metadata
license: apache-2.0
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- mteb
model-index:
- name: cai-lunaris-text-embeddings
results:
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.07
- type: map_at_10
value: 29.372999999999998
- type: map_at_100
value: 30.79
- type: map_at_1000
value: 30.819999999999997
- type: map_at_3
value: 24.395
- type: map_at_5
value: 27.137
- type: mrr_at_1
value: 17.923000000000002
- type: mrr_at_10
value: 29.695
- type: mrr_at_100
value: 31.098
- type: mrr_at_1000
value: 31.128
- type: mrr_at_3
value: 24.704
- type: mrr_at_5
value: 27.449
- type: ndcg_at_1
value: 17.07
- type: ndcg_at_10
value: 37.269000000000005
- type: ndcg_at_100
value: 43.716
- type: ndcg_at_1000
value: 44.531
- type: ndcg_at_3
value: 26.839000000000002
- type: ndcg_at_5
value: 31.845000000000002
- type: precision_at_1
value: 17.07
- type: precision_at_10
value: 6.3020000000000005
- type: precision_at_100
value: 0.922
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 11.309
- type: precision_at_5
value: 9.246
- type: recall_at_1
value: 17.07
- type: recall_at_10
value: 63.016000000000005
- type: recall_at_100
value: 92.24799999999999
- type: recall_at_1000
value: 98.72
- type: recall_at_3
value: 33.926
- type: recall_at_5
value: 46.23
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 53.44266265900711
- type: mrr
value: 66.54695950402322
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 75.9652953730204
- type: cos_sim_spearman
value: 73.96554077670989
- type: euclidean_pearson
value: 75.68477255792381
- type: euclidean_spearman
value: 74.59447076995703
- type: manhattan_pearson
value: 75.94984623881341
- type: manhattan_spearman
value: 74.72218452337502
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 14.119000000000002
- type: map_at_10
value: 19.661
- type: map_at_100
value: 20.706
- type: map_at_1000
value: 20.848
- type: map_at_3
value: 17.759
- type: map_at_5
value: 18.645
- type: mrr_at_1
value: 17.166999999999998
- type: mrr_at_10
value: 23.313
- type: mrr_at_100
value: 24.263
- type: mrr_at_1000
value: 24.352999999999998
- type: mrr_at_3
value: 21.412
- type: mrr_at_5
value: 22.313
- type: ndcg_at_1
value: 17.166999999999998
- type: ndcg_at_10
value: 23.631
- type: ndcg_at_100
value: 28.427000000000003
- type: ndcg_at_1000
value: 31.862000000000002
- type: ndcg_at_3
value: 20.175
- type: ndcg_at_5
value: 21.397
- type: precision_at_1
value: 17.166999999999998
- type: precision_at_10
value: 4.549
- type: precision_at_100
value: 0.8370000000000001
- type: precision_at_1000
value: 0.136
- type: precision_at_3
value: 9.68
- type: precision_at_5
value: 6.981
- type: recall_at_1
value: 14.119000000000002
- type: recall_at_10
value: 32.147999999999996
- type: recall_at_100
value: 52.739999999999995
- type: recall_at_1000
value: 76.67
- type: recall_at_3
value: 22.019
- type: recall_at_5
value: 25.361
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.576
- type: map_at_10
value: 22.281000000000002
- type: map_at_100
value: 23.066
- type: map_at_1000
value: 23.166
- type: map_at_3
value: 20.385
- type: map_at_5
value: 21.557000000000002
- type: mrr_at_1
value: 20.892
- type: mrr_at_10
value: 26.605
- type: mrr_at_100
value: 27.229
- type: mrr_at_1000
value: 27.296
- type: mrr_at_3
value: 24.809
- type: mrr_at_5
value: 25.927
- type: ndcg_at_1
value: 20.892
- type: ndcg_at_10
value: 26.092
- type: ndcg_at_100
value: 29.398999999999997
- type: ndcg_at_1000
value: 31.884
- type: ndcg_at_3
value: 23.032
- type: ndcg_at_5
value: 24.634
- type: precision_at_1
value: 20.892
- type: precision_at_10
value: 4.885
- type: precision_at_100
value: 0.818
- type: precision_at_1000
value: 0.126
- type: precision_at_3
value: 10.977
- type: precision_at_5
value: 8.013
- type: recall_at_1
value: 16.576
- type: recall_at_10
value: 32.945
- type: recall_at_100
value: 47.337
- type: recall_at_1000
value: 64.592
- type: recall_at_3
value: 24.053
- type: recall_at_5
