
value: 27.33
type: mrr_at_3
value: 24.386
type: mrr_at_5
value: 25.496000000000002
type: ndcg_at_1
value: 19.339000000000002
type: ndcg_at_10
value: 27.139999999999997
type: ndcg_at_100
value: 31.944
type: ndcg_at_1000
value: 35.077999999999996
type: ndcg_at_3
value: 23.424
type: ndcg_at_5
value: 25.188
type: precision_at_1
value: 19.339000000000002
type: precision_at_10
value: 4.8309999999999995
type: precision_at_100
value: 0.845
type: precision_at_1000
value: 0.128
type: precision_at_3
value: 10.874
type: precision_at_5
value: 7.825
type: recall_at_1
value: 16.236
type: recall_at_10
value: 36.513
type: recall_at_100
value: 57.999
type: recall_at_1000
value: 80.512
type: recall_at_3
value: 26.179999999999996
type: recall_at_5
value: 30.712
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 24.11
type: map_at_10
value: 31.566
type: map_at_100
value: 32.647
type: map_at_1000
value: 32.753
type: map_at_3
value: 29.24
type: map_at_5
value: 30.564999999999998
type: mrr_at_1
value: 28.265
type: mrr_at_10
value: 35.504000000000005
type: mrr_at_100
value: 36.436
type: mrr_at_1000
value: 36.503
type: mrr_at_3
value: 33.349000000000004
type: mrr_at_5
value: 34.622
type: ndcg_at_1
value: 28.265
type: ndcg_at_10
value: 36.192
type: ndcg_at_100
value: 41.388000000000005
type: ndcg_at_1000
value: 43.948
type: ndcg_at_3
value: 31.959
type: ndcg_at_5
value: 33.998
type: precision_at_1
value: 28.265
type: precision_at_10
value: 5.989
type: precision_at_100
value: 0.9650000000000001
type: precision_at_1000
value: 0.13
type: precision_at_3
value: 14.335
type: precision_at_5
value: 10.112
type: recall_at_1
value: 24.11
type: recall_at_10
value: 46.418
type: recall_at_100
value: 69.314
type: recall_at_1000
value: 87.397
type: recall_at_3
value: 34.724
type: recall_at_5
value: 39.925
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 22.091
type: map_at_10
value: 29.948999999999998
type: map_at_100
value: 31.502000000000002
type: map_at_1000
value: 31.713
type: map_at_3
value: 27.464
type: map_at_5
value: 28.968
type: mrr_at_1
value: 26.482
type: mrr_at_10
value: 34.009
type: mrr_at_100
value: 35.081
type: mrr_at_1000
value: 35.138000000000005
type: mrr_at_3
value: 31.785000000000004
type: mrr_at_5
value: 33.178999999999995
type: ndcg_at_1
value: 26.482
type: ndcg_at_10
value: 35.008
type: ndcg_at_100
value: 41.272999999999996
type: ndcg_at_1000
value: 43.972
type: ndcg_at_3
value: 30.804
type: ndcg_at_5
value: 33.046
type: precision_at_1
value: 26.482
type: precision_at_10
value: 6.462
type: precision_at_100
value: 1.431
type: precision_at_1000
value: 0.22899999999999998
type: precision_at_3
value: 14.360999999999999
type: precision_at_5
value: 10.474
type: recall_at_1
value: 22.091
type: recall_at_10
value: 45.125
type: recall_at_100
value: 72.313
type: recall_at_1000
value: 89.503
type: recall_at_3
value: 33.158
type: recall_at_5
value: 39.086999999999996
task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 19.883
type: map_at_10
value: 26.951000000000004
type: map_at_100
value: 27.927999999999997
type: map_at_1000
value: 28.022000000000002
type: map_at_3
value: 24.616
type: map_at_5
value: 25.917
type: mrr_at_1
value: 21.996
type: mrr_at_10
value: 29.221000000000004
type: mrr_at_100
value: 30.024
type: mrr_at_1000
value: 30.095
type: mrr_at_3
value: 26.833000000000002
type: mrr_at_5
value: 28.155
type: ndcg_at_1
value: 21.996
type: ndcg_at_10
value: 31.421
type: ndcg_at_100
value: 36.237
type: ndcg_at_1000
value: 38.744
type: ndcg_at_3
value: 26.671
type: ndcg_at_5
value: 28.907
type: precision_at_1
