metadata
tags:
- mteb
model-index:
- name: SFR-Embedding-Mistral
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 77.92537313432834
- type: ap
value: 40.86767661556651
- type: f1
value: 71.65758897929837
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 95.967
- type: ap
value: 94.46300829592593
- type: f1
value: 95.96507173189292
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 54.352000000000004
- type: f1
value: 53.636682615380174
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 43.314
- type: ndcg_at_2
value: 54.757
- type: ndcg_at_3
value: 58.84700000000001
- type: ndcg_at_5
value: 63.634
- type: ndcg_at_7
value: 65.741
- type: ndcg_at_10
value: 67.171
- type: ndcg_at_20
value: 68.585
- type: ndcg_at_30
value: 68.81
- type: ndcg_at_50
value: 68.932
- type: ndcg_at_70
value: 68.992
- type: ndcg_at_100
value: 69.014
- type: ndcg_at_200
value: 69.014
- type: ndcg_at_300
value: 69.014
- type: ndcg_at_500
value: 69.014
- type: ndcg_at_700
value: 69.014
- type: ndcg_at_1000
value: 69.014
- type: map_at_1
value: 43.314
- type: map_at_2
value: 52.383
- type: map_at_3
value: 55.108999999999995
- type: map_at_5
value: 57.772999999999996
- type: map_at_7
value: 58.718
- type: map_at_10
value: 59.256
- type: map_at_20
value: 59.668
- type: map_at_30
value: 59.709999999999994
- type: map_at_50
value: 59.727
- type: map_at_70
value: 59.733999999999995
- type: map_at_100
value: 59.73500000000001
- type: map_at_200
value: 59.73500000000001
- type: map_at_300
value: 59.73500000000001
- type: map_at_500
value: 59.73500000000001
- type: map_at_700
value: 59.73500000000001
- type: map_at_1000
value: 59.73500000000001
- type: recall_at_1
value: 43.314
- type: recall_at_2
value: 61.451
- type: recall_at_3
value: 69.63000000000001
- type: recall_at_5
value: 81.223
- type: recall_at_7
value: 87.33999999999999
- type: recall_at_10
value: 92.034
- type: recall_at_20
value: 97.44
- type: recall_at_30
value: 98.506
- type: recall_at_50
value: 99.14699999999999
- type: recall_at_70
value: 99.502
- type: recall_at_100
value: 99.644
- type: recall_at_200
value: 99.644
- type: recall_at_300
value: 99.644
- type: recall_at_500
value: 99.644
- type: recall_at_700
value: 99.644
- type: recall_at_1000
value: 99.644
- type: precision_at_1
value: 43.314
- type: precision_at_2
value: 30.725
- type: precision_at_3
value: 23.21
- type: precision_at_5
value: 16.245
- type: precision_at_7
value: 12.477
- type: precision_at_10
value: 9.203
- type: precision_at_20
value: 4.872
- type: precision_at_30
value: 3.2840000000000003
- type: precision_at_50
value: 1.983
- type: precision_at_70
value: 1.421
- type: precision_at_100
value: 0.996
- type: precision_at_200
value: 0.498
- type: precision_at_300
value: 0.332
- type: precision_at_500
value: 0.199
- type: precision_at_700
value: 0.14200000000000002
- type: precision_at_1000
value: 0.1
- type: mrr_at_1
value: 44.666
- type: mrr_at_2
value: 52.418
- type: mrr_at_3
value: 55.595000000000006
- type: mrr_at_5
value: 58.205
- type: mrr_at_7
value: 59.202999999999996
- type: mrr_at_10
value: 59.727
- type: mrr_at_20
value: 60.133
- type: mrr_at_30
value: 60.178
- type: mrr_at_50
value: 60.192
- type: mrr_at_70
value: 60.19799999999999
- type: mrr_at_100
value: 60.199999999999996
- type: mrr_at_200
value: 60.199999999999996
- type: mrr_at_300
value: 60.199999999999996
- type: mrr_at_500
value: 60.199999999999996
- type: mrr_at_700
value: 60.199999999999996
- type: mrr_at_1000
value: 60.199999999999996
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 52.07508593014336
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 47.381339333240675
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 67.58376647859171
- type: mrr
value: 80.56885635140483
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 88.40107280274783
- type: cos_sim_spearman
value: 86.07003345325681
- type: euclidean_pearson
value: 87.1726034325395
- type: euclidean_spearman
value: 86.07003345325681
- type: manhattan_pearson
value: 87.25660625029772
- type: manhattan_spearman
value: 86.3808839096893
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 88.81168831168831
- type: f1
value: 88.76514496560141
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 43.9382520874344
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 41.14351847240913
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 34.51166666666667
- type: ndcg_at_2
value: 38.51591666666667
- type: ndcg_at_3
value: 40.95083333333333
- type: ndcg_at_5
value: 43.580666666666666
- type: ndcg_at_7
value: 45.0625
- type: ndcg_at_10
value: 46.49083333333333
- type: ndcg_at_20
value: 48.731333333333325
- type: ndcg_at_30
value: 49.78666666666667
- type: ndcg_at_50
value: 50.84049999999999
- type: ndcg_at_70
value: 51.393750000000004
- type: ndcg_at_100
value: 51.883333333333326
- type: ndcg_at_200
value: 52.65225
- type: ndcg_at_300
value: 52.98241666666669
- type: ndcg_at_500
value: 53.28541666666668
- type: ndcg_at_700
value: 53.49241666666668
- type: ndcg_at_1000
value: 53.63758333333334
- type: map_at_1
value: 29.10075
- type: map_at_2
value: 34.636500000000005
- type: map_at_3
value: 36.92033333333333
- type: map_at_5
value: 38.81641666666666
- type: map_at_7
value: 39.635416666666664
- type: map_at_10
value: 40.294583333333335
- type: map_at_20
value: 41.07574999999999
- type: map_at_30
value: 41.333
- type: map_at_50
value: 41.529333333333334
- type: map_at_70
value: 41.606833333333334
- type: map_at_100
value: 41.66224999999999
- type: map_at_200
value: 41.72691666666666
- type: map_at_300
value: 41.746583333333334
- type: map_at_500
value: 41.75983333333333
- type: map_at_700
value: 41.76558333333333
- type: map_at_1000
value: 41.769000000000005
- type: recall_at_1
value: 29.10075
- type: recall_at_2
value: 39.07658333333333
- type: recall_at_3
value: 44.93591666666667
- type: recall_at_5
value: 51.66883333333333
- type: recall_at_7
value: 55.881000000000014
- type: recall_at_10
value: 60.34691666666667
- type: recall_at_20