value: 28.465
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.604
- type: map_at_10
value: 28.754999999999995
- type: map_at_100
value: 29.767
- type: map_at_1000
value: 29.852
- type: map_at_3
value: 26.268
- type: map_at_5
value: 27.559
- type: mrr_at_1
value: 24.326
- type: mrr_at_10
value: 31.602000000000004
- type: mrr_at_100
value: 32.46
- type: mrr_at_1000
value: 32.521
- type: mrr_at_3
value: 29.415000000000003
- type: mrr_at_5
value: 30.581000000000003
- type: ndcg_at_1
value: 24.326
- type: ndcg_at_10
value: 33.335
- type: ndcg_at_100
value: 38.086
- type: ndcg_at_1000
value: 40.319
- type: ndcg_at_3
value: 28.796
- type: ndcg_at_5
value: 30.758999999999997
- type: precision_at_1
value: 24.326
- type: precision_at_10
value: 5.712
- type: precision_at_100
value: 0.893
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 13.208
- type: precision_at_5
value: 9.329
- type: recall_at_1
value: 20.604
- type: recall_at_10
value: 44.505
- type: recall_at_100
value: 65.866
- type: recall_at_1000
value: 82.61800000000001
- type: recall_at_3
value: 31.794
- type: recall_at_5
value: 36.831
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.280999999999999
- type: map_at_10
value: 11.636000000000001
- type: map_at_100
value: 12.363
- type: map_at_1000
value: 12.469
- type: map_at_3
value: 10.415000000000001
- type: map_at_5
value: 11.144
- type: mrr_at_1
value: 9.266
- type: mrr_at_10
value: 12.838
- type: mrr_at_100
value: 13.608999999999998
- type: mrr_at_1000
value: 13.700999999999999
- type: mrr_at_3
value: 11.507000000000001
- type: mrr_at_5
value: 12.343
- type: ndcg_at_1
value: 9.266
- type: ndcg_at_10
value: 13.877
- type: ndcg_at_100
value: 18.119
- type: ndcg_at_1000
value: 21.247
- type: ndcg_at_3
value: 11.376999999999999
- type: ndcg_at_5
value: 12.675
- type: precision_at_1
value: 9.266
- type: precision_at_10
value: 2.226
- type: precision_at_100
value: 0.47200000000000003
- type: precision_at_1000
value: 0.077
- type: precision_at_3
value: 4.859
- type: precision_at_5
value: 3.6380000000000003
- type: recall_at_1
value: 8.280999999999999
- type: recall_at_10
value: 19.872999999999998
- type: recall_at_100
value: 40.585
- type: recall_at_1000
value: 65.225
- type: recall_at_3
value: 13.014000000000001
- type: recall_at_5
value: 16.147
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.1209999999999996
- type: map_at_10
value: 7.272
- type: map_at_100
value: 8.079
- type: map_at_1000
value: 8.199
- type: map_at_3
value: 6.212
- type: map_at_5
value: 6.736000000000001
- type: mrr_at_1
value: 5.721
- type: mrr_at_10
value: 9.418
- type: mrr_at_100
value: 10.281
- type: mrr_at_1000
value: 10.385
- type: mrr_at_3
value: 8.126
- type: mrr_at_5
value: 8.779
- type: ndcg_at_1
value: 5.721
- type: ndcg_at_10
value: 9.673
- type: ndcg_at_100
value: 13.852999999999998
- type: ndcg_at_1000
value: 17.546999999999997
- type: ndcg_at_3
value: 7.509
- type: ndcg_at_5
value: 8.373
- type: precision_at_1
value: 5.721
- type: precision_at_10
value: 2.04
- type: precision_at_100
value: 0.48
- type: precision_at_1000
value: 0.093
- type: precision_at_3
value: 4.022
- type: precision_at_5
value: 3.06
- type: recall_at_1
value: 4.1209999999999996
- type: recall_at_10
value: 15.201
- type: recall_at_100
value: 33.922999999999995
- type: recall_at_1000
value: 61.529999999999994
- type: recall_at_3
value: 8.869
- type: recall_at_5
value: 11.257
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 14.09
- type: map_at_10
value: 19.573999999999998
- type: map_at_100
value: 20.580000000000002
- type: map_at_1000
value: 20.704
- type: map_at_3
value: 17.68
- type: map_at_5
value: 18.64
- type: mrr_at_1
value: 17.227999999999998
- type: mrr_at_10
value: 23.152
- type: mrr_at_100
value: 24.056
- type: mrr_at_1000
value: 24.141000000000002
- type: mrr_at_3
value: 21.142
- type: mrr_at_5
value: 22.201
- type: ndcg_at_1
value: 17.227999999999998
- type: ndcg_at_10
value: 23.39