value: 21.996
type: precision_at_10
value: 5.009
type: precision_at_100
value: 0.799
type: precision_at_1000
value: 0.11199999999999999
type: precision_at_3
value: 11.275
type: precision_at_5
value: 8.059
type: recall_at_1
value: 19.883
type: recall_at_10
value: 43.132999999999996
type: recall_at_100
value: 65.654
type: recall_at_1000
value: 84.492
type: recall_at_3
value: 30.209000000000003
type: recall_at_5
value: 35.616
task: type: Retrieval
dataset: type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics: type: map_at_1
value: 17.756
type: map_at_10
value: 30.378
type: map_at_100
value: 32.537
type: map_at_1000
value: 32.717
type: map_at_3
value: 25.599
type: map_at_5
value: 28.372999999999998
type: mrr_at_1
value: 41.303
type: mrr_at_10
value: 53.483999999999995
type: mrr_at_100
value: 54.106
type: mrr_at_1000
value: 54.127
type: mrr_at_3
value: 50.315
type: mrr_at_5
value: 52.396
type: ndcg_at_1
value: 41.303
type: ndcg_at_10
value: 40.503
type: ndcg_at_100
value: 47.821000000000005
type: ndcg_at_1000
value: 50.788
type: ndcg_at_3
value: 34.364
type: ndcg_at_5
value: 36.818
type: precision_at_1
value: 41.303
type: precision_at_10
value: 12.463000000000001
type: precision_at_100
value: 2.037
type: precision_at_1000
value: 0.26
type: precision_at_3
value: 25.798
type: precision_at_5
value: 19.896
type: recall_at_1
value: 17.756
type: recall_at_10
value: 46.102
type: recall_at_100
value: 70.819
type: recall_at_1000
value: 87.21799999999999
type: recall_at_3
value: 30.646
type: recall_at_5
value: 38.022
task: type: Retrieval
dataset: type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics: type: map_at_1
value: 9.033
type: map_at_10
value: 20.584
type: map_at_100
value: 29.518
type: map_at_1000
value: 31.186000000000003
type: map_at_3
value: 14.468
type: map_at_5
value: 17.177
type: mrr_at_1
value: 69.75
type: mrr_at_10
value: 77.025
type: mrr_at_100
value: 77.36699999999999
type: mrr_at_1000
value: 77.373
type: mrr_at_3
value: 75.583
type: mrr_at_5
value: 76.396
type: ndcg_at_1
value: 58.5
type: ndcg_at_10
value: 45.033
type: ndcg_at_100
value: 49.071
type: ndcg_at_1000
value: 56.056
type: ndcg_at_3
value: 49.936
type: ndcg_at_5
value: 47.471999999999994
type: precision_at_1
value: 69.75
type: precision_at_10
value: 35.775
type: precision_at_100
value: 11.594999999999999
type: precision_at_1000
value: 2.062
type: precision_at_3
value: 52.5
type: precision_at_5
value: 45.300000000000004
type: recall_at_1
value: 9.033
type: recall_at_10
value: 26.596999999999998
type: recall_at_100
value: 54.607000000000006
type: recall_at_1000
value: 76.961
type: recall_at_3
value: 15.754999999999999
type: recall_at_5
value: 20.033
task: type: Classification
dataset: type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics: type: accuracy
value: 48.345000000000006
type: f1
value: 43.4514918068706
task: type: Retrieval
dataset: type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics: type: map_at_1
value: 71.29100000000001
type: map_at_10
value: 81.059
type: map_at_100
value: 81.341
type: map_at_1000
value: 81.355
type: map_at_3
value: 79.74799999999999
type: map_at_5
value: 80.612
type: mrr_at_1
value: 76.40299999999999
type: mrr_at_10
value: 84.615
type: mrr_at_100
value: 84.745
type: mrr_at_1000
value: 84.748
type: mrr_at_3
value: 83.776
type: mrr_at_5
value: 84.343
type: ndcg_at_1
value: 76.40299999999999
type: ndcg_at_10
value: 84.981
type: ndcg_at_100
value: 86.00999999999999
type: ndcg_at_1000
value: 86.252
type: ndcg_at_3
value: 82.97
type: ndcg_at_5
value: 84.152