value: 68.44016666666667
- type: recall_at_30
value: 72.90766666666667
- type: recall_at_50
value: 77.843
- type: recall_at_70
value: 80.70366666666668
- type: recall_at_100
value: 83.42866666666667
- type: recall_at_200
value: 88.06816666666668
- type: recall_at_300
value: 90.249
- type: recall_at_500
value: 92.37616666666668
- type: recall_at_700
value: 93.978
- type: recall_at_1000
value: 95.12791666666666
- type: precision_at_1
value: 34.51166666666667
- type: precision_at_2
value: 24.326333333333327
- type: precision_at_3
value: 19.099249999999998
- type: precision_at_5
value: 13.672666666666666
- type: precision_at_7
value: 10.772
- type: precision_at_10
value: 8.302166666666668
- type: precision_at_20
value: 4.8960833333333325
- type: precision_at_30
value: 3.551083333333333
- type: precision_at_50
value: 2.3386666666666662
- type: precision_at_70
value: 1.7605833333333334
- type: precision_at_100
value: 1.2965
- type: precision_at_200
value: 0.7106666666666668
- type: precision_at_300
value: 0.4955
- type: precision_at_500
value: 0.3106666666666667
- type: precision_at_700
value: 0.22791666666666668
- type: precision_at_1000
value: 0.1635833333333333
- type: mrr_at_1
value: 34.51166666666667
- type: mrr_at_2
value: 39.954249999999995
- type: mrr_at_3
value: 41.93741666666668
- type: mrr_at_5
value: 43.487166666666674
- type: mrr_at_7
value: 44.14983333333333
- type: mrr_at_10
value: 44.62766666666666
- type: mrr_at_20
value: 45.15291666666668
- type: mrr_at_30
value: 45.317
- type: mrr_at_50
value: 45.42875
- type: mrr_at_70
value: 45.46966666666667
- type: mrr_at_100
value: 45.49716666666667
- type: mrr_at_200
value: 45.525166666666664
- type: mrr_at_300
value: 45.53233333333335
- type: mrr_at_500
value: 45.5365
- type: mrr_at_700
value: 45.538583333333335
- type: mrr_at_1000
value: 45.539583333333326
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 35.179
- type: ndcg_at_2
value: 31.243
- type: ndcg_at_3
value: 30.562
- type: ndcg_at_5
value: 32.409
- type: ndcg_at_7
value: 34.525
- type: ndcg_at_10
value: 36.415
- type: ndcg_at_20
value: 39.443
- type: ndcg_at_30
value: 40.796
- type: ndcg_at_50
value: 42.16
- type: ndcg_at_70
value: 42.971
- type: ndcg_at_100
value: 43.691
- type: ndcg_at_200
value: 45.004
- type: ndcg_at_300
value: 45.527
- type: ndcg_at_500
value: 46.072
- type: ndcg_at_700
value: 46.387
- type: ndcg_at_1000
value: 46.663
- type: map_at_1
value: 15.692
- type: map_at_2
value: 20.116
- type: map_at_3
value: 22.6
- type: map_at_5
value: 24.701
- type: map_at_7
value: 25.934
- type: map_at_10
value: 26.843
- type: map_at_20
value: 27.975
- type: map_at_30
value: 28.372000000000003
- type: map_at_50
value: 28.671000000000003
- type: map_at_70
value: 28.803
- type: map_at_100
value: 28.895
- type: map_at_200
value: 29.011
- type: map_at_300
value: 29.042
- type: map_at_500
value: 29.065
- type: map_at_700
value: 29.075
- type: map_at_1000
value: 29.081000000000003
- type: recall_at_1
value: 15.692
- type: recall_at_2
value: 22.602
- type: recall_at_3
value: 27.814
- type: recall_at_5
value: 33.756
- type: recall_at_7
value: 38.073
- type: recall_at_10
value: 42.553000000000004
- type: recall_at_20
value: 51.121
- type: recall_at_30
value: 55.523999999999994
- type: recall_at_50
value: 60.586
- type: recall_at_70
value: 63.94
- type: recall_at_100
value: 67.134
- type: recall_at_200
value: 73.543
- type: recall_at_300
value: 76.372
- type: recall_at_500
value: 79.60199999999999
- type: recall_at_700
value: 81.536
- type: recall_at_1000
value: 83.37400000000001
- type: precision_at_1
value: 35.179
- type: precision_at_2
value: 27.199
- type: precision_at_3
value: 22.953000000000003
- type: precision_at_5
value: 17.224999999999998
- type: precision_at_7
value: 14.238999999999999
- type: precision_at_10
value: 11.303
- type: precision_at_20
value: 6.954000000000001
- type: precision_at_30
value: 5.116
- type: precision_at_50
value: 3.395
- type: precision_at_70
value: 2.579
- type: precision_at_100
value: 1.9109999999999998
- type: precision_at_200
value: 1.065
- type: precision_at_300
value: 0.743
- type: precision_at_500
value: 0.46699999999999997
- type: precision_at_700
value: 0.344
- type: precision_at_1000
value: 0.247
- type: mrr_at_1
value: 35.179
- type: mrr_at_2
value: 41.792
- type: mrr_at_3
value: 44.484
- type: mrr_at_5
value: 46.39
- type: mrr_at_7
value: 47.125
- type: mrr_at_10
value: 47.711999999999996
- type: mrr_at_20
value: 48.214
- type: mrr_at_30
value: 48.325
- type: mrr_at_50
value: 48.392
- type: mrr_at_70
value: 48.418
- type: mrr_at_100
value: 48.44
- type: mrr_at_200
value: 48.46
- type: mrr_at_300
value: 48.461999999999996
- type: mrr_at_500
value: 48.466
- type: mrr_at_700
value: 48.466
- type: mrr_at_1000
value: 48.467
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 62.375
- type: ndcg_at_2
value: 56.286
- type: ndcg_at_3
value: 53.665
- type: ndcg_at_5
value: 51.139
- type: ndcg_at_7
value: 49.873
- type: ndcg_at_10
value: 49.056
- type: ndcg_at_20
value: 48.783
- type: ndcg_at_30
value: 49.166
- type: ndcg_at_50
value: 51.141999999999996
- type: ndcg_at_70
value: 52.774
- type: ndcg_at_100
value: 54.403
- type: ndcg_at_200
value: 57.419
- type: ndcg_at_300
value: 58.778
- type: ndcg_at_500
value: 60.228
- type: ndcg_at_700
value: 61.07599999999999
- type: ndcg_at_1000
value: 61.846000000000004
- type: map_at_1
value: 10.359
- type: map_at_2
value: 14.446
- type: map_at_3
value: 16.689
- type: map_at_5
value: 20.096
- type: map_at_7
value: 22.247
- type: map_at_10
value: 24.468999999999998
- type: map_at_20
value: 28.938000000000002
- type: map_at_30
value: 31.134
- type: map_at_50
value: 33.403
- type: map_at_70
value: 34.486
- type: map_at_100
value: 35.337
- type: map_at_200
value: 36.364999999999995
- type: map_at_300
value: 36.735
- type: map_at_500
value: 37.057
- type: map_at_700
value: 37.225
- type: map_at_1000
value: 37.379
- type: recall_at_1
value: 10.359
- type: recall_at_2
value: 14.945
- type: recall_at_3
value: 17.694