- type: ndcg_at_100
value: 28.483999999999998
- type: ndcg_at_1000
value: 31.709
- type: ndcg_at_3
value: 19.883
- type: ndcg_at_5
value: 21.34
- type: precision_at_1
value: 17.227999999999998
- type: precision_at_10
value: 4.3790000000000004
- type: precision_at_100
value: 0.826
- type: precision_at_1000
value: 0.128
- type: precision_at_3
value: 9.496
- type: precision_at_5
value: 6.872
- type: recall_at_1
value: 14.09
- type: recall_at_10
value: 31.580000000000002
- type: recall_at_100
value: 54.074
- type: recall_at_1000
value: 77.092
- type: recall_at_3
value: 21.601
- type: recall_at_5
value: 25.333
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 10.538
- type: map_at_10
value: 15.75
- type: map_at_100
value: 16.71
- type: map_at_1000
value: 16.838
- type: map_at_3
value: 13.488
- type: map_at_5
value: 14.712
- type: mrr_at_1
value: 13.813
- type: mrr_at_10
value: 19.08
- type: mrr_at_100
value: 19.946
- type: mrr_at_1000
value: 20.044
- type: mrr_at_3
value: 16.838
- type: mrr_at_5
value: 17.951
- type: ndcg_at_1
value: 13.813
- type: ndcg_at_10
value: 19.669
- type: ndcg_at_100
value: 24.488
- type: ndcg_at_1000
value: 27.87
- type: ndcg_at_3
value: 15.479000000000001
- type: ndcg_at_5
value: 17.229
- type: precision_at_1
value: 13.813
- type: precision_at_10
value: 3.916
- type: precision_at_100
value: 0.743
- type: precision_at_1000
value: 0.122
- type: precision_at_3
value: 7.534000000000001
- type: precision_at_5
value: 5.822
- type: recall_at_1
value: 10.538
- type: recall_at_10
value: 28.693
- type: recall_at_100
value: 50.308
- type: recall_at_1000
value: 74.44
- type: recall_at_3
value: 16.866999999999997
- type: recall_at_5
value: 21.404999999999998
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 11.044583333333332
- type: map_at_10
value: 15.682833333333335
- type: map_at_100
value: 16.506500000000003
- type: map_at_1000
value: 16.623833333333334
- type: map_at_3
value: 14.130833333333333
- type: map_at_5
value: 14.963583333333332
- type: mrr_at_1
value: 13.482833333333332
- type: mrr_at_10
value: 18.328500000000002
- type: mrr_at_100
value: 19.095416666666665
- type: mrr_at_1000
value: 19.18241666666666
- type: mrr_at_3
value: 16.754749999999998
- type: mrr_at_5
value: 17.614749999999997
- type: ndcg_at_1
value: 13.482833333333332
- type: ndcg_at_10
value: 18.81491666666667
- type: ndcg_at_100
value: 22.946833333333334
- type: ndcg_at_1000
value: 26.061083333333336
- type: ndcg_at_3
value: 15.949333333333332
- type: ndcg_at_5
value: 17.218333333333334
- type: precision_at_1
value: 13.482833333333332
- type: precision_at_10
value: 3.456583333333333
- type: precision_at_100
value: 0.6599166666666666
- type: precision_at_1000
value: 0.109
- type: precision_at_3
value: 7.498833333333332
- type: precision_at_5
value: 5.477166666666667
- type: recall_at_1
value: 11.044583333333332
- type: recall_at_10
value: 25.737750000000005
- type: recall_at_100
value: 44.617916666666666
- type: recall_at_1000
value: 67.56524999999999
- type: recall_at_3
value: 17.598249999999997
- type: recall_at_5
value: 20.9035
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.362
- type: map_at_10
value: 13.414000000000001
- type: map_at_100
value: 14.083000000000002
- type: map_at_1000
value: 14.168
- type: map_at_3
value: 12.098
- type: map_at_5
value: 12.803999999999998
- type: mrr_at_1
value: 11.043
- type: mrr_at_10
value: 15.158
- type: mrr_at_100
value: 15.845999999999998
- type: mrr_at_1000
value: 15.916
- type: mrr_at_3
value: 13.88
- type: mrr_at_5
value: 14.601
- type: ndcg_at_1
value: 11.043
- type: ndcg_at_10
value: 16.034000000000002
- type: ndcg_at_100
value: 19.686
- type: ndcg_at_1000
value: 22.188
- type: ndcg_at_3
value: 13.530000000000001
- type: ndcg_at_5
value: 14.704
- type: precision_at_1
value: 11.043
- type: precision_at_10
value: 2.791
- type: precision_at_100
value: 0.5
- type: precision_at_1000
value: 0.077
- type: precision_at_3