type: precision_at_1
value: 76.40299999999999
type: precision_at_10
value: 10.446
type: precision_at_100
value: 1.1199999999999999
type: precision_at_1000
value: 0.116
type: precision_at_3
value: 32.147999999999996
type: precision_at_5
value: 20.135
type: recall_at_1
value: 71.29100000000001
type: recall_at_10
value: 93.232
type: recall_at_100
value: 97.363
type: recall_at_1000
value: 98.905
type: recall_at_3
value: 87.893
type: recall_at_5
value: 90.804
task: type: Retrieval
dataset: type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics: type: map_at_1
value: 18.667
type: map_at_10
value: 30.853
type: map_at_100
value: 32.494
type: map_at_1000
value: 32.677
type: map_at_3
value: 26.91
type: map_at_5
value: 29.099000000000004
type: mrr_at_1
value: 37.191
type: mrr_at_10
value: 46.171
type: mrr_at_100
value: 47.056
type: mrr_at_1000
value: 47.099000000000004
type: mrr_at_3
value: 44.059
type: mrr_at_5
value: 45.147
type: ndcg_at_1
value: 37.191
type: ndcg_at_10
value: 38.437
type: ndcg_at_100
value: 44.62
type: ndcg_at_1000
value: 47.795
type: ndcg_at_3
value: 35.003
type: ndcg_at_5
value: 36.006
type: precision_at_1
value: 37.191
type: precision_at_10
value: 10.586
type: precision_at_100
value: 1.688
type: precision_at_1000
value: 0.22699999999999998
type: precision_at_3
value: 23.302
type: precision_at_5
value: 17.006
type: recall_at_1
value: 18.667
type: recall_at_10
value: 45.367000000000004
type: recall_at_100
value: 68.207
type: recall_at_1000
value: 87.072
type: recall_at_3
value: 32.129000000000005
type: recall_at_5
value: 37.719
task: type: Retrieval
dataset: type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics: type: map_at_1
value: 39.494
type: map_at_10
value: 66.223
type: map_at_100
value: 67.062
type: map_at_1000
value: 67.11500000000001
type: map_at_3
value: 62.867
type: map_at_5
value: 64.994
type: mrr_at_1
value: 78.987
type: mrr_at_10
value: 84.585
type: mrr_at_100
value: 84.773
type: mrr_at_1000
value: 84.77900000000001
type: mrr_at_3
value: 83.592
type: mrr_at_5
value: 84.235
type: ndcg_at_1
value: 78.987
type: ndcg_at_10
value: 73.64
type: ndcg_at_100
value: 76.519
type: ndcg_at_1000
value: 77.51
type: ndcg_at_3
value: 68.893
type: ndcg_at_5
value: 71.585
type: precision_at_1
value: 78.987
type: precision_at_10
value: 15.529000000000002
type: precision_at_100
value: 1.7770000000000001
type: precision_at_1000
value: 0.191
type: precision_at_3
value: 44.808
type: precision_at_5
value: 29.006999999999998
type: recall_at_1
value: 39.494
type: recall_at_10
value: 77.643
type: recall_at_100
value: 88.825
type: recall_at_1000
value: 95.321
type: recall_at_3
value: 67.211
type: recall_at_5
value: 72.519
task: type: Classification
dataset: type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics: type: accuracy
value: 85.55959999999999
type: ap
value: 80.7246500384617
type: f1
value: 85.52336485065454
task: type: Retrieval
dataset: type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics: type: map_at_1
value: 23.631
type: map_at_10
value: 36.264
type: map_at_100
value: 37.428
type: map_at_1000
value: 37.472
type: map_at_3
value: 32.537
type: map_at_5
value: 34.746
type: mrr_at_1
value: 24.312
type: mrr_at_10
value: 36.858000000000004
type: mrr_at_100
value: 37.966
type: mrr_at_1000
value: 38.004
type: mrr_at_3
value: 33.188
type: mrr_at_5
value: 35.367
type: ndcg_at_1
value: 24.312
type: ndcg_at_10
value: 43.126999999999995
type: ndcg_at_100
value: 48.642
type: ndcg_at_1000
value: 49.741
type: ndcg_at_3
value: 35.589
type: ndcg_at_5
value: 39.515