- type: recall_at_5
value: 22.677
- type: recall_at_7
value: 26.131
- type: recall_at_10
value: 30.053
- type: recall_at_20
value: 39.518
- type: recall_at_30
value: 44.925
- type: recall_at_50
value: 52.154
- type: recall_at_70
value: 56.729
- type: recall_at_100
value: 61.18900000000001
- type: recall_at_200
value: 70.407
- type: recall_at_300
value: 74.412
- type: recall_at_500
value: 78.891
- type: recall_at_700
value: 81.74
- type: recall_at_1000
value: 84.253
- type: precision_at_1
value: 75
- type: precision_at_2
value: 64.125
- type: precision_at_3
value: 57.833
- type: precision_at_5
value: 50.24999999999999
- type: precision_at_7
value: 44.75
- type: precision_at_10
value: 39.75
- type: precision_at_20
value: 30.412
- type: precision_at_30
value: 25.141999999999996
- type: precision_at_50
value: 19.2
- type: precision_at_70
value: 15.729000000000001
- type: precision_at_100
value: 12.552
- type: precision_at_200
value: 7.866
- type: precision_at_300
value: 5.9270000000000005
- type: precision_at_500
value: 4.1129999999999995
- type: precision_at_700
value: 3.2460000000000004
- type: precision_at_1000
value: 2.5260000000000002
- type: mrr_at_1
value: 75
- type: mrr_at_2
value: 78.625
- type: mrr_at_3
value: 79.708
- type: mrr_at_5
value: 80.446
- type: mrr_at_7
value: 80.862
- type: mrr_at_10
value: 81.161
- type: mrr_at_20
value: 81.3
- type: mrr_at_30
value: 81.348
- type: mrr_at_50
value: 81.361
- type: mrr_at_70
value: 81.361
- type: mrr_at_100
value: 81.361
- type: mrr_at_200
value: 81.367
- type: mrr_at_300
value: 81.367
- type: mrr_at_500
value: 81.368
- type: mrr_at_700
value: 81.368
- type: mrr_at_1000
value: 81.368
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 50.239999999999995
- type: f1
value: 46.42361822342044
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 83.723
- type: ndcg_at_2
value: 86.777
- type: ndcg_at_3
value: 87.997
- type: ndcg_at_5
value: 88.864
- type: ndcg_at_7
value: 89.143
- type: ndcg_at_10
value: 89.349
- type: ndcg_at_20
value: 89.709
- type: ndcg_at_30
value: 89.82900000000001
- type: ndcg_at_50
value: 89.923
- type: ndcg_at_70
value: 89.982
- type: ndcg_at_100
value: 90.026
- type: ndcg_at_200
value: 90.10000000000001
- type: ndcg_at_300
value: 90.12599999999999
- type: ndcg_at_500
value: 90.17399999999999
- type: ndcg_at_700
value: 90.19
- type: ndcg_at_1000
value: 90.208
- type: map_at_1
value: 77.64999999999999
- type: map_at_2
value: 83.769
- type: map_at_3
value: 85.041
- type: map_at_5
value: 85.736
- type: map_at_7
value: 85.924
- type: map_at_10
value: 86.032
- type: map_at_20
value: 86.177
- type: map_at_30
value: 86.213
- type: map_at_50
value: 86.233
- type: map_at_70
value: 86.24300000000001
- type: map_at_100
value: 86.249
- type: map_at_200
value: 86.256
- type: map_at_300
value: 86.258
- type: map_at_500
value: 86.26
- type: map_at_700
value: 86.26
- type: map_at_1000
value: 86.261
- type: recall_at_1
value: 77.64999999999999
- type: recall_at_2
value: 88.53999999999999
- type: recall_at_3
value: 91.696
- type: recall_at_5
value: 93.916
- type: recall_at_7
value: 94.731
- type: recall_at_10
value: 95.318
- type: recall_at_20
value: 96.507
- type: recall_at_30
value: 96.956
- type: recall_at_50
value: 97.34899999999999
- type: recall_at_70
value: 97.61
- type: recall_at_100
value: 97.83
- type: recall_at_200
value: 98.223
- type: recall_at_300
value: 98.374
- type: recall_at_500
value: 98.67899999999999
- type: recall_at_700
value: 98.787
- type: recall_at_1000
value: 98.919
- type: precision_at_1
value: 83.723
- type: precision_at_2
value: 48.425000000000004
- type: precision_at_3
value: 33.638
- type: precision_at_5
value: 20.843
- type: precision_at_7
value: 15.079
- type: precision_at_10
value: 10.674999999999999
- type: precision_at_20
value: 5.457999999999999
- type: precision_at_30
value: 3.6740000000000004
- type: precision_at_50
value: 2.2239999999999998
- type: precision_at_70
value: 1.599
- type: precision_at_100
value: 1.125
- type: precision_at_200
value: 0.5680000000000001
- type: precision_at_300
value: 0.38
- type: precision_at_500
value: 0.22999999999999998
- type: precision_at_700
value: 0.165
- type: precision_at_1000
value: 0.116
- type: mrr_at_1
value: 83.723
- type: mrr_at_2
value: 88.794
- type: mrr_at_3
value: 89.679
- type: mrr_at_5
value: 90.049
- type: mrr_at_7
value: 90.129
- type: mrr_at_10
value: 90.167
- type: mrr_at_20
value: 90.208
- type: mrr_at_30
value: 90.214
- type: mrr_at_50
value: 90.217
- type: mrr_at_70
value: 90.218
- type: mrr_at_100
value: 90.21900000000001
- type: mrr_at_200
value: 90.21900000000001
- type: mrr_at_300
value: 90.21900000000001
- type: mrr_at_500
value: 90.21900000000001
- type: mrr_at_700
value: 90.21900000000001
- type: mrr_at_1000
value: 90.21900000000001
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 59.721999999999994
- type: ndcg_at_2
value: 56.85
- type: ndcg_at_3
value: 56.462999999999994
- type: ndcg_at_5
value: 57.75599999999999
- type: ndcg_at_7
value: 59.109
- type: ndcg_at_10
value: 60.402
- type: ndcg_at_20
value: 63.071999999999996
- type: ndcg_at_30
value: 64.302
- type: ndcg_at_50
value: 65.619
- type: ndcg_at_70
value: 66.161
- type: ndcg_at_100
value: 66.645
- type: ndcg_at_200
value: 67.353
- type: ndcg_at_300
value: 67.646
- type: ndcg_at_500
value: 67.852
- type: ndcg_at_700
value: 67.974
- type: ndcg_at_1000
value: 68.084
- type: map_at_1
value: 31.56
- type: map_at_2
value: 42.093
- type: map_at_3
value: 46.177
- type: map_at_5
value: 49.78
- type: map_at_7
value: 51.410999999999994
- type: map_at_10
value: 52.524
- type: map_at_20
value: 53.815000000000005
- type: map_at_30
value: 54.201
- type: map_at_50
value: 54.531
- type: map_at_70
value: 54.625
- type: map_at_100
value: 54.686
- type: map_at_200
value: 54.757999999999996
- type: map_at_300
value: 54.776
- type: map_at_500
value: 54.786
- type: map_at_700
value: 54.790000000000006
- type: map_at_1000
value: 54.793000000000006
- type: recall_at_1
value: 31.56
- type: recall_at_2