value: 6.237
- type: precision_at_5
value: 4.5089999999999995
- type: recall_at_1
value: 9.362
- type: recall_at_10
value: 22.396
- type: recall_at_100
value: 39.528999999999996
- type: recall_at_1000
value: 58.809
- type: recall_at_3
value: 15.553
- type: recall_at_5
value: 18.512
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.657
- type: map_at_10
value: 8.273
- type: map_at_100
value: 8.875
- type: map_at_1000
value: 8.977
- type: map_at_3
value: 7.32
- type: map_at_5
value: 7.792000000000001
- type: mrr_at_1
value: 7.02
- type: mrr_at_10
value: 9.966999999999999
- type: mrr_at_100
value: 10.636
- type: mrr_at_1000
value: 10.724
- type: mrr_at_3
value: 8.872
- type: mrr_at_5
value: 9.461
- type: ndcg_at_1
value: 7.02
- type: ndcg_at_10
value: 10.199
- type: ndcg_at_100
value: 13.642000000000001
- type: ndcg_at_1000
value: 16.643
- type: ndcg_at_3
value: 8.333
- type: ndcg_at_5
value: 9.103
- type: precision_at_1
value: 7.02
- type: precision_at_10
value: 1.8929999999999998
- type: precision_at_100
value: 0.43
- type: precision_at_1000
value: 0.08099999999999999
- type: precision_at_3
value: 3.843
- type: precision_at_5
value: 2.884
- type: recall_at_1
value: 5.657
- type: recall_at_10
value: 14.563
- type: recall_at_100
value: 30.807000000000002
- type: recall_at_1000
value: 53.251000000000005
- type: recall_at_3
value: 9.272
- type: recall_at_5
value: 11.202
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 10.671999999999999
- type: map_at_10
value: 14.651
- type: map_at_100
value: 15.406
- type: map_at_1000
value: 15.525
- type: map_at_3
value: 13.461
- type: map_at_5
value: 14.163
- type: mrr_at_1
value: 12.407
- type: mrr_at_10
value: 16.782
- type: mrr_at_100
value: 17.562
- type: mrr_at_1000
value: 17.653
- type: mrr_at_3
value: 15.47
- type: mrr_at_5
value: 16.262
- type: ndcg_at_1
value: 12.407
- type: ndcg_at_10
value: 17.251
- type: ndcg_at_100
value: 21.378
- type: ndcg_at_1000
value: 24.689
- type: ndcg_at_3
value: 14.915000000000001
- type: ndcg_at_5
value: 16.1
- type: precision_at_1
value: 12.407
- type: precision_at_10
value: 2.91
- type: precision_at_100
value: 0.573
- type: precision_at_1000
value: 0.096
- type: precision_at_3
value: 6.779
- type: precision_at_5
value: 4.888
- type: recall_at_1
value: 10.671999999999999
- type: recall_at_10
value: 23.099
- type: recall_at_100
value: 41.937999999999995
- type: recall_at_1000
value: 66.495
- type: recall_at_3
value: 16.901
- type: recall_at_5
value: 19.807
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 13.364
- type: map_at_10
value: 17.772
- type: map_at_100
value: 18.659
- type: map_at_1000
value: 18.861
- type: map_at_3
value: 16.659
- type: map_at_5
value: 17.174
- type: mrr_at_1
value: 16.996
- type: mrr_at_10
value: 21.687
- type: mrr_at_100
value: 22.313
- type: mrr_at_1000
value: 22.422
- type: mrr_at_3
value: 20.652
- type: mrr_at_5
value: 21.146
- type: ndcg_at_1
value: 16.996
- type: ndcg_at_10
value: 21.067
- type: ndcg_at_100
value: 24.829
- type: ndcg_at_1000
value: 28.866999999999997
- type: ndcg_at_3
value: 19.466
- type: ndcg_at_5
value: 19.993
- type: precision_at_1
value: 16.996
- type: precision_at_10
value: 4.071000000000001
- type: precision_at_100
value: 0.9329999999999999
- type: precision_at_1000
value: 0.183
- type: precision_at_3
value: 9.223
- type: precision_at_5
value: 6.4030000000000005
- type: recall_at_1
value: 13.364
- type: recall_at_10
value: 25.976
- type: recall_at_100
value: 44.134
- type: recall_at_1000
value: 73.181
- type: recall_at_3
value: 20.503
- type: recall_at_5
value: 22.409000000000002
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.151
- type: map_at_10
value: 9.155000000000001
- type: map_at_100
value: 9.783999999999999
- type: map_at_1000
value: 9.879
- type: map_at_3
value: 7.825
- type: map_at_5
value: 8.637
- type: mrr_at_1
value: 5.915
- type: mrr_at_10
value: 10.34
- type: mrr_at_100
value: 10.943999999999999
- type: mrr_at_1000
