metadata
tags:
- mteb
model-index:
- name: l3_wordllama_fixed
results:
- task:
type: Classification
dataset:
type: None
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 67.40298507462687
- type: ap
value: 28.677454675181384
- type: f1
value: 60.58324071299079
- task:
type: Classification
dataset:
type: None
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 63.75847499999999
- type: ap
value: 59.00482910406265
- type: f1
value: 63.59920748914567
- task:
type: Classification
dataset:
type: None
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 32.09
- type: f1
value: 31.527306414565835
- task:
type: Retrieval
dataset:
type: None
name: MTEB ArguAna
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 20.413
- type: map_at_10
value: 35.176
- type: map_at_100
value: 36.489
- type: map_at_1000
value: 36.507
- type: map_at_3
value: 30.69
- type: map_at_5
value: 32.859
- type: mrr_at_1
value: 21.124000000000002
- type: mrr_at_10
value: 35.44
- type: mrr_at_100
value: 36.753
- type: mrr_at_1000
value: 36.77
- type: mrr_at_3
value: 30.915
- type: mrr_at_5
value: 33.113
- type: ndcg_at_1
value: 20.413
- type: ndcg_at_10
value: 43.565
- type: ndcg_at_100
value: 49.329
- type: ndcg_at_1000
value: 49.757
- type: ndcg_at_3
value: 34.143
- type: ndcg_at_5
value: 38.046
- type: precision_at_1
value: 20.413
- type: precision_at_10
value: 7.048
- type: precision_at_100
value: 0.9610000000000001
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 14.723
- type: precision_at_5
value: 10.725
- type: recall_at_1
value: 20.413
- type: recall_at_10
value: 70.48400000000001
- type: recall_at_100
value: 96.088
- type: recall_at_1000
value: 99.36
- type: recall_at_3
value: 44.168
- type: recall_at_5
value: 53.627
- task:
type: Clustering
dataset:
type: None
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 39.885229242790935
- task:
type: Clustering
dataset:
type: None
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 29.49720713710708
- task:
type: Reranking
dataset:
type: None
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 55.61953366105678
- type: mrr
value: 70.12344457635315
- task:
type: STS
dataset:
type: None
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 76.26075421266883
- type: cos_sim_spearman
value: 71.32873370732024
- type: euclidean_pearson
value: 74.59312194402976
- type: euclidean_spearman
value: 71.32873370732024
- type: manhattan_pearson
value: 74.5892678336525
- type: manhattan_spearman
value: 71.02450990790472
- task:
type: Classification
dataset:
type: None
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 73.68506493506494
- type: f1
value: 72.88555102531198
- task:
type: Clustering
dataset:
type: None
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 33.29089107203252
- task:
type: Clustering
dataset:
type: None
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 25.19965378718348
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: f46a197baaae43b4f621051089b82a364682dfeb
metrics:
- type: map_at_1
value: 21.508
- type: map_at_10
value: 29.088
- type: map_at_100
value: 30.279
- type: map_at_1000
value: 30.445
- type: map_at_3
value: 26.552999999999997
- type: map_at_5
value: 27.939000000000004
- type: mrr_at_1
value: 26.466
- type: mrr_at_10
value: 34.171
- type: mrr_at_100
value: 35.059000000000005
- type: mrr_at_1000
value: 35.137
- type: mrr_at_3
value: 31.855
- type: mrr_at_5
value: 33.093
- type: ndcg_at_1
value: 26.466
- type: ndcg_at_10
value: 34.097
- type: ndcg_at_100
value: 39.612
- type: ndcg_at_1000
value: 42.819
- type: ndcg_at_3
value: 29.918
- type: ndcg_at_5
value: 31.683
- type: precision_at_1
value: 26.466
- type: precision_at_10
value: 6.422999999999999
- type: precision_at_100
value: 1.15
- type: precision_at_1000
value: 0.17700000000000002
- type: precision_at_3
value: 13.972000000000001
- type: precision_at_5
value: 10.129000000000001
- type: recall_at_1
value: 21.508
- type: recall_at_10
value: 43.699
- type: recall_at_100
value: 68.404
- type: recall_at_1000
value: 89.687
- type: recall_at_3
value: 31.773
- type: recall_at_5
value: 36.687
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
metrics:
- type: map_at_1
value: 16.865
- type: map_at_10
value: 23.164
- type: map_at_100
value: 24.15
- type: map_at_1000
value: 24.288
- type: map_at_3
value: 20.97
- type: map_at_5
value: 22.277
- type: mrr_at_1
value: 21.401
- type: mrr_at_10
value: 27.614
- type: mrr_at_100
value: 28.395
- type: mrr_at_1000
value: 28.469
- type: mrr_at_3
value: 25.594
- type: mrr_at_5
value: 26.735
- type: ndcg_at_1
value: 21.401
- type: ndcg_at_10
value: 27.343
- type: ndcg_at_100
value: 31.726
- type: ndcg_at_1000
value: 34.586
- type: ndcg_at_3
value: 23.723
- type: ndcg_at_5
value: 25.524
- type: precision_at_1
value: 21.401
- type: precision_at_10
value: 5.236
- type: precision_at_100
value: 0.9650000000000001
- type: precision_at_1000
value: 0.146
- type: precision_at_3
value: 11.444
- type: precision_at_5
value: 8.497
- type: recall_at_1
value: 16.865
- type: recall_at_10
value: 35.209
- type: recall_at_100
value: 54.371
- type: recall_at_1000
value: 73.651
- type: recall_at_3
value: 24.943
- type: recall_at_5
value: 29.634
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 25.424000000000003
- type: map_at_10
value: 34.318
- type: map_at_100
value: 35.461999999999996
- type: map_at_1000
value: 35.551
- type: map_at_3
value: 31.694
- type: map_at_5