value: 44.858
- type: recall_at_3
value: 51.11
- type: recall_at_5
value: 58.394
- type: recall_at_7
value: 63.001
- type: recall_at_10
value: 66.81200000000001
- type: recall_at_20
value: 74.901
- type: recall_at_30
value: 79.218
- type: recall_at_50
value: 84.49
- type: recall_at_70
value: 87.003
- type: recall_at_100
value: 89.345
- type: recall_at_200
value: 93.173
- type: recall_at_300
value: 94.906
- type: recall_at_500
value: 96.223
- type: recall_at_700
value: 97.043
- type: recall_at_1000
value: 97.785
- type: precision_at_1
value: 59.721999999999994
- type: precision_at_2
value: 46.682
- type: precision_at_3
value: 37.602999999999994
- type: precision_at_5
value: 27.500000000000004
- type: precision_at_7
value: 21.847
- type: precision_at_10
value: 16.667
- type: precision_at_20
value: 9.545
- type: precision_at_30
value: 6.795
- type: precision_at_50
value: 4.38
- type: precision_at_70
value: 3.221
- type: precision_at_100
value: 2.319
- type: precision_at_200
value: 1.2149999999999999
- type: precision_at_300
value: 0.827
- type: precision_at_500
value: 0.504
- type: precision_at_700
value: 0.364
- type: precision_at_1000
value: 0.257
- type: mrr_at_1
value: 59.721999999999994
- type: mrr_at_2
value: 64.506
- type: mrr_at_3
value: 65.792
- type: mrr_at_5
value: 66.965
- type: mrr_at_7
value: 67.34700000000001
- type: mrr_at_10
value: 67.57
- type: mrr_at_20
value: 67.896
- type: mrr_at_30
value: 68.008
- type: mrr_at_50
value: 68.083
- type: mrr_at_70
value: 68.105
- type: mrr_at_100
value: 68.116
- type: mrr_at_200
value: 68.12700000000001
- type: mrr_at_300
value: 68.13
- type: mrr_at_500
value: 68.132
- type: mrr_at_700
value: 68.133
- type: mrr_at_1000
value: 68.133
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 81.796
- type: ndcg_at_2
value: 67.999
- type: ndcg_at_3
value: 72.15599999999999
- type: ndcg_at_5
value: 74.99900000000001
- type: ndcg_at_7
value: 76.179
- type: ndcg_at_10
value: 77.022
- type: ndcg_at_20
value: 78.173
- type: ndcg_at_30
value: 78.648
- type: ndcg_at_50
value: 79.104
- type: ndcg_at_70
value: 79.335
- type: ndcg_at_100
value: 79.56
- type: ndcg_at_200
value: 79.911
- type: ndcg_at_300
value: 80.045
- type: ndcg_at_500
value: 80.19500000000001
- type: ndcg_at_700
value: 80.281
- type: ndcg_at_1000
value: 80.35
- type: map_at_1
value: 40.898
- type: map_at_2
value: 62.016000000000005
- type: map_at_3
value: 66.121
- type: map_at_5
value: 68.471
- type: map_at_7
value: 69.261
- type: map_at_10
value: 69.738
- type: map_at_20
value: 70.208
- type: map_at_30
value: 70.343
- type: map_at_50
value: 70.43700000000001
- type: map_at_70
value: 70.47099999999999
- type: map_at_100
value: 70.498
- type: map_at_200
value: 70.526
- type: map_at_300
value: 70.533
- type: map_at_500
value: 70.538
- type: map_at_700
value: 70.541
- type: map_at_1000
value: 70.542
- type: recall_at_1
value: 40.898
- type: recall_at_2
value: 63.964
- type: recall_at_3
value: 70.743
- type: recall_at_5
value: 76.36699999999999
- type: recall_at_7
value: 79.142
- type: recall_at_10
value: 81.404
- type: recall_at_20
value: 85.111
- type: recall_at_30
value: 86.92800000000001
- type: recall_at_50
value: 88.899
- type: recall_at_70
value: 90.01400000000001
- type: recall_at_100
value: 91.19500000000001
- type: recall_at_200
value: 93.234
- type: recall_at_300
value: 94.105
- type: recall_at_500
value: 95.159
- type: recall_at_700
value: 95.8
- type: recall_at_1000
value: 96.34700000000001
- type: precision_at_1
value: 81.796
- type: precision_at_2
value: 63.964
- type: precision_at_3
value: 47.162
- type: precision_at_5
value: 30.547
- type: precision_at_7
value: 22.612
- type: precision_at_10
value: 16.281000000000002
- type: precision_at_20
value: 8.511000000000001
- type: precision_at_30
value: 5.795
- type: precision_at_50
value: 3.556
- type: precision_at_70
value: 2.572
- type: precision_at_100
value: 1.8239999999999998
- type: precision_at_200
value: 0.932
- type: precision_at_300
value: 0.627
- type: precision_at_500
value: 0.381
- type: precision_at_700
value: 0.27399999999999997
- type: precision_at_1000
value: 0.193
- type: mrr_at_1
value: 81.796
- type: mrr_at_2
value: 85.69200000000001
- type: mrr_at_3
value: 86.52
- type: mrr_at_5
value: 86.973
- type: mrr_at_7
value: 87.13300000000001
- type: mrr_at_10
value: 87.208
- type: mrr_at_20
value: 87.303
- type: mrr_at_30
value: 87.32799999999999
- type: mrr_at_50
value: 87.347
- type: mrr_at_70
value: 87.35199999999999
- type: mrr_at_100
value: 87.355
- type: mrr_at_200
value: 87.357
- type: mrr_at_300
value: 87.357
- type: mrr_at_500
value: 87.358
- type: mrr_at_700
value: 87.358
- type: mrr_at_1000
value: 87.358
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 94.79200000000002
- type: ap
value: 92.54484356773553
- type: f1
value: 94.78965313682525
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: ndcg_at_1
value: 24.398
- type: ndcg_at_2
value: 31.336000000000002
- type: ndcg_at_3
value: 35.266999999999996
- type: ndcg_at_5
value: 39.356
- type: ndcg_at_7
value: 41.562
- type: ndcg_at_10
value: 43.408
- type: ndcg_at_20
value: 46.107
- type: ndcg_at_30
value: 47.164
- type: ndcg_at_50
value: 48.126000000000005
- type: ndcg_at_70
value: 48.626999999999995
- type: ndcg_at_100
value: 49.043
- type: ndcg_at_200
value: 49.575
- type: ndcg_at_300
value: 49.794
- type: ndcg_at_500
value: 49.942
- type: ndcg_at_700
value: 50.014
- type: ndcg_at_1000
value: 50.077000000000005
- type: map_at_1
value: 23.723
- type: map_at_2
value: 29.593000000000004
- type: map_at_3
value: 32.273
- type: map_at_5
value: 34.587
- type: map_at_7
value: 35.589999999999996
- type: map_at_10
value: 36.296
- type: map_at_20
value: 37.059999999999995
- type: map_at_30
value: 37.265
- type: map_at_50
value: 37.402
- type: map_at_70
value: 37.454
- type: map_at_100
value: 37.486999999999995
- type: map_at_200
value: 37.516
- type: map_at_300
value: 37.524
- type: map_at_500
value: 37.528
- type: map_at_700
value: 37.529
- type: map_at_1000
value: 37.53