type: precision_at_1
value: 24.312
type: precision_at_10
value: 6.699
type: precision_at_100
value: 0.9450000000000001
type: precision_at_1000
value: 0.104
type: precision_at_3
value: 15.153
type: precision_at_5
value: 11.065999999999999
type: recall_at_1
value: 23.631
type: recall_at_10
value: 64.145
type: recall_at_100
value: 89.41
type: recall_at_1000
value: 97.83500000000001
type: recall_at_3
value: 43.769000000000005
type: recall_at_5
value: 53.169
task: type: Classification
dataset: type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics: type: accuracy
value: 93.4108527131783
type: f1
value: 93.1415880261038
task: type: Classification
dataset: type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics: type: accuracy
value: 77.24806201550388
type: f1
value: 60.531916308197175
task: type: Classification
dataset: type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics: type: accuracy
value: 73.71553463349024
type: f1
value: 71.70753174900791
task: type: Classification
dataset: type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics: type: accuracy
value: 77.79757901815736
type: f1
value: 77.83719850433258
task: type: Clustering
dataset: type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics: type: v_measure
value: 33.74193296622113
task: type: Clustering
dataset: type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics: type: v_measure
value: 30.64257594108566
task: type: Reranking
dataset: type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics: type: map
value: 30.811018518883625
type: mrr
value: 31.910376577445003
task: type: Retrieval
dataset: type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics: type: map_at_1
value: 5.409
type: map_at_10
value: 13.093
type: map_at_100
value: 16.256999999999998
type: map_at_1000
value: 17.617
type: map_at_3
value: 9.555
type: map_at_5
value: 11.428
type: mrr_at_1
value: 45.201
type: mrr_at_10
value: 54.179
type: mrr_at_100
value: 54.812000000000005
type: mrr_at_1000
value: 54.840999999999994
type: mrr_at_3
value: 51.909000000000006
type: mrr_at_5
value: 53.519000000000005
type: ndcg_at_1
value: 43.189
type: ndcg_at_10
value: 35.028
type: ndcg_at_100
value: 31.226
type: ndcg_at_1000
value: 39.678000000000004
type: ndcg_at_3
value: 40.596
type: ndcg_at_5
value: 38.75
type: precision_at_1
value: 44.582
type: precision_at_10
value: 25.974999999999998
type: precision_at_100
value: 7.793
type: precision_at_1000
value: 2.036
type: precision_at_3
value: 38.493
type: precision_at_5
value: 33.994
type: recall_at_1
value: 5.409
type: recall_at_10
value: 16.875999999999998
type: recall_at_100
value: 30.316
type: recall_at_1000
value: 60.891
type: recall_at_3
value: 10.688
type: recall_at_5
value: 13.832
task: type: Retrieval
dataset: type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics: type: map_at_1
value: 36.375
type: map_at_10
value: 51.991
type: map_at_100
value: 52.91400000000001
type: map_at_1000
value: 52.93600000000001
type: map_at_3
value: 48.014
type: map_at_5
value: 50.381
type: mrr_at_1
value: 40.759
type: mrr_at_10
value: 54.617000000000004
type: mrr_at_100
value: 55.301
type: mrr_at_1000
value: 55.315000000000005
type: mrr_at_3
value: 51.516
type: mrr_at_5
value: 53.435
type: ndcg_at_1
value: 40.759
type: ndcg_at_10
value: 59.384
type: ndcg_at_100
value: 63.157
type: ndcg_at_1000
value: 63.654999999999994
type: ndcg_at_3
value: 52.114000000000004
type: ndcg_at_5
value: 55.986000000000004
type: precision_at_1
value: 40.759
type: precision_at_10
value: 9.411999999999999
type: precision_at_100
value: 1.153