value: 33.111000000000004
- type: mrr_at_1
value: 29.215999999999998
- type: mrr_at_10
value: 37.333
- type: mrr_at_100
value: 38.223
- type: mrr_at_1000
value: 38.282
- type: mrr_at_3
value: 35.004999999999995
- type: mrr_at_5
value: 36.272
- type: ndcg_at_1
value: 29.215999999999998
- type: ndcg_at_10
value: 39.309
- type: ndcg_at_100
value: 44.718999999999994
- type: ndcg_at_1000
value: 46.877
- type: ndcg_at_3
value: 34.449999999999996
- type: ndcg_at_5
value: 36.675999999999995
- type: precision_at_1
value: 29.215999999999998
- type: precision_at_10
value: 6.483
- type: precision_at_100
value: 1.0330000000000001
- type: precision_at_1000
value: 0.128
- type: precision_at_3
value: 15.298
- type: precision_at_5
value: 10.734
- type: recall_at_1
value: 25.424000000000003
- type: recall_at_10
value: 51.464
- type: recall_at_100
value: 75.87
- type: recall_at_1000
value: 91.77300000000001
- type: recall_at_3
value: 38.396
- type: recall_at_5
value: 43.759
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 5003b3064772da1887988e05400cf3806fe491f2
metrics:
- type: map_at_1
value: 14.674000000000001
- type: map_at_10
value: 18.984
- type: map_at_100
value: 19.867
- type: map_at_1000
value: 19.975
- type: map_at_3
value: 17.488999999999997
- type: map_at_5
value: 18.412
- type: mrr_at_1
value: 15.818999999999999
- type: mrr_at_10
value: 20.472
- type: mrr_at_100
value: 21.342
- type: mrr_at_1000
value: 21.431
- type: mrr_at_3
value: 18.908
- type: mrr_at_5
value: 19.811999999999998
- type: ndcg_at_1
value: 15.818999999999999
- type: ndcg_at_10
value: 21.823
- type: ndcg_at_100
value: 27
- type: ndcg_at_1000
value: 30.064999999999998
- type: ndcg_at_3
value: 18.776
- type: ndcg_at_5
value: 20.395
- type: precision_at_1
value: 15.818999999999999
- type: precision_at_10
value: 3.367
- type: precision_at_100
value: 0.649
- type: precision_at_1000
value: 0.095
- type: precision_at_3
value: 7.797
- type: precision_at_5
value: 5.582
- type: recall_at_1
value: 14.674000000000001
- type: recall_at_10
value: 29.087000000000003
- type: recall_at_100
value: 54.52
- type: recall_at_1000
value: 78.27
- type: recall_at_3
value: 21.075
- type: recall_at_5
value: 24.92
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
metrics:
- type: map_at_1
value: 8.123
- type: map_at_10
value: 13.483
- type: map_at_100
value: 14.457999999999998
- type: map_at_1000
value: 14.579
- type: map_at_3
value: 11.271
- type: map_at_5
value: 12.418
- type: mrr_at_1
value: 10.323
- type: mrr_at_10
value: 16.244
- type: mrr_at_100
value: 17.186
- type: mrr_at_1000
value: 17.27
- type: mrr_at_3
value: 13.91
- type: mrr_at_5
value: 15.116
- type: ndcg_at_1
value: 10.323
- type: ndcg_at_10
value: 17.366999999999997
- type: ndcg_at_100
value: 22.553
- type: ndcg_at_1000
value: 25.817
- type: ndcg_at_3
value: 12.895000000000001
- type: ndcg_at_5
value: 14.856
- type: precision_at_1
value: 10.323
- type: precision_at_10
value: 3.5069999999999997
- type: precision_at_100
value: 0.711
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 6.3020000000000005
- type: precision_at_5
value: 5
- type: recall_at_1
value: 8.123
- type: recall_at_10
value: 26.889000000000003
- type: recall_at_100
value: 50.397999999999996
- type: recall_at_1000
value: 74.244
- type: recall_at_3
value: 14.691
- type: recall_at_5
value: 19.503
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
metrics:
- type: map_at_1
value: 18.607000000000003
- type: map_at_10
value: 25.596000000000004
- type: map_at_100
value: 26.984
- type: map_at_1000
value: 27.125
- type: map_at_3
value: 22.917
- type: map_at_5
value: 24.201
- type: mrr_at_1
value: 22.907
- type: mrr_at_10
value: 30.384
- type: mrr_at_100
value: 31.432
- type: mrr_at_1000
value: 31.5
- type: mrr_at_3
value: 27.703
- type: mrr_at_5
value: 29.137
- type: ndcg_at_1
value: 22.907
- type: ndcg_at_10
value: 30.824
- type: ndcg_at_100
value: 37.265
- type: ndcg_at_1000
value: 40.191
- type: ndcg_at_3
value: 25.913000000000004
- type: ndcg_at_5
value: 27.849
- type: precision_at_1
value: 22.907
- type: precision_at_10
value: 5.9479999999999995
- type: precision_at_100
value: 1.094
- type: precision_at_1000
value: 0.155
- type: precision_at_3
value: 12.384
- type: precision_at_5
value: 9.009
- type: recall_at_1
value: 18.607000000000003
- type: recall_at_10
value: 42.082
- type: recall_at_100
value: 70.018
- type: recall_at_1000
value: 90.003
- type: recall_at_3
value: 27.932000000000002
- type: recall_at_5
value: 32.975
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
metrics:
- type: map_at_1
value: 14.52
- type: map_at_10
value: 21.61
- type: map_at_100
value: 22.827
- type: map_at_1000
value: 22.964000000000002
- type: map_at_3
value: 19.500999999999998
- type: map_at_5
value: 20.798
- type: mrr_at_1
value: 17.694
- type: mrr_at_10
value: 25.161
- type: mrr_at_100
value: 26.180999999999997
- type: mrr_at_1000
value: 26.269
- type: mrr_at_3
value: 23.116
- type: mrr_at_5
value: 24.412
- type: ndcg_at_1
value: 17.694
- type: ndcg_at_10
value: 25.924000000000003
- type: ndcg_at_100
value: 31.615
- type: ndcg_at_1000
value: 34.955000000000005
- type: ndcg_at_3
value: 22.161
- type: ndcg_at_5
value: 24.16
- type: precision_at_1
value: 17.694
- type: precision_at_10
value: 4.874
- type: precision_at_100
value: 0.91
- type: precision_at_1000
value: 0.13799999999999998
- type: precision_at_3
value: 10.731
- type: precision_at_5
value: 8.014000000000001