- type: recall_at_1
value: 23.723
- type: recall_at_2
value: 35.355
- type: recall_at_3
value: 43.22
- type: recall_at_5
value: 53.025
- type: recall_at_7
value: 59.327
- type: recall_at_10
value: 65.302
- type: recall_at_20
value: 75.765
- type: recall_at_30
value: 80.632
- type: recall_at_50
value: 85.63499999999999
- type: recall_at_70
value: 88.554
- type: recall_at_100
value: 91.16300000000001
- type: recall_at_200
value: 94.85
- type: recall_at_300
value: 96.532
- type: recall_at_500
value: 97.751
- type: recall_at_700
value: 98.383
- type: recall_at_1000
value: 98.97
- type: precision_at_1
value: 24.398
- type: precision_at_2
value: 18.274
- type: precision_at_3
value: 14.951999999999998
- type: precision_at_5
value: 11.052
- type: precision_at_7
value: 8.84
- type: precision_at_10
value: 6.8309999999999995
- type: precision_at_20
value: 3.978
- type: precision_at_30
value: 2.827
- type: precision_at_50
value: 1.807
- type: precision_at_70
value: 1.336
- type: precision_at_100
value: 0.964
- type: precision_at_200
value: 0.502
- type: precision_at_300
value: 0.34099999999999997
- type: precision_at_500
value: 0.208
- type: precision_at_700
value: 0.15
- type: precision_at_1000
value: 0.105
- type: mrr_at_1
value: 24.398
- type: mrr_at_2
value: 30.351
- type: mrr_at_3
value: 33.001000000000005
- type: mrr_at_5
value: 35.228
- type: mrr_at_7
value: 36.223
- type: mrr_at_10
value: 36.903999999999996
- type: mrr_at_20
value: 37.631
- type: mrr_at_30
value: 37.830000000000005
- type: mrr_at_50
value: 37.955
- type: mrr_at_70
value: 38.003
- type: mrr_at_100
value: 38.033
- type: mrr_at_200
value: 38.059
- type: mrr_at_300
value: 38.066
- type: mrr_at_500
value: 38.068999999999996
- type: mrr_at_700
value: 38.07
- type: mrr_at_1000
value: 38.07
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 96.35658914728683
- type: f1
value: 96.15039630903114
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 86.29730962152303
- type: f1
value: 71.12166316567485
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 79.98991257565568
- type: f1
value: 77.41680115095276
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 82.1990585070612
- type: f1
value: 82.23719179179362
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 40.03019554933584
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 38.999760551497815
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.72383151953079
- type: mrr
value: 33.93989699030721
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 51.858000000000004
- type: ndcg_at_2
value: 49.675999999999995
- type: ndcg_at_3
value: 47.519
- type: ndcg_at_5
value: 45.198
- type: ndcg_at_7
value: 43.504
- type: ndcg_at_10
value: 41.88
- type: ndcg_at_20
value: 39.122
- type: ndcg_at_30
value: 37.95
- type: ndcg_at_50
value: 37.602999999999994
- type: ndcg_at_70
value: 37.836
- type: ndcg_at_100
value: 38.493
- type: ndcg_at_200
value: 40.187
- type: ndcg_at_300
value: 41.524
- type: ndcg_at_500
value: 43.657000000000004
- type: ndcg_at_700
value: 45.234
- type: ndcg_at_1000
value: 47.047
- type: map_at_1
value: 6.392
- type: map_at_2
value: 10.113
- type: map_at_3
value: 11.543000000000001
- type: map_at_5
value: 13.729
- type: map_at_7
value: 14.985000000000001
- type: map_at_10
value: 16.217000000000002
- type: map_at_20
value: 18.106
- type: map_at_30
value: 18.878
- type: map_at_50
value: 19.822
- type: map_at_70
value: 20.352999999999998
- type: map_at_100
value: 20.827
- type: map_at_200
value: 21.512
- type: map_at_300
value: 21.826
- type: map_at_500
value: 22.155
- type: map_at_700
value: 22.349
- type: map_at_1000
value: 22.531000000000002
- type: recall_at_1
value: 6.392
- type: recall_at_2
value: 11.215
- type: recall_at_3
value: 13.231000000000002
- type: recall_at_5
value: 16.66
- type: recall_at_7
value: 18.802
- type: recall_at_10
value: 21.185000000000002
- type: recall_at_20
value: 25.35
- type: recall_at_30
value: 27.91
- type: recall_at_50
value: 32.845
- type: recall_at_70
value: 35.789
- type: recall_at_100
value: 39.247
- type: recall_at_200
value: 46.655
- type: recall_at_300
value: 51.43299999999999
- type: recall_at_500
value: 59.472
- type: recall_at_700
value: 64.742
- type: recall_at_1000
value: 70.97099999999999
- type: precision_at_1
value: 53.559999999999995
- type: precision_at_2
value: 48.762
- type: precision_at_3
value: 44.169000000000004
- type: precision_at_5
value: 39.071
- type: precision_at_7
value: 35.161
- type: precision_at_10
value: 31.238
- type: precision_at_20
value: 23.064999999999998
- type: precision_at_30
value: 18.844
- type: precision_at_50
value: 14.601
- type: precision_at_70
value: 12.088000000000001
- type: precision_at_100
value: 9.844999999999999
- type: precision_at_200
value: 6.358
- type: precision_at_300
value: 4.915
- type: precision_at_500
value: 3.531
- type: precision_at_700
value: 2.8649999999999998
- type: precision_at_1000
value: 2.289
- type: mrr_at_1
value: 54.17999999999999
- type: mrr_at_2
value: 59.288
- type: mrr_at_3
value: 60.836
- type: mrr_at_5
value: 62.275999999999996
- type: mrr_at_7
value: 62.688
- type: mrr_at_10
value: 62.865
- type: mrr_at_20
value: 63.11
- type: mrr_at_30
value: 63.193999999999996
- type: mrr_at_50
value: 63.258
- type: mrr_at_70
value: 63.278
- type: mrr_at_100
value: 63.297000000000004
- type: mrr_at_200
value: 63.315999999999995
- type: mrr_at_300
value: 63.318
- type: mrr_at_500
value: 63.32299999999999
- type: mrr_at_700
value: 63.324000000000005
- type: mrr_at_1000
value: 63.324999999999996
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 50.897999999999996
- type: ndcg_at_2
value: 59.126
- type: ndcg_at_3
value: 63.093999999999994
- type: ndcg_at_5
value: 67.197
- type: ndcg_at_7
value: 68.719
- type: ndcg_at_10
value: 69.915
- type: ndcg_at_20
value: 71.229
- type: ndcg_at_30
value: 71.667
- type: ndcg_at_50
value: 71.98
- type: ndcg_at_70
value: 72.127
- type: ndcg_at_100
value: 72.217
- type: ndcg_at_200
value: 72.319
- type: ndcg_at_300
value: 72.347