value: 11.033
- type: mrr_at_3
value: 8.934000000000001
- type: mrr_at_5
value: 9.812
- type: ndcg_at_1
value: 5.915
- type: ndcg_at_10
value: 11.561
- type: ndcg_at_100
value: 14.971
- type: ndcg_at_1000
value: 17.907999999999998
- type: ndcg_at_3
value: 8.896999999999998
- type: ndcg_at_5
value: 10.313
- type: precision_at_1
value: 5.915
- type: precision_at_10
value: 2.1069999999999998
- type: precision_at_100
value: 0.414
- type: precision_at_1000
value: 0.074
- type: precision_at_3
value: 4.128
- type: precision_at_5
value: 3.327
- type: recall_at_1
value: 5.151
- type: recall_at_10
value: 17.874000000000002
- type: recall_at_100
value: 34.174
- type: recall_at_1000
value: 56.879999999999995
- type: recall_at_3
value: 10.732999999999999
- type: recall_at_5
value: 14.113000000000001
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.101
- type: map_at_10
value: 5.434
- type: map_at_100
value: 6.267
- type: map_at_1000
value: 6.418
- type: map_at_3
value: 4.377000000000001
- type: map_at_5
value: 4.841
- type: mrr_at_1
value: 7.166
- type: mrr_at_10
value: 12.012
- type: mrr_at_100
value: 13.144
- type: mrr_at_1000
value: 13.229
- type: mrr_at_3
value: 9.826
- type: mrr_at_5
value: 10.921
- type: ndcg_at_1
value: 7.166
- type: ndcg_at_10
value: 8.687000000000001
- type: ndcg_at_100
value: 13.345
- type: ndcg_at_1000
value: 16.915
- type: ndcg_at_3
value: 6.276
- type: ndcg_at_5
value: 7.013
- type: precision_at_1
value: 7.166
- type: precision_at_10
value: 2.9250000000000003
- type: precision_at_100
value: 0.771
- type: precision_at_1000
value: 0.13999999999999999
- type: precision_at_3
value: 4.734
- type: precision_at_5
value: 3.8830000000000005
- type: recall_at_1
value: 3.101
- type: recall_at_10
value: 11.774999999999999
- type: recall_at_100
value: 28.819
- type: recall_at_1000
value: 49.886
- type: recall_at_3
value: 5.783
- type: recall_at_5
value: 7.692
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.758
- type: map_at_10
value: 5.507
- type: map_at_100
value: 7.1819999999999995
- type: map_at_1000
value: 7.652
- type: map_at_3
value: 4.131
- type: map_at_5
value: 4.702
- type: mrr_at_1
value: 28.499999999999996
- type: mrr_at_10
value: 37.693
- type: mrr_at_100
value: 38.657000000000004
- type: mrr_at_1000
value: 38.704
- type: mrr_at_3
value: 34.792
- type: mrr_at_5
value: 36.417
- type: ndcg_at_1
value: 20.625
- type: ndcg_at_10
value: 14.771999999999998
- type: ndcg_at_100
value: 16.821
- type: ndcg_at_1000
value: 21.546000000000003
- type: ndcg_at_3
value: 16.528000000000002
- type: ndcg_at_5
value: 15.573
- type: precision_at_1
value: 28.499999999999996
- type: precision_at_10
value: 12.25
- type: precision_at_100
value: 3.7600000000000002
- type: precision_at_1000
value: 0.86
- type: precision_at_3
value: 19.167
- type: precision_at_5
value: 16.25
- type: recall_at_1
value: 2.758
- type: recall_at_10
value: 9.164
- type: recall_at_100
value: 21.022
- type: recall_at_1000
value: 37.053999999999995
- type: recall_at_3
value: 5.112
- type: recall_at_5
value: 6.413
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 28.53554681148413
- type: mrr
value: 29.290078704990325
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 76.52926207453477
- type: cos_sim_spearman
value: 68.98528351149498
- type: euclidean_pearson
value: 73.7744559091218
- type: euclidean_spearman
value: 69.03481995814735
- type: manhattan_pearson
value: 73.72818267270651
- type: manhattan_spearman
value: 69.00576442086793
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 61.71540153163407
- type: cos_sim_spearman
value: 58.502746406116614
- type: euclidean_pearson
value: 60.82817999438477
- type: euclidean_spearman
value: 58.988494433752756
- type: manhattan_pearson
value: 60.87147859170236
- type: manhattan_spearman
value: 59.03527382025516
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 72.89990498692094
- type: cos_sim_spearman
value: 74.03028513377879