- type: recall_at_1
value: 14.52
- type: recall_at_10
value: 35.369
- type: recall_at_100
value: 60
- type: recall_at_1000
value: 83.66799999999999
- type: recall_at_3
value: 25.058999999999997
- type: recall_at_5
value: 30.131999999999998
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 15.35675
- type: map_at_10
value: 21.087750000000007
- type: map_at_100
value: 22.12925
- type: map_at_1000
value: 22.262
- type: map_at_3
value: 19.156249999999996
- type: map_at_5
value: 20.202916666666663
- type: mrr_at_1
value: 18.301583333333333
- type: mrr_at_10
value: 24.283083333333334
- type: mrr_at_100
value: 25.176583333333337
- type: mrr_at_1000
value: 25.262083333333337
- type: mrr_at_3
value: 22.38533333333333
- type: mrr_at_5
value: 23.408
- type: ndcg_at_1
value: 18.301583333333333
- type: ndcg_at_10
value: 24.931416666666667
- type: ndcg_at_100
value: 30.107249999999997
- type: ndcg_at_1000
value: 33.292500000000004
- type: ndcg_at_3
value: 21.380833333333335
- type: ndcg_at_5
value: 22.965416666666663
- type: precision_at_1
value: 18.301583333333333
- type: precision_at_10
value: 4.475583333333334
- type: precision_at_100
value: 0.84875
- type: precision_at_1000
value: 0.13066666666666668
- type: precision_at_3
value: 9.858500000000001
- type: precision_at_5
value: 7.125333333333334
- type: recall_at_1
value: 15.35675
- type: recall_at_10
value: 33.385666666666665
- type: recall_at_100
value: 57.03541666666667
- type: recall_at_1000
value: 80.00874999999999
- type: recall_at_3
value: 23.440833333333337
- type: recall_at_5
value: 27.48841666666666
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
metrics:
- type: map_at_1
value: 13.023000000000001
- type: map_at_10
value: 17.116999999999997
- type: map_at_100
value: 18.016
- type: map_at_1000
value: 18.124000000000002
- type: map_at_3
value: 15.654000000000002
- type: map_at_5
value: 16.494
- type: mrr_at_1
value: 14.877
- type: mrr_at_10
value: 19.061
- type: mrr_at_100
value: 19.933
- type: mrr_at_1000
value: 20.027
- type: mrr_at_3
value: 17.740000000000002
- type: mrr_at_5
value: 18.384
- type: ndcg_at_1
value: 14.877
- type: ndcg_at_10
value: 19.991999999999997
- type: ndcg_at_100
value: 24.836
- type: ndcg_at_1000
value: 27.922000000000004
- type: ndcg_at_3
value: 17.221
- type: ndcg_at_5
value: 18.496000000000002
- type: precision_at_1
value: 14.877
- type: precision_at_10
value: 3.298
- type: precision_at_100
value: 0.629
- type: precision_at_1000
value: 0.098
- type: precision_at_3
value: 7.617999999999999
- type: precision_at_5
value: 5.428999999999999
- type: recall_at_1
value: 13.023000000000001
- type: recall_at_10
value: 27.064
- type: recall_at_100
value: 49.971
- type: recall_at_1000
value: 73.195
- type: recall_at_3
value: 19.273
- type: recall_at_5
value: 22.465
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 8.86
- type: map_at_10
value: 12.806999999999999
- type: map_at_100
value: 13.55
- type: map_at_1000
value: 13.684
- type: map_at_3
value: 11.368
- type: map_at_5
value: 12.106
- type: mrr_at_1
value: 10.943
- type: mrr_at_10
value: 15.397
- type: mrr_at_100
value: 16.139
- type: mrr_at_1000
value: 16.242
- type: mrr_at_3
value: 13.805
- type: mrr_at_5
value: 14.601
- type: ndcg_at_1
value: 10.943
- type: ndcg_at_10
value: 15.693999999999999
- type: ndcg_at_100
value: 19.869
- type: ndcg_at_1000
value: 23.579
- type: ndcg_at_3
value: 12.920000000000002
- type: ndcg_at_5
value: 14.054
- type: precision_at_1
value: 10.943
- type: precision_at_10
value: 2.97
- type: precision_at_100
value: 0.609
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 6.148
- type: precision_at_5
value: 4.529
- type: recall_at_1
value: 8.86
- type: recall_at_10
value: 22.041
- type: recall_at_100
value: 41.528
- type: recall_at_1000
value: 68.917
- type: recall_at_3
value: 14.257
- type: recall_at_5
value: 17.191000000000003
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
metrics:
- type: map_at_1
value: 14.508
- type: map_at_10
value: 19.814999999999998
- type: map_at_100
value: 20.761
- type: map_at_1000
value: 20.899
- type: map_at_3
value: 17.959
- type: map_at_5
value: 18.877
- type: mrr_at_1
value: 17.444000000000003
- type: mrr_at_10
value: 23.067
- type: mrr_at_100
value: 23.906
- type: mrr_at_1000
value: 24.015
- type: mrr_at_3
value: 21.191
- type: mrr_at_5
value: 22.124
- type: ndcg_at_1
value: 17.444000000000003
- type: ndcg_at_10
value: 23.519000000000002
- type: ndcg_at_100
value: 28.546
- type: ndcg_at_1000
value: 32.243
- type: ndcg_at_3
value: 19.958000000000002
- type: ndcg_at_5
value: 21.391
- type: precision_at_1
value: 17.444000000000003
- type: precision_at_10
value: 4.104
- type: precision_at_100
value: 0.758
- type: precision_at_1000
value: 0.11900000000000001
- type: precision_at_3
value: 9.142
- type: precision_at_5
value: 6.474
- type: recall_at_1
value: 14.508
- type: recall_at_10
value: 31.788
- type: recall_at_100
value: 55.047999999999995
- type: recall_at_1000
value: 82.155
- type: recall_at_3
value: 21.857
- type: recall_at_5
value: 25.549
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 16.733
- type: map_at_10
value: 21.721
- type: map_at_100
value: 22.986
- type: map_at_1000
value: 23.198
- type: map_at_3
value: 20.229
- type: map_at_5
value: 21.066
- type: mrr_at_1
value: 19.96
- type: mrr_at_10
value: 25.683
- type: mrr_at_100
value: 26.662000000000003
- type: mrr_at_1000
value: 26.749000000000002