- type: ndcg_at_500
value: 72.37
- type: ndcg_at_700
value: 72.379
- type: ndcg_at_1000
value: 72.381
- type: map_at_1
value: 45.297
- type: map_at_2
value: 55.596000000000004
- type: map_at_3
value: 58.724
- type: map_at_5
value: 61.387
- type: map_at_7
value: 62.173
- type: map_at_10
value: 62.69
- type: map_at_20
value: 63.125
- type: map_at_30
value: 63.223
- type: map_at_50
value: 63.27700000000001
- type: map_at_70
value: 63.295
- type: map_at_100
value: 63.303
- type: map_at_200
value: 63.31
- type: map_at_300
value: 63.31099999999999
- type: map_at_500
value: 63.312000000000005
- type: map_at_700
value: 63.312000000000005
- type: map_at_1000
value: 63.312000000000005
- type: recall_at_1
value: 45.297
- type: recall_at_2
value: 63.866
- type: recall_at_3
value: 71.898
- type: recall_at_5
value: 81.16600000000001
- type: recall_at_7
value: 85.301
- type: recall_at_10
value: 88.94800000000001
- type: recall_at_20
value: 93.719
- type: recall_at_30
value: 95.628
- type: recall_at_50
value: 97.14699999999999
- type: recall_at_70
value: 97.955
- type: recall_at_100
value: 98.48599999999999
- type: recall_at_200
value: 99.157
- type: recall_at_300
value: 99.355
- type: recall_at_500
value: 99.53699999999999
- type: recall_at_700
value: 99.62299999999999
- type: recall_at_1000
value: 99.638
- type: precision_at_1
value: 50.897999999999996
- type: precision_at_2
value: 36.703
- type: precision_at_3
value: 27.926000000000002
- type: precision_at_5
value: 19.276
- type: precision_at_7
value: 14.533999999999999
- type: precision_at_10
value: 10.678
- type: precision_at_20
value: 5.663
- type: precision_at_30
value: 3.8600000000000003
- type: precision_at_50
value: 2.358
- type: precision_at_70
value: 1.7000000000000002
- type: precision_at_100
value: 1.198
- type: precision_at_200
value: 0.603
- type: precision_at_300
value: 0.40299999999999997
- type: precision_at_500
value: 0.242
- type: precision_at_700
value: 0.173
- type: precision_at_1000
value: 0.121
- type: mrr_at_1
value: 50.897999999999996
- type: mrr_at_2
value: 59.994
- type: mrr_at_3
value: 62.553000000000004
- type: mrr_at_5
value: 64.307
- type: mrr_at_7
value: 64.864
- type: mrr_at_10
value: 65.22200000000001
- type: mrr_at_20
value: 65.499
- type: mrr_at_30
value: 65.561
- type: mrr_at_50
value: 65.592
- type: mrr_at_70
value: 65.602
- type: mrr_at_100
value: 65.607
- type: mrr_at_200
value: 65.61099999999999
- type: mrr_at_300
value: 65.61200000000001
- type: mrr_at_500
value: 65.61200000000001
- type: mrr_at_700
value: 65.61200000000001
- type: mrr_at_1000
value: 65.61200000000001
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 82.96
- type: ndcg_at_2
value: 85.614
- type: ndcg_at_3
value: 87.19
- type: ndcg_at_5
value: 88.654
- type: ndcg_at_7
value: 89.287
- type: ndcg_at_10
value: 89.785
- type: ndcg_at_20
value: 90.384
- type: ndcg_at_30
value: 90.589
- type: ndcg_at_50
value: 90.738
- type: ndcg_at_70
value: 90.789
- type: ndcg_at_100
value: 90.824
- type: ndcg_at_200
value: 90.869
- type: ndcg_at_300
value: 90.881
- type: ndcg_at_500
value: 90.886
- type: ndcg_at_700
value: 90.889
- type: ndcg_at_1000
value: 90.889
- type: map_at_1
value: 72.152
- type: map_at_2
value: 80.818
- type: map_at_3
value: 83.462
- type: map_at_5
value: 85.286
- type: map_at_7
value: 85.921
- type: map_at_10
value: 86.334
- type: map_at_20
value: 86.737
- type: map_at_30
value: 86.847
- type: map_at_50
value: 86.911
- type: map_at_70
value: 86.932
- type: map_at_100
value: 86.943
- type: map_at_200
value: 86.953
- type: map_at_300
value: 86.955
- type: map_at_500
value: 86.956
- type: map_at_700
value: 86.956
- type: map_at_1000
value: 86.956
- type: recall_at_1
value: 72.152
- type: recall_at_2
value: 84.129
- type: recall_at_3
value: 88.87
- type: recall_at_5
value: 93.067
- type: recall_at_7
value: 94.882
- type: recall_at_10
value: 96.353
- type: recall_at_20
value: 98.26700000000001
- type: recall_at_30
value: 98.92999999999999
- type: recall_at_50
value: 99.441
- type: recall_at_70
value: 99.619
- type: recall_at_100
value: 99.748
- type: recall_at_200
value: 99.911
- type: recall_at_300
value: 99.956
- type: recall_at_500
value: 99.98
- type: recall_at_700
value: 99.991
- type: recall_at_1000
value: 99.996
- type: precision_at_1
value: 82.96
- type: precision_at_2
value: 52.175000000000004
- type: precision_at_3
value: 38.223
- type: precision_at_5
value: 25.056
- type: precision_at_7
value: 18.717
- type: precision_at_10
value: 13.614999999999998
- type: precision_at_20
value: 7.208
- type: precision_at_30
value: 4.928
- type: precision_at_50
value: 3.024
- type: precision_at_70
value: 2.183
- type: precision_at_100
value: 1.54
- type: precision_at_200
value: 0.779
- type: precision_at_300
value: 0.521
- type: precision_at_500
value: 0.313
- type: precision_at_700
value: 0.22399999999999998
- type: precision_at_1000
value: 0.157
- type: mrr_at_1
value: 82.96
- type: mrr_at_2
value: 87.005
- type: mrr_at_3
value: 88.07199999999999
- type: mrr_at_5
value: 88.634
- type: mrr_at_7
value: 88.793
- type: mrr_at_10
value: 88.87899999999999
- type: mrr_at_20
value: 88.94999999999999
- type: mrr_at_30
value: 88.96
- type: mrr_at_50
value: 88.965
- type: mrr_at_70
value: 88.966
- type: mrr_at_100
value: 88.967
- type: mrr_at_200
value: 88.967
- type: mrr_at_300
value: 88.967
- type: mrr_at_500
value: 88.967
- type: mrr_at_700
value: 88.967
- type: mrr_at_1000
value: 88.967
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 59.90388554491155
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 67.64232539036783
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 22.6
- type: ndcg_at_2
value: 20.355999999999998
- type: ndcg_at_3
value: 18.536
- type: ndcg_at_5
value: 16.523
- type: ndcg_at_7
value: 17.979
- type: ndcg_at_10
value: 19.908
- type: ndcg_at_20
value: 22.887
- type: ndcg_at_30
value: 24.43
- type: ndcg_at_50
value: 25.959
- type: ndcg_at_70
value: 26.989
- type: ndcg_at_100
value: 27.977
- type: ndcg_at_200
value: 29.831000000000003