type: precision_at_1000
value: 0.12
type: precision_at_3
value: 23.329
type: precision_at_5
value: 16.256999999999998
type: recall_at_1
value: 36.375
type: recall_at_10
value: 79.053
type: recall_at_100
value: 95.167
type: recall_at_1000
value: 98.82
type: recall_at_3
value: 60.475
type: recall_at_5
value: 69.327
task: type: Retrieval
dataset: type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 70.256
type: map_at_10
value: 83.8
type: map_at_100
value: 84.425
type: map_at_1000
value: 84.444
type: map_at_3
value: 80.906
type: map_at_5
value: 82.717
type: mrr_at_1
value: 80.97999999999999
type: mrr_at_10
value: 87.161
type: mrr_at_100
value: 87.262
type: mrr_at_1000
value: 87.263
type: mrr_at_3
value: 86.175
type: mrr_at_5
value: 86.848
type: ndcg_at_1
value: 80.97999999999999
type: ndcg_at_10
value: 87.697
type: ndcg_at_100
value: 88.959
type: ndcg_at_1000
value: 89.09899999999999
type: ndcg_at_3
value: 84.83800000000001
type: ndcg_at_5
value: 86.401
type: precision_at_1
value: 80.97999999999999
type: precision_at_10
value: 13.261000000000001
type: precision_at_100
value: 1.5150000000000001
type: precision_at_1000
value: 0.156
type: precision_at_3
value: 37.01
type: precision_at_5
value: 24.298000000000002
type: recall_at_1
value: 70.256
type: recall_at_10
value: 94.935
type: recall_at_100
value: 99.274
type: recall_at_1000
value: 99.928
type: recall_at_3
value: 86.602
type: recall_at_5
value: 91.133
task: type: Clustering
dataset: type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics: type: v_measure
value: 56.322692497613104
task: type: Clustering
dataset: type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics: type: v_measure
value: 61.895813503775074
task: type: Retrieval
dataset: type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics: type: map_at_1
value: 4.338
type: map_at_10
value: 10.767
type: map_at_100
value: 12.537999999999998
type: map_at_1000
value: 12.803999999999998
type: map_at_3
value: 7.788
type: map_at_5
value: 9.302000000000001
type: mrr_at_1
value: 21.4
type: mrr_at_10
value: 31.637999999999998
type: mrr_at_100
value: 32.688
type: mrr_at_1000
value: 32.756
type: mrr_at_3
value: 28.433000000000003
type: mrr_at_5
value: 30.178
type: ndcg_at_1
value: 21.4
type: ndcg_at_10
value: 18.293
type: ndcg_at_100
value: 25.274
type: ndcg_at_1000
value: 30.284
type: ndcg_at_3
value: 17.391000000000002
type: ndcg_at_5
value: 15.146999999999998
type: precision_at_1
value: 21.4
type: precision_at_10
value: 9.48
type: precision_at_100
value: 1.949
type: precision_at_1000
value: 0.316
type: precision_at_3
value: 16.167
type: precision_at_5
value: 13.22
type: recall_at_1
value: 4.338
type: recall_at_10
value: 19.213
type: recall_at_100
value: 39.562999999999995
type: recall_at_1000
value: 64.08
type: recall_at_3
value: 9.828000000000001
type: recall_at_5
value: 13.383000000000001
task: type: STS
dataset: type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics: type: cos_sim_pearson
value: 82.42568163642142
type: cos_sim_spearman
value: 78.5797159641342
type: euclidean_pearson
value: 80.22151260811604
type: euclidean_spearman
value: 78.5797151953878
type: manhattan_pearson
value: 80.21224215864788
type: manhattan_spearman
value: 78.55641478381344
task: type: STS
dataset: type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics: type: cos_sim_pearson
value: 85.44020710812569
type: cos_sim_spearman
value: 78.91631735081286
type: euclidean_pearson
value: 81.64188964182102
type: euclidean_spearman
value: 78.91633286881678
type: manhattan_pearson