- type: mrr_at_3
value: 24.209
- type: mrr_at_5
value: 25.049
- type: ndcg_at_1
value: 19.96
- type: ndcg_at_10
value: 25.413999999999998
- type: ndcg_at_100
value: 30.916
- type: ndcg_at_1000
value: 34.678
- type: ndcg_at_3
value: 23.138
- type: ndcg_at_5
value: 24.169
- type: precision_at_1
value: 19.96
- type: precision_at_10
value: 4.743
- type: precision_at_100
value: 1.126
- type: precision_at_1000
value: 0.201
- type: precision_at_3
value: 10.935
- type: precision_at_5
value: 7.707999999999999
- type: recall_at_1
value: 16.733
- type: recall_at_10
value: 31.512
- type: recall_at_100
value: 57.079
- type: recall_at_1000
value: 82.661
- type: recall_at_3
value: 24.252000000000002
- type: recall_at_5
value: 27.317000000000004
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 11.436
- type: map_at_10
value: 15.35
- type: map_at_100
value: 16.211000000000002
- type: map_at_1000
value: 16.311999999999998
- type: map_at_3
value: 14.27
- type: map_at_5
value: 14.735999999999999
- type: mrr_at_1
value: 12.568999999999999
- type: mrr_at_10
value: 16.81
- type: mrr_at_100
value: 17.660999999999998
- type: mrr_at_1000
value: 17.754
- type: mrr_at_3
value: 15.588
- type: mrr_at_5
value: 16.161
- type: ndcg_at_1
value: 12.568999999999999
- type: ndcg_at_10
value: 17.871000000000002
- type: ndcg_at_100
value: 22.63
- type: ndcg_at_1000
value: 25.778000000000002
- type: ndcg_at_3
value: 15.497
- type: ndcg_at_5
value: 16.332
- type: precision_at_1
value: 12.568999999999999
- type: precision_at_10
value: 2.754
- type: precision_at_100
value: 0.551
- type: precision_at_1000
value: 0.087
- type: precision_at_3
value: 6.531000000000001
- type: precision_at_5
value: 4.399
- type: recall_at_1
value: 11.436
- type: recall_at_10
value: 24.424
- type: recall_at_100
value: 47.217999999999996
- type: recall_at_1000
value: 71.881
- type: recall_at_3
value: 17.782
- type: recall_at_5
value: 19.729
- task:
type: Retrieval
dataset:
type: None
name: MTEB ClimateFEVER
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 6.822
- type: map_at_10
value: 12.872
- type: map_at_100
value: 14.504
- type: map_at_1000
value: 14.712
- type: map_at_3
value: 10.357
- type: map_at_5
value: 11.700000000000001
- type: mrr_at_1
value: 15.895999999999999
- type: mrr_at_10
value: 26.407999999999998
- type: mrr_at_100
value: 27.528999999999996
- type: mrr_at_1000
value: 27.586
- type: mrr_at_3
value: 22.714000000000002
- type: mrr_at_5
value: 24.762999999999998
- type: ndcg_at_1
value: 15.895999999999999
- type: ndcg_at_10
value: 19.643
- type: ndcg_at_100
value: 26.863999999999997
- type: ndcg_at_1000
value: 30.804
- type: ndcg_at_3
value: 14.914
- type: ndcg_at_5
value: 16.723
- type: precision_at_1
value: 15.895999999999999
- type: precision_at_10
value: 6.612
- type: precision_at_100
value: 1.434
- type: precision_at_1000
value: 0.216
- type: precision_at_3
value: 11.488
- type: precision_at_5
value: 9.354999999999999
- type: recall_at_1
value: 6.822
- type: recall_at_10
value: 25.478
- type: recall_at_100
value: 50.94
- type: recall_at_1000
value: 73.264
- type: recall_at_3
value: 14.228
- type: recall_at_5
value: 18.91
- task:
type: Retrieval
dataset:
type: None
name: MTEB DBPedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 4.601999999999999
- type: map_at_10
value: 9.225999999999999
- type: map_at_100
value: 12.692
- type: map_at_1000
value: 13.65
- type: map_at_3
value: 6.883
- type: map_at_5
value: 7.904
- type: mrr_at_1
value: 34
- type: mrr_at_10
value: 45.83
- type: mrr_at_100
value: 46.608
- type: mrr_at_1000
value: 46.635
- type: mrr_at_3
value: 42.583
- type: mrr_at_5
value: 44.721
- type: ndcg_at_1
value: 24.75
- type: ndcg_at_10
value: 21.092
- type: ndcg_at_100
value: 25.288
- type: ndcg_at_1000
value: 32.550000000000004
- type: ndcg_at_3
value: 22.808999999999997
- type: ndcg_at_5
value: 21.931
- type: precision_at_1
value: 34
- type: precision_at_10
value: 18.525
- type: precision_at_100
value: 6.265
- type: precision_at_1000
value: 1.395
- type: precision_at_3
value: 27.500000000000004
- type: precision_at_5
value: 23.799999999999997
- type: recall_at_1
value: 4.601999999999999
- type: recall_at_10
value: 13.578000000000001
- type: recall_at_100
value: 32.438
- type: recall_at_1000
value: 57.067
- type: recall_at_3
value: 8.013
- type: recall_at_5
value: 10.057
- task:
type: Classification
dataset:
type: None
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 39
- type: f1
value: 35.038106148143335
- task:
type: Retrieval
dataset:
type: None
name: MTEB FEVER
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 16.577
- type: map_at_10
value: 25.397
- type: map_at_100
value: 26.493
- type: map_at_1000
value: 26.56
- type: map_at_3
value: 22.523
- type: map_at_5
value: 24.102
- type: mrr_at_1
value: 17.717
- type: mrr_at_10
value: 26.999000000000002
- type: mrr_at_100
value: 28.084999999999997
- type: mrr_at_1000
value: 28.144999999999996
- type: mrr_at_3
value: 24.01
- type: mrr_at_5
value: 25.669999999999998
- type: ndcg_at_1
value: 17.717
- type: ndcg_at_10
value: 30.836999999999996
- type: ndcg_at_100
value: 36.278
- type: ndcg_at_1000
value: 38.139
- type: ndcg_at_3
value: 24.868000000000002
- type: ndcg_at_5
value: 27.701999999999998
- type: precision_at_1
value: 17.717
- type: precision_at_10
value: 5.0569999999999995
- type: precision_at_100
value: 0.791
- type: precision_at_1000
value: 0.097
- type: precision_at_3