- type: euclidean_pearson
value: 73.8252088833803
- type: euclidean_spearman
value: 74.15554246478399
- type: manhattan_pearson
value: 73.80947397334666
- type: manhattan_spearman
value: 74.13117958176566
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 70.67974206005906
- type: cos_sim_spearman
value: 66.18263558486296
- type: euclidean_pearson
value: 69.5048876024341
- type: euclidean_spearman
value: 66.36380457878391
- type: manhattan_pearson
value: 69.4895372451589
- type: manhattan_spearman
value: 66.36941569935124
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 73.99856913569187
- type: cos_sim_spearman
value: 75.54712054246464
- type: euclidean_pearson
value: 74.55692573876115
- type: euclidean_spearman
value: 75.34499056740096
- type: manhattan_pearson
value: 74.59342318869683
- type: manhattan_spearman
value: 75.35708317926819
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 72.3343670787494
- type: cos_sim_spearman
value: 73.7136650302399
- type: euclidean_pearson
value: 73.86004257913046
- type: euclidean_spearman
value: 73.9557418048638
- type: manhattan_pearson
value: 73.78919091538661
- type: manhattan_spearman
value: 73.86316425954108
- 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: 79.08159601556619
- type: cos_sim_spearman
value: 80.13910828685532
- type: euclidean_pearson
value: 79.39197806617453
- type: euclidean_spearman
value: 79.85692277871196
- type: manhattan_pearson
value: 79.32452246324705
- type: manhattan_spearman
value: 79.70120373587193
- 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: 62.29720207747786
- type: cos_sim_spearman
value: 65.65260681394685
- type: euclidean_pearson
value: 64.49002165983158
- type: euclidean_spearman
value: 65.25917651158736
- type: manhattan_pearson
value: 64.49981108236335
- type: manhattan_spearman
value: 65.20426825202405
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 71.1871068550574
- type: cos_sim_spearman
value: 71.40167034949341
- type: euclidean_pearson
value: 72.2373684855404
- type: euclidean_spearman
value: 71.90255429812984
- type: manhattan_pearson
value: 72.23173532049509
- type: manhattan_spearman
value: 71.87843489689064
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 68.65000574464773
- type: mrr
value: 88.29363084265044
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 40.76107749144358
- type: mrr
value: 41.03689202953908
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 28.68520527813894
- type: cos_sim_spearman
value: 29.017620841627433
- type: dot_pearson
value: 29.25380949876322
- type: dot_spearman
value: 29.33885250837327
{MODEL_NAME}
This is a sentence-transformers model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed:
pip install -U sentence-transformers
Then you can use the model like this:
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]
model = SentenceTransformer('{MODEL_NAME}')
embeddings = model.encode(sentences)
print(embeddings)
Usage (HuggingFace Transformers)
Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.
from transformers import AutoTokenizer, AutoModel
import torch
#Mean Pooling - Take attention mask into account for correct averaging
def mean_pooling(model_output, attention_mask):
token_embeddings = model_output[0] #First element of model_output contains all token embeddings
input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
# Sentences we want sentence embeddings for
sentences = ['This is an example sentence', 'Each sentence is converted']
# Load model from HuggingFace Hub
tokenizer = AutoTokenizer.from_pretrained('{MODEL_NAME}')
model = AutoModel.from_pretrained('{MODEL_NAME}')
# Tokenize sentences
encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
# Compute token embeddings
with torch.no_grad():
model_output = model(**encoded_input)
# Perform pooling. In this case, mean pooling.
sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask'])
print("Sentence embeddings:")
print(sentence_embeddings)