value: 81.69294748512496
type: manhattan_spearman
value: 78.93438558002656
task: type: STS
dataset: type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics: type: cos_sim_pearson
value: 84.27165426412311
type: cos_sim_spearman
value: 85.40429140249618
type: euclidean_pearson
value: 84.7509580724893
type: euclidean_spearman
value: 85.40429140249618
type: manhattan_pearson
value: 84.76488289321308
type: manhattan_spearman
value: 85.4256793698708
task: type: STS
dataset: type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics: type: cos_sim_pearson
value: 83.138851760732
type: cos_sim_spearman
value: 81.64101363896586
type: euclidean_pearson
value: 82.55165038934942
type: euclidean_spearman
value: 81.64105257080502
type: manhattan_pearson
value: 82.52802949883335
type: manhattan_spearman
value: 81.61255430718158
task: type: STS
dataset: type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics: type: cos_sim_pearson
value: 86.0654695484029
type: cos_sim_spearman
value: 87.20408521902229
type: euclidean_pearson
value: 86.8110651362115
type: euclidean_spearman
value: 87.20408521902229
type: manhattan_pearson
value: 86.77984656478691
type: manhattan_spearman
value: 87.1719947099227
task: type: STS
dataset: type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics: type: cos_sim_pearson
value: 83.77823915496512
type: cos_sim_spearman
value: 85.43566325729779
type: euclidean_pearson
value: 84.5396956658821
type: euclidean_spearman
value: 85.43566325729779
type: manhattan_pearson
value: 84.5665398848169
type: manhattan_spearman
value: 85.44375870303232
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: 87.20030208471798
type: cos_sim_spearman
value: 87.20485505076539
type: euclidean_pearson
value: 88.10588324368722
type: euclidean_spearman
value: 87.20485505076539
type: manhattan_pearson
value: 87.92324770415183
type: manhattan_spearman
value: 87.0571314561877
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: 63.06093161604453
type: cos_sim_spearman
value: 64.2163140357722
type: euclidean_pearson
value: 65.27589680994006
type: euclidean_spearman
value: 64.2163140357722
type: manhattan_pearson
value: 65.45904383711101
type: manhattan_spearman
value: 64.55404716679305
task: type: STS
dataset: type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics: type: cos_sim_pearson
value: 84.32976164578706
type: cos_sim_spearman
value: 85.54302197678368
type: euclidean_pearson
value: 85.26307149193056
type: euclidean_spearman
value: 85.54302197678368
type: manhattan_pearson
value: 85.26647282029371
type: manhattan_spearman
value: 85.5316135265568
task: type: Reranking
dataset: type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics: type: map
value: 81.44675968318754
type: mrr
value: 94.92741826075158
task: type: Retrieval
dataset: type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics: type: map_at_1
value: 56.34400000000001
type: map_at_10
value: 65.927
type: map_at_100
value: 66.431
type: map_at_1000
value: 66.461
type: map_at_3
value: 63.529
type: map_at_5
value: 64.818
type: mrr_at_1
value: 59.333000000000006
type: mrr_at_10
value: 67.54599999999999
type: mrr_at_100
value: 67.892
type: mrr_at_1000
value: 67.917
type: mrr_at_3
value: 65.778
type: mrr_at_5
value: 66.794
type: ndcg_at_1
value: 59.333000000000006
type: ndcg_at_10
value: 70.5
type: ndcg_at_100
value: 72.688
type: ndcg_at_1000
value: 73.483
type: ndcg_at_3
value: 66.338
type: ndcg_at_5
value: 68.265
type: precision_at_1
value: 59.333000000000006
type: precision_at_10
value: 9.3
type: precision_at_100
value: 1.053