- type: ndcg_at_300
value: 30.787
- type: ndcg_at_500
value: 31.974999999999998
- type: ndcg_at_700
value: 32.554
- type: ndcg_at_1000
value: 33.277
- type: map_at_1
value: 4.593
- type: map_at_2
value: 6.923
- type: map_at_3
value: 8.3
- type: map_at_5
value: 10.072000000000001
- type: map_at_7
value: 10.782
- type: map_at_10
value: 11.72
- type: map_at_20
value: 12.838
- type: map_at_30
value: 13.257
- type: map_at_50
value: 13.569
- type: map_at_70
value: 13.733
- type: map_at_100
value: 13.858999999999998
- type: map_at_200
value: 14.018
- type: map_at_300
value: 14.072999999999999
- type: map_at_500
value: 14.126
- type: map_at_700
value: 14.145
- type: map_at_1000
value: 14.161999999999999
- type: recall_at_1
value: 4.593
- type: recall_at_2
value: 7.997999999999999
- type: recall_at_3
value: 10.563
- type: recall_at_5
value: 14.907
- type: recall_at_7
value: 17.4
- type: recall_at_10
value: 21.18
- type: recall_at_20
value: 28.144999999999996
- type: recall_at_30
value: 32.462
- type: recall_at_50
value: 37.267
- type: recall_at_70
value: 40.875
- type: recall_at_100
value: 44.641999999999996
- type: recall_at_200
value: 52.573
- type: recall_at_300
value: 57.089999999999996
- type: recall_at_500
value: 63.14300000000001
- type: recall_at_700
value: 66.313
- type: recall_at_1000
value: 70.458
- type: precision_at_1
value: 22.6
- type: precision_at_2
value: 19.7
- type: precision_at_3
value: 17.333000000000002
- type: precision_at_5
value: 14.680000000000001
- type: precision_at_7
value: 12.243
- type: precision_at_10
value: 10.440000000000001
- type: precision_at_20
value: 6.944999999999999
- type: precision_at_30
value: 5.333
- type: precision_at_50
value: 3.678
- type: precision_at_70
value: 2.881
- type: precision_at_100
value: 2.2030000000000003
- type: precision_at_200
value: 1.295
- type: precision_at_300
value: 0.9369999999999999
- type: precision_at_500
value: 0.622
- type: precision_at_700
value: 0.466
- type: precision_at_1000
value: 0.347
- type: mrr_at_1
value: 22.6
- type: mrr_at_2
value: 27.900000000000002
- type: mrr_at_3
value: 30.067
- type: mrr_at_5
value: 32.207
- type: mrr_at_7
value: 33.004
- type: mrr_at_10
value: 33.596
- type: mrr_at_20
value: 34.268
- type: mrr_at_30
value: 34.492
- type: mrr_at_50
value: 34.628
- type: mrr_at_70
value: 34.681
- type: mrr_at_100
value: 34.717
- type: mrr_at_200
value: 34.757
- type: mrr_at_300
value: 34.768
- type: mrr_at_500
value: 34.772
- type: mrr_at_700
value: 34.774
- type: mrr_at_1000
value: 34.775
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 86.90122745229677
- type: cos_sim_spearman
value: 82.92294737327579
- type: euclidean_pearson
value: 84.08979655773187
- type: euclidean_spearman
value: 82.92294657285412
- type: manhattan_pearson
value: 84.09347480531832
- type: manhattan_spearman
value: 82.91564613948087
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 87.01218713698583
- type: cos_sim_spearman
value: 79.46865215168464
- type: euclidean_pearson
value: 83.22621889891909
- type: euclidean_spearman
value: 79.46853821709514
- type: manhattan_pearson
value: 83.69962580788805
- type: manhattan_spearman
value: 79.9561593356932
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 88.98438696342964
- type: cos_sim_spearman
value: 89.15419511870839
- type: euclidean_pearson
value: 88.49646141802894
- type: euclidean_spearman
value: 89.15419503946019
- type: manhattan_pearson
value: 88.6420585616327
- type: manhattan_spearman
value: 89.42648950757743
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 87.30772547759544
- type: cos_sim_spearman
value: 84.93199878424691
- type: euclidean_pearson
value: 86.16266630395455
- type: euclidean_spearman
value: 84.93198798543634
- type: manhattan_pearson
value: 86.14285723189803
- type: manhattan_spearman
value: 85.0361672522687
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 90.21342071197127
- type: cos_sim_spearman
value: 90.7407512744838
- type: euclidean_pearson
value: 90.1517933113061
- type: euclidean_spearman
value: 90.74075125431919
- type: manhattan_pearson
value: 90.17963034676193
- type: manhattan_spearman
value: 90.88999275865135
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 86.82518054100498
- type: cos_sim_spearman
value: 87.81570533154735
- type: euclidean_pearson
value: 86.91684561573618
- type: euclidean_spearman
value: 87.81570533154735
- type: manhattan_pearson
value: 86.98311935744032
- type: manhattan_spearman
value: 87.9594667151966
- 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: 92.09578436612053
- type: cos_sim_spearman
value: 92.01519349090438
- type: euclidean_pearson
value: 92.07113635890894
- type: euclidean_spearman
value: 92.01519349090438
- type: manhattan_pearson
value: 91.89343820765625
- type: manhattan_spearman
value: 91.7443476810177
- 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: 69.29997751464549
- type: cos_sim_spearman
value: 68.36425436812782
- type: euclidean_pearson
value: 69.81381677661783
- type: euclidean_spearman
value: 68.36425436812782
- type: manhattan_pearson
value: 69.92823397008026
- type: manhattan_spearman
value: 68.35770640039254
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 88.39126315452359
- type: cos_sim_spearman
value: 88.99708463265337
- type: euclidean_pearson
value: 88.60793820038607
- type: euclidean_spearman
value: 88.99708463265337
- type: manhattan_pearson
value: 88.69860633571047
- type: manhattan_spearman
value: 89.20094593888012
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 86.58028062818582
- type: mrr
value: 96.53586790841693
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 66.333
- type: ndcg_at_2
value: 70.655
- type: ndcg_at_3
value: 72.801
- type: ndcg_at_5
value: 75.793
- type: ndcg_at_7
value: 76.946
- type: ndcg_at_10
value: 77.66199999999999
- type: ndcg_at_20
value: 78.786
- type: ndcg_at_30
value: 79.066
- type: ndcg_at_50
value: 79.255
- type: ndcg_at_70
value: 79.423
- type: ndcg_at_100
value: 79.476
- type: ndcg_at_200