value: 10.850999999999999
- type: precision_at_5
value: 8.004999999999999
- type: recall_at_1
value: 16.577
- type: recall_at_10
value: 46.451
- type: recall_at_100
value: 71.61800000000001
- type: recall_at_1000
value: 85.902
- type: recall_at_3
value: 30.130000000000003
- type: recall_at_5
value: 36.902
- task:
type: Retrieval
dataset:
type: None
name: MTEB FiQA2018
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 7.0680000000000005
- type: map_at_10
value: 12.424
- type: map_at_100
value: 13.750000000000002
- type: map_at_1000
value: 13.963999999999999
- type: map_at_3
value: 10.41
- type: map_at_5
value: 11.459999999999999
- type: mrr_at_1
value: 14.506
- type: mrr_at_10
value: 21.644
- type: mrr_at_100
value: 22.708000000000002
- type: mrr_at_1000
value: 22.811
- type: mrr_at_3
value: 19.084
- type: mrr_at_5
value: 20.543
- type: ndcg_at_1
value: 14.506
- type: ndcg_at_10
value: 17.485
- type: ndcg_at_100
value: 23.565
- type: ndcg_at_1000
value: 28.177000000000003
- type: ndcg_at_3
value: 14.423
- type: ndcg_at_5
value: 15.536
- type: precision_at_1
value: 14.506
- type: precision_at_10
value: 5.122999999999999
- type: precision_at_100
value: 1.13
- type: precision_at_1000
value: 0.193
- type: precision_at_3
value: 9.722
- type: precision_at_5
value: 7.623
- type: recall_at_1
value: 7.0680000000000005
- type: recall_at_10
value: 23.423
- type: recall_at_100
value: 46.682
- type: recall_at_1000
value: 75.22999999999999
- type: recall_at_3
value: 13.544999999999998
- type: recall_at_5
value: 17.448
- task:
type: Retrieval
dataset:
type: None
name: MTEB HotpotQA
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 21.837
- type: map_at_10
value: 30.614
- type: map_at_100
value: 31.6
- type: map_at_1000
value: 31.71
- type: map_at_3
value: 28.219
- type: map_at_5
value: 29.598000000000003
- type: mrr_at_1
value: 43.673
- type: mrr_at_10
value: 51.627
- type: mrr_at_100
value: 52.323
- type: mrr_at_1000
value: 52.364
- type: mrr_at_3
value: 49.527
- type: mrr_at_5
value: 50.76500000000001
- type: ndcg_at_1
value: 43.673
- type: ndcg_at_10
value: 38.696000000000005
- type: ndcg_at_100
value: 43.124
- type: ndcg_at_1000
value: 45.552
- type: ndcg_at_3
value: 34.338
- type: ndcg_at_5
value: 36.553000000000004
- type: precision_at_1
value: 43.673
- type: precision_at_10
value: 8.432
- type: precision_at_100
value: 1.198
- type: precision_at_1000
value: 0.152
- type: precision_at_3
value: 21.58
- type: precision_at_5
value: 14.706
- type: recall_at_1
value: 21.837
- type: recall_at_10
value: 42.161
- type: recall_at_100
value: 59.899
- type: recall_at_1000
value: 76.036
- type: recall_at_3
value: 32.37
- type: recall_at_5
value: 36.766
- task:
type: Classification
dataset:
type: None
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 65.0232
- type: ap
value: 59.81346113056583
- type: f1
value: 64.78827292080608
- task:
type: Retrieval
dataset:
type: None
name: MTEB MSMARCO
config: default
split: dev
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 6.614000000000001
- type: map_at_10
value: 11.733
- type: map_at_100
value: 12.757
- type: map_at_1000
value: 12.873999999999999
- type: map_at_3
value: 9.783999999999999
- type: map_at_5
value: 10.807
- type: mrr_at_1
value: 6.834
- type: mrr_at_10
value: 12.074
- type: mrr_at_100
value: 13.099
- type: mrr_at_1000
value: 13.211
- type: mrr_at_3
value: 10.098
- type: mrr_at_5
value: 11.132
- type: ndcg_at_1
value: 6.834
- type: ndcg_at_10
value: 15.046000000000001
- type: ndcg_at_100
value: 20.657
- type: ndcg_at_1000
value: 24.112000000000002
- type: ndcg_at_3
value: 10.95
- type: ndcg_at_5
value: 12.796
- type: precision_at_1
value: 6.834
- type: precision_at_10
value: 2.633
- type: precision_at_100
value: 0.555
- type: precision_at_1000
value: 0.08499999999999999
- type: precision_at_3
value: 4.842
- type: precision_at_5
value: 3.8249999999999997
- type: recall_at_1
value: 6.614000000000001
- type: recall_at_10
value: 25.39
- type: recall_at_100
value: 52.793
- type: recall_at_1000
value: 80.415
- type: recall_at_3
value: 14.033000000000001
- type: recall_at_5
value: 18.496000000000002
- task:
type: Classification
dataset:
type: None
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 85.58139534883719
- type: f1
value: 84.72133199480218
- task:
type: Classification
dataset:
type: None
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 56.2608299133607
- type: f1
value: 36.74698315617003
- task:
type: Classification
dataset:
type: None
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 61.993947545393404
- type: f1
value: 59.68762807193991
- task:
type: Classification
dataset:
type: None
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 68.49361129791525
- type: f1
value: 67.16568787114376
- task:
type: Clustering
dataset:
type: None
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 30.675655693797378
- task:
type: Clustering
dataset:
type: None
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 26.87954369022046
- task:
type: Reranking
dataset:
type: None
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 30.47254787311633
- type: mrr
value: 31.476216991631862
- task:
type: Retrieval
dataset:
type: None
name: MTEB NFCorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 2.703
- type: map_at_10
value: 6.99
- type: map_at_100
value: 9.191
- type: map_at_1000
value: 10.385
- type: map_at_3
value: 5.015
- type: map_at_5
value: 5.904