type: precision_at_1000
value: 0.11199999999999999
type: precision_at_3
value: 25.889
type: precision_at_5
value: 16.866999999999997
type: recall_at_1
value: 56.34400000000001
type: recall_at_10
value: 82.789
type: recall_at_100
value: 92.767
type: recall_at_1000
value: 99
type: recall_at_3
value: 71.64399999999999
type: recall_at_5
value: 76.322
task: type: PairClassification
dataset: type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics: type: cos_sim_accuracy
value: 99.75742574257426
type: cos_sim_ap
value: 93.52081548447406
type: cos_sim_f1
value: 87.33850129198966
type: cos_sim_precision
value: 90.37433155080214
type: cos_sim_recall
value: 84.5
type: dot_accuracy
value: 99.75742574257426
type: dot_ap
value: 93.52081548447406
type: dot_f1
value: 87.33850129198966
type: dot_precision
value: 90.37433155080214
type: dot_recall
value: 84.5
type: euclidean_accuracy
value: 99.75742574257426
type: euclidean_ap
value: 93.52081548447406
type: euclidean_f1
value: 87.33850129198966
type: euclidean_precision
value: 90.37433155080214
type: euclidean_recall
value: 84.5
type: manhattan_accuracy
value: 99.75841584158415
type: manhattan_ap
value: 93.4975678585854
type: manhattan_f1
value: 87.26708074534162
type: manhattan_precision
value: 90.45064377682404
type: manhattan_recall
value: 84.3
type: max_accuracy
value: 99.75841584158415
type: max_ap
value: 93.52081548447406
type: max_f1
value: 87.33850129198966
task: type: Clustering
dataset: type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics: type: v_measure
value: 64.31437036686651
task: type: Clustering
dataset: type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics: type: v_measure
value: 33.25569319007206
task: type: Reranking
dataset: type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics: type: map
value: 49.90474939720706
type: mrr
value: 50.568115503777264
task: type: Summarization
dataset: type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics: type: cos_sim_pearson
value: 29.866828641244712
type: cos_sim_spearman
value: 30.077555055873866
type: dot_pearson
value: 29.866832988572266
type: dot_spearman
value: 30.077555055873866
task: type: Retrieval
dataset: type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics: type: map_at_1
value: 0.232
type: map_at_10
value: 2.094
type: map_at_100
value: 11.971
type: map_at_1000
value: 28.158
type: map_at_3
value: 0.688
type: map_at_5
value: 1.114
type: mrr_at_1
value: 88
type: mrr_at_10
value: 93.4
type: mrr_at_100
value: 93.4
type: mrr_at_1000
value: 93.4
type: mrr_at_3
value: 93
type: mrr_at_5
value: 93.4
type: ndcg_at_1
value: 84
type: ndcg_at_10
value: 79.923
type: ndcg_at_100
value: 61.17
type: ndcg_at_1000
value: 53.03
type: ndcg_at_3
value: 84.592
type: ndcg_at_5
value: 82.821
type: precision_at_1
value: 88
type: precision_at_10
value: 85
type: precision_at_100
value: 63.019999999999996
type: precision_at_1000
value: 23.554
type: precision_at_3
value: 89.333
type: precision_at_5
value: 87.2
type: recall_at_1
value: 0.232
type: recall_at_10
value: 2.255
type: recall_at_100
value: 14.823
type: recall_at_1000
value: 49.456
type: recall_at_3
value: 0.718
type: recall_at_5
value: 1.175
task: type: Retrieval
dataset: type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics: type: map_at_1
value: 2.547
type: map_at_10
value: 11.375
type: map_at_100
value: 18.194
type: map_at_1000
value: 19.749
type: map_at_3
value: 5.825
type: map_at_5
value: 8.581
type: mrr_at_1
value: 32.653
type: mrr_at_10
value: 51.32
type: mrr_at_100
value: 51.747
type: mrr_at_1000