- type: mrr_at_1
value: 30.031000000000002
- type: mrr_at_10
value: 40.001
- type: mrr_at_100
value: 40.724
- type: mrr_at_1000
value: 40.778
- type: mrr_at_3
value: 37.358000000000004
- type: mrr_at_5
value: 38.426
- type: ndcg_at_1
value: 28.483000000000004
- type: ndcg_at_10
value: 23.229
- type: ndcg_at_100
value: 22.115000000000002
- type: ndcg_at_1000
value: 31.263
- type: ndcg_at_3
value: 26.432
- type: ndcg_at_5
value: 25.074999999999996
- type: precision_at_1
value: 30.031000000000002
- type: precision_at_10
value: 17.957
- type: precision_at_100
value: 6.3
- type: precision_at_1000
value: 1.909
- type: precision_at_3
value: 26.006
- type: precision_at_5
value: 22.786
- type: recall_at_1
value: 2.703
- type: recall_at_10
value: 11.333
- type: recall_at_100
value: 24.629
- type: recall_at_1000
value: 57.162
- type: recall_at_3
value: 6.148
- type: recall_at_5
value: 7.902000000000001
- task:
type: Retrieval
dataset:
type: None
name: MTEB NQ
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 10.904
- type: map_at_10
value: 18.551000000000002
- type: map_at_100
value: 19.913
- type: map_at_1000
value: 20.008
- type: map_at_3
value: 15.8
- type: map_at_5
value: 17.261000000000003
- type: mrr_at_1
value: 12.457
- type: mrr_at_10
value: 20.319000000000003
- type: mrr_at_100
value: 21.532999999999998
- type: mrr_at_1000
value: 21.61
- type: mrr_at_3
value: 17.449
- type: mrr_at_5
value: 19.023
- type: ndcg_at_1
value: 12.457
- type: ndcg_at_10
value: 23.488999999999997
- type: ndcg_at_100
value: 30.109
- type: ndcg_at_1000
value: 32.725
- type: ndcg_at_3
value: 17.73
- type: ndcg_at_5
value: 20.387
- type: precision_at_1
value: 12.457
- type: precision_at_10
value: 4.3709999999999996
- type: precision_at_100
value: 0.8109999999999999
- type: precision_at_1000
value: 0.106
- type: precision_at_3
value: 8.333
- type: precision_at_5
value: 6.489000000000001
- type: recall_at_1
value: 10.904
- type: recall_at_10
value: 37.143
- type: recall_at_100
value: 67.432
- type: recall_at_1000
value: 87.59400000000001
- type: recall_at_3
value: 21.734
- type: recall_at_5
value: 27.927999999999997
- task:
type: Retrieval
dataset:
type: None
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 63.499
- type: map_at_10
value: 77.088
- type: map_at_100
value: 77.91
- type: map_at_1000
value: 77.935
- type: map_at_3
value: 73.88900000000001
- type: map_at_5
value: 75.797
- type: mrr_at_1
value: 73.2
- type: mrr_at_10
value: 80.927
- type: mrr_at_100
value: 81.146
- type: mrr_at_1000
value: 81.148
- type: mrr_at_3
value: 79.427
- type: mrr_at_5
value: 80.363
- type: ndcg_at_1
value: 73.22999999999999
- type: ndcg_at_10
value: 81.926
- type: ndcg_at_100
value: 83.929
- type: ndcg_at_1000
value: 84.127
- type: ndcg_at_3
value: 78.071
- type: ndcg_at_5
value: 80.015
- type: precision_at_1
value: 73.22999999999999
- type: precision_at_10
value: 12.639
- type: precision_at_100
value: 1.5110000000000001
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 34.217
- type: precision_at_5
value: 22.722
- type: recall_at_1
value: 63.499
- type: recall_at_10
value: 91.646
- type: recall_at_100
value: 98.92999999999999
- type: recall_at_1000
value: 99.914
- type: recall_at_3
value: 80.703
- type: recall_at_5
value: 86.048
- task:
type: Clustering
dataset:
type: None
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 43.80644854168368
- task:
type: Clustering
dataset:
type: None
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 48.708800185514974
- task:
type: Retrieval
dataset:
type: None
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.773
- type: map_at_10
value: 9.305
- type: map_at_100
value: 11.469
- type: map_at_1000
value: 11.828
- type: map_at_3
value: 6.675000000000001
- type: map_at_5
value: 7.965
- type: mrr_at_1
value: 18.6
- type: mrr_at_10
value: 28.392
- type: mrr_at_100
value: 29.664
- type: mrr_at_1000
value: 29.724
- type: mrr_at_3
value: 25.183
- type: mrr_at_5
value: 26.893
- type: ndcg_at_1
value: 18.6
- type: ndcg_at_10
value: 16.292
- type: ndcg_at_100
value: 25
- type: ndcg_at_1000
value: 31.136000000000003
- type: ndcg_at_3
value: 15.212
- type: ndcg_at_5
value: 13.354
- type: precision_at_1
value: 18.6
- type: precision_at_10
value: 8.57
- type: precision_at_100
value: 2.122
- type: precision_at_1000
value: 0.359
- type: precision_at_3
value: 14.267
- type: precision_at_5
value: 11.799999999999999
- type: recall_at_1
value: 3.773
- type: recall_at_10
value: 17.352999999999998
- type: recall_at_100
value: 43.062
- type: recall_at_1000
value: 72.775
- type: recall_at_3
value: 8.677999999999999
- type: recall_at_5
value: 11.958
- task:
type: STS
dataset:
type: None
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 77.70369570699015
- type: cos_sim_spearman
value: 67.00421728409633
- type: euclidean_pearson
value: 71.7303217538682
- type: euclidean_spearman
value: 67.00421728409633
- type: manhattan_pearson
value: 71.62358736603595
- type: manhattan_spearman
value: 66.93696271331966
- task:
type: STS
dataset:
type: None
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 72.3464707081196
- type: cos_sim_spearman
value: 63.91086584602619
- type: euclidean_pearson
value: 68.22390430027092
- type: euclidean_spearman
value: 63.91086584602619
- type: manhattan_pearson
value: 68.14984324829423
- type: manhattan_spearman
value: 63.86219497566778
- task:
type: STS
dataset:
type: None
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 72.80276772789091
- type: cos_sim_spearman
value: 73.34700075766551
- type: euclidean_pearson
value: 72.88415583236083
- type: euclidean_spearman
value: 73.34700075766551
- type: manhattan_pearson
value: 72.71141307415924
- type: manhattan_spearman
value: 73.10626124984765
- task:
type: STS
dataset:
type: None
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 74.00122656955553
- type: cos_sim_spearman
value: 69.07090069837032
- type: euclidean_pearson
value: 71.79931055857548
- type: euclidean_spearman
value: 69.07090069837032
- type: manhattan_pearson
value: 71.71577354549707
- type: manhattan_spearman
value: 69.0177557195104
- task:
type: STS
dataset:
type: None
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 81.17450916936498
- type: cos_sim_spearman
value: 81.53568053124042
- type: euclidean_pearson
value: 81.04779414575466
- type: euclidean_spearman
value: 81.53568053124042
- type: manhattan_pearson
value: 80.95262960295437
- type: manhattan_spearman
value: 81.43365291054681
- task:
type: STS
dataset:
type: None
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 75.7401837172966
- type: cos_sim_spearman
value: 76.13099867057305
- type: euclidean_pearson
value: 75.56851096153042
- type: euclidean_spearman
value: 76.13099867057305
- type: manhattan_pearson
value: 75.4483276223799
- type: manhattan_spearman
value: 75.96804558062843
- task:
type: STS
dataset:
type: None
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 85.0294369233462
- type: cos_sim_spearman
value: 85.17543345937065
- type: euclidean_pearson
value: 84.55546274084796
- type: euclidean_spearman
value: 85.17543345937065
- type: manhattan_pearson
value: 84.48053547013386
- type: manhattan_spearman
value: 85.1543300887167
- task:
type: STS
dataset:
type: None
name: MTEB STS22 (en)
config: en
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson
value: 61.225097153955176
- type: cos_sim_spearman
value: 60.16234340521003
- type: euclidean_pearson
value: 62.59204214787284
- type: euclidean_spearman
value: 60.16234340521003
- type: manhattan_pearson
value: 62.17494761193987
- type: manhattan_spearman
value: 59.80098747946264
- task:
type: STS
dataset:
type: None
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 78.76720129845401
- type: cos_sim_spearman
value: 77.01581381977705
- type: euclidean_pearson
value: 78.25405293225397
- type: euclidean_spearman
value: 77.01581381977705
- type: manhattan_pearson
value: 78.1737464440924
- type: manhattan_spearman
value: 76.98020258619971
- task:
type: Reranking
dataset:
type: None
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 83.38429389881968
- type: mrr
value: 94.92898441427853
- task:
type: Retrieval
dataset:
type: None
name: MTEB SciFact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 39.306000000000004
- type: map_at_10
value: 49.913000000000004
- type: map_at_100
value: 50.965
- type: map_at_1000
value: 51.022999999999996
- type: map_at_3
value: 47.398
- type: map_at_5
value: 48.962
- type: mrr_at_1
value: 41
- type: mrr_at_10
value: 51.147
- type: mrr_at_100
value: 52.022
- type: mrr_at_1000
value: 52.073
- type: mrr_at_3
value: 48.888999999999996
- type: mrr_at_5
value: 50.239
- type: ndcg_at_1
value: 41
- type: ndcg_at_10
value: 55.033
- type: ndcg_at_100
value: 59.364
- type: ndcg_at_1000
value: 60.849
- type: ndcg_at_3
value: 50.159
- type: ndcg_at_5
value: 52.788999999999994
- type: precision_at_1
value: 41
- type: precision_at_10
value: 7.632999999999999
- type: precision_at_100
value: 0.997
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 20.222
- type: precision_at_5
value: 13.667000000000002
- type: recall_at_1
value: 39.306000000000004
- type: recall_at_10
value: 69.45599999999999
- type: recall_at_100
value: 88.022
- type: recall_at_1000
value: 99.6
- type: recall_at_3
value: 56.27799999999999
- type: recall_at_5
value: 62.639
- task:
type: PairClassification
dataset:
type: None
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.73960396039604
- type: cos_sim_ap
value: 91.77061379171414
- type: cos_sim_f1
value: 86.49746192893402
- type: cos_sim_precision
value: 87.83505154639175
- type: cos_sim_recall
value: 85.2
- type: dot_accuracy
value: 99.73960396039604
- type: dot_ap
value: 91.77061379171414
- type: dot_f1
value: 86.49746192893402
- type: dot_precision
value: 87.83505154639175
- type: dot_recall
value: 85.2
- type: euclidean_accuracy
value: 99.73960396039604
- type: euclidean_ap
value: 91.77061379171414
- type: euclidean_f1
value: 86.49746192893402
- type: euclidean_precision
value: 87.83505154639175
- type: euclidean_recall
value: 85.2
- type: manhattan_accuracy
value: 99.73861386138614
- type: manhattan_ap
value: 91.73584684604442
- type: manhattan_f1
value: 86.41722193746797
- type: manhattan_precision
value: 88.64353312302839
- type: manhattan_recall
value: 84.3
- type: max_accuracy
value: 99.73960396039604
- type: max_ap
value: 91.77061379171414
- type: max_f1
value: 86.49746192893402
- task:
type: Clustering
dataset:
type: None
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 53.7931704300123
- task:
type: Clustering
dataset:
type: None
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 32.48651577951652
- task:
type: Reranking
dataset:
type: None
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 41.818447756127505
- type: mrr
value: 42.1808155080214
- task:
type: Summarization
dataset:
type: None
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 29.799110359832028
- type: cos_sim_spearman
value: 30.826213689865888
- type: dot_pearson
value: 29.79911097173556
- type: dot_spearman
value: 30.8964325010969
- task:
type: Retrieval
dataset:
type: None
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.186
- type: map_at_10
value: 1.304
- type: map_at_100
value: 6.688
- type: map_at_1000
value: 15.162
- type: map_at_3
value: 0.46499999999999997
- type: map_at_5
value: 0.7100000000000001
- type: mrr_at_1
value: 72
- type: mrr_at_10
value: 79.51899999999999
- type: mrr_at_100
value: 79.673
- type: mrr_at_1000
value: 79.673
- type: mrr_at_3
value: 77.667
- type: mrr_at_5
value: 78.567
- type: ndcg_at_1
value: 66
- type: ndcg_at_10
value: 58.172000000000004
- type: ndcg_at_100
value: 41.583999999999996
- type: ndcg_at_1000
value: 34.916000000000004
- type: ndcg_at_3
value: 62
- type: ndcg_at_5
value: 60.104
- type: precision_at_1
value: 72
- type: precision_at_10
value: 62
- type: precision_at_100
value: 43.32
- type: precision_at_1000
value: 15.962000000000002
- type: precision_at_3
value: 65.333
- type: precision_at_5
value: 63.6
- type: recall_at_1
value: 0.186
- type: recall_at_10
value: 1.525
- type: recall_at_100
value: 9.600999999999999
- type: recall_at_1000
value: 32.72
- type: recall_at_3
value: 0.492
- type: recall_at_5
value: 0.782
- task:
type: Retrieval
dataset:
type: None
name: MTEB Touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 2.6100000000000003
- type: map_at_10
value: 10.317
- type: map_at_100
value: 16.651
- type: map_at_1000
value: 18.4
- type: map_at_3
value: 4.952999999999999
- type: map_at_5
value: 7.037
- type: mrr_at_1
value: 34.694
- type: mrr_at_10
value: 51.351
- type: mrr_at_100
value: 51.912000000000006
- type: mrr_at_1000
value: 51.912000000000006
- type: mrr_at_3
value: 46.599000000000004
- type: mrr_at_5
value: 49.762
- type: ndcg_at_1
value: 31.633
- type: ndcg_at_10
value: 27.601
- type: ndcg_at_100
value: 39.080999999999996
- type: ndcg_at_1000
value: 50.308
- type: ndcg_at_3
value: 30.020000000000003
- type: ndcg_at_5
value: 29.465999999999998
- type: precision_at_1
value: 34.694
- type: precision_at_10
value: 26.122
- type: precision_at_100
value: 8.530999999999999
- type: precision_at_1000
value: 1.5650000000000002
- type: precision_at_3
value: 31.973000000000003
- type: precision_at_5
value: 31.019999999999996
- type: recall_at_1
value: 2.6100000000000003
- type: recall_at_10
value: 17.166
- type: recall_at_100
value: 50.480999999999995
- type: recall_at_1000
value: 84.87599999999999
- type: recall_at_3
value: 6.026
- type: recall_at_5
value: 10.165000000000001
- task:
type: Classification
dataset:
type: None
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 66.8218
- type: ap
value: 11.906071313412117
- type: f1
value: 50.99103419180737
- task:
type: Classification
dataset:
type: None
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 50.1188455008489
- type: f1
value: 50.19144196024773
- task:
type: Clustering
dataset:
type: None
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 33.550995025713995
- task:
type: PairClassification
dataset:
type: None
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 79.29307981164689
- type: cos_sim_ap
value: 48.474835734978406
- type: cos_sim_f1
value: 48.95389383959706
- type: cos_sim_precision
value: 38.674625038261404
- type: cos_sim_recall
value: 66.6754617414248
- type: dot_accuracy
value: 79.29307981164689
- type: dot_ap
value: 48.4748345893063
- type: dot_f1
value: 48.95389383959706
- type: dot_precision
value: 38.674625038261404
- type: dot_recall
value: 66.6754617414248
- type: euclidean_accuracy
value: 79.29307981164689
- type: euclidean_ap
value: 48.47484295524529
- type: euclidean_f1
value: 48.95389383959706
- type: euclidean_precision
value: 38.674625038261404
- type: euclidean_recall
value: 66.6754617414248
- type: manhattan_accuracy
value: 79.34672468260118
- type: manhattan_ap
value: 48.423218655778356
- type: manhattan_f1
value: 48.93181153058239
- type: manhattan_precision
value: 38.81752050766135
- type: manhattan_recall
value: 66.17414248021109
- type: max_accuracy
value: 79.34672468260118
- type: max_ap
value: 48.47484295524529
- type: max_f1
value: 48.95389383959706
- task:
type: PairClassification
dataset:
type: None
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 86.65541196103544
- type: cos_sim_ap
value: 80.9065470343605
- type: cos_sim_f1
value: 73.7394283267316
- type: cos_sim_precision
value: 68.7196541403392
- type: cos_sim_recall
value: 79.55035417308285
- type: dot_accuracy
value: 86.65541196103544
- type: dot_ap
value: 80.90654522467446
- type: dot_f1
value: 73.7394283267316
- type: dot_precision
value: 68.7196541403392
- type: dot_recall
value: 79.55035417308285
- type: euclidean_accuracy
value: 86.65541196103544
- type: euclidean_ap
value: 80.90654748736512
- type: euclidean_f1
value: 73.7394283267316
- type: euclidean_precision
value: 68.7196541403392
- type: euclidean_recall
value: 79.55035417308285
- type: manhattan_accuracy
value: 86.61272169829627
- type: manhattan_ap
value: 80.85801370403492
- type: manhattan_f1
value: 73.63878299647558
- type: manhattan_precision
value: 69.0916452962613
- type: manhattan_recall
value: 78.8266091777025
- type: max_accuracy
value: 86.65541196103544
- type: max_ap
value: 80.90654748736512
- type: max_f1
value: 73.7394283267316