value: 51.747
type: mrr_at_3
value: 47.278999999999996
type: mrr_at_5
value: 48.605
type: ndcg_at_1
value: 29.592000000000002
type: ndcg_at_10
value: 28.151
type: ndcg_at_100
value: 39.438
type: ndcg_at_1000
value: 50.769
type: ndcg_at_3
value: 30.758999999999997
type: ndcg_at_5
value: 30.366
type: precision_at_1
value: 32.653
type: precision_at_10
value: 25.714
type: precision_at_100
value: 8.041
type: precision_at_1000
value: 1.555
type: precision_at_3
value: 33.333
type: precision_at_5
value: 31.837
type: recall_at_1
value: 2.547
type: recall_at_10
value: 18.19
type: recall_at_100
value: 49.538
type: recall_at_1000
value: 83.86
type: recall_at_3
value: 7.329
type: recall_at_5
value: 11.532
task: type: Classification
dataset: type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics: type: accuracy
value: 71.4952
type: ap
value: 14.793362635531409
type: f1
value: 55.204635551516915
task: type: Classification
dataset: type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics: type: accuracy
value: 61.5365025466893
type: f1
value: 61.81742556334845
task: type: Clustering
dataset: type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics: type: v_measure
value: 49.05531070301185
task: type: PairClassification
dataset: type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics: type: cos_sim_accuracy
value: 86.51725576682364
type: cos_sim_ap
value: 75.2292304265163
type: cos_sim_f1
value: 69.54022988505749
type: cos_sim_precision
value: 63.65629110039457
type: cos_sim_recall
value: 76.62269129287598
type: dot_accuracy
value: 86.51725576682364
type: dot_ap
value: 75.22922386081054
type: dot_f1
value: 69.54022988505749
type: dot_precision
value: 63.65629110039457
type: dot_recall
value: 76.62269129287598
type: euclidean_accuracy
value: 86.51725576682364
type: euclidean_ap
value: 75.22925730473472
type: euclidean_f1
value: 69.54022988505749
type: euclidean_precision
value: 63.65629110039457
type: euclidean_recall
value: 76.62269129287598
type: manhattan_accuracy
value: 86.52321630804077
type: manhattan_ap
value: 75.20608115037336
type: manhattan_f1
value: 69.60000000000001
type: manhattan_precision
value: 64.37219730941705
type: manhattan_recall
value: 75.75197889182058
type: max_accuracy
value: 86.52321630804077
type: max_ap
value: 75.22925730473472
type: max_f1
value: 69.60000000000001
task: type: PairClassification
dataset: type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics: type: cos_sim_accuracy
value: 89.34877944657896
type: cos_sim_ap
value: 86.71257569277373
type: cos_sim_f1
value: 79.10386355986088
type: cos_sim_precision
value: 76.91468470434214
type: cos_sim_recall
value: 81.4213119802895
type: dot_accuracy
value: 89.34877944657896
type: dot_ap
value: 86.71257133133368
type: dot_f1
value: 79.10386355986088
type: dot_precision
value: 76.91468470434214
type: dot_recall
value: 81.4213119802895
type: euclidean_accuracy
value: 89.34877944657896
type: euclidean_ap
value: 86.71257651501476
type: euclidean_f1
value: 79.10386355986088
type: euclidean_precision
value: 76.91468470434214
type: euclidean_recall
value: 81.4213119802895
type: manhattan_accuracy
value: 89.35848177901967
type: manhattan_ap
value: 86.69330615469126
type: manhattan_f1
value: 79.13867741453949
type: manhattan_precision
value: 76.78881807647741
type: manhattan_recall
value: 81.63689559593472
type: max_accuracy
value: 89.35848177901967
type: max_ap
value: 86.71257651501476
type: max_f1
value: 79.13867741453949
license: apache-2.0
language: en
new_version: nomic-ai/nomic-embed-text-v1.5
title: API endpoint