value: 79.65299999999999
- type: ndcg_at_300
value: 79.696
- type: ndcg_at_500
value: 79.73599999999999
- type: ndcg_at_700
value: 79.77199999999999
- type: ndcg_at_1000
value: 79.77199999999999
- type: map_at_1
value: 63.383
- type: map_at_2
value: 68.144
- type: map_at_3
value: 70.19800000000001
- type: map_at_5
value: 72.38
- type: map_at_7
value: 72.955
- type: map_at_10
value: 73.312
- type: map_at_20
value: 73.678
- type: map_at_30
value: 73.72800000000001
- type: map_at_50
value: 73.75500000000001
- type: map_at_70
value: 73.771
- type: map_at_100
value: 73.776
- type: map_at_200
value: 73.783
- type: map_at_300
value: 73.784
- type: map_at_500
value: 73.785
- type: map_at_700
value: 73.786
- type: map_at_1000
value: 73.786
- type: recall_at_1
value: 63.383
- type: recall_at_2
value: 72.283
- type: recall_at_3
value: 77.183
- type: recall_at_5
value: 84.56099999999999
- type: recall_at_7
value: 87.67200000000001
- type: recall_at_10
value: 89.822
- type: recall_at_20
value: 94
- type: recall_at_30
value: 95.333
- type: recall_at_50
value: 96.333
- type: recall_at_70
value: 97.333
- type: recall_at_100
value: 97.667
- type: recall_at_200
value: 99
- type: recall_at_300
value: 99.333
- type: recall_at_500
value: 99.667
- type: recall_at_700
value: 100
- type: recall_at_1000
value: 100
- type: precision_at_1
value: 66.333
- type: precision_at_2
value: 38.667
- type: precision_at_3
value: 28.111000000000004
- type: precision_at_5
value: 18.933
- type: precision_at_7
value: 14.094999999999999
- type: precision_at_10
value: 10.167
- type: precision_at_20
value: 5.35
- type: precision_at_30
value: 3.611
- type: precision_at_50
value: 2.1870000000000003
- type: precision_at_70
value: 1.576
- type: precision_at_100
value: 1.107
- type: precision_at_200
value: 0.5599999999999999
- type: precision_at_300
value: 0.374
- type: precision_at_500
value: 0.22499999999999998
- type: precision_at_700
value: 0.161
- type: precision_at_1000
value: 0.11299999999999999
- type: mrr_at_1
value: 66.333
- type: mrr_at_2
value: 70.833
- type: mrr_at_3
value: 72.167
- type: mrr_at_5
value: 73.6
- type: mrr_at_7
value: 74.084
- type: mrr_at_10
value: 74.283
- type: mrr_at_20
value: 74.54499999999999
- type: mrr_at_30
value: 74.59599999999999
- type: mrr_at_50
value: 74.622
- type: mrr_at_70
value: 74.639
- type: mrr_at_100
value: 74.643
- type: mrr_at_200
value: 74.65
- type: mrr_at_300
value: 74.652
- type: mrr_at_500
value: 74.653
- type: mrr_at_700
value: 74.653
- type: mrr_at_1000
value: 74.653
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.84554455445544
- type: cos_sim_ap
value: 96.31178339136798
- type: cos_sim_f1
value: 92.1921921921922
- type: cos_sim_precision
value: 92.28456913827655
- type: cos_sim_recall
value: 92.10000000000001
- type: dot_accuracy
value: 99.84554455445544
- type: dot_ap
value: 96.31178339136797
- type: dot_f1
value: 92.1921921921922
- type: dot_precision
value: 92.28456913827655
- type: dot_recall
value: 92.10000000000001
- type: euclidean_accuracy
value: 99.84554455445544
- type: euclidean_ap
value: 96.31178339136798
- type: euclidean_f1
value: 92.1921921921922
- type: euclidean_precision
value: 92.28456913827655
- type: euclidean_recall
value: 92.10000000000001
- type: manhattan_accuracy
value: 99.84752475247525
- type: manhattan_ap
value: 96.4591954606088
- type: manhattan_f1
value: 92.25352112676056
- type: manhattan_precision
value: 92.81376518218623
- type: manhattan_recall
value: 91.7
- type: max_accuracy
value: 99.84752475247525
- type: max_ap
value: 96.4591954606088
- type: max_f1
value: 92.25352112676056
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 74.24659759283294
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 46.77690051260451
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 55.68436757803185
- type: mrr
value: 56.82157711569475
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.652482405629843
- type: cos_sim_spearman
value: 31.16341822347735
- type: dot_pearson
value: 31.652479892699837
- type: dot_spearman
value: 31.16341822347735
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 92
- type: ndcg_at_2
value: 90.839
- type: ndcg_at_3
value: 90.642
- type: ndcg_at_5
value: 90.348
- type: ndcg_at_7
value: 89.015
- type: ndcg_at_10
value: 87.599
- type: ndcg_at_20
value: 84.434
- type: ndcg_at_30
value: 81.655
- type: ndcg_at_50
value: 77.278
- type: ndcg_at_70
value: 73.957
- type: ndcg_at_100
value: 69.56
- type: ndcg_at_200
value: 60.724000000000004
- type: ndcg_at_300
value: 57.245000000000005
- type: ndcg_at_500
value: 56.316
- type: ndcg_at_700
value: 58.399
- type: ndcg_at_1000
value: 62.21600000000001
- type: map_at_1
value: 0.247
- type: map_at_2
value: 0.488
- type: map_at_3
value: 0.7230000000000001
- type: map_at_5
value: 1.204
- type: map_at_7
value: 1.6500000000000001
- type: map_at_10
value: 2.292
- type: map_at_20
value: 4.274
- type: map_at_30
value: 6.027
- type: map_at_50
value: 9.083
- type: map_at_70
value: 11.751000000000001
- type: map_at_100
value: 14.912
- type: map_at_200
value: 22.213
- type: map_at_300
value: 26.667999999999996
- type: map_at_500
value: 31.556
- type: map_at_700
value: 34.221000000000004
- type: map_at_1000
value: 36.443999999999996
- type: recall_at_1
value: 0.247
- type: recall_at_2
value: 0.49899999999999994
- type: recall_at_3
value: 0.742
- type: recall_at_5
value: 1.247
- type: recall_at_7
value: 1.722
- type: recall_at_10
value: 2.405
- type: recall_at_20
value: 4.583
- type: recall_at_30
value: 6.587999999999999
- type: recall_at_50
value: 10.188
- type: recall_at_70
value: 13.496
- type: recall_at_100
value: 17.578
- type: recall_at_200
value: 28.158
- type: recall_at_300
value: 35.532000000000004
- type: recall_at_500
value: 45.31
- type: recall_at_700
value: 51.822
- type: recall_at_1000
value: 58.53
- type: precision_at_1
value: 96
- type: precision_at_2
value: 96
- type: precision_at_3
value: 95.333
- type: precision_at_5
value: 94.8
- type: precision_at_7
value: 93.429
- type: precision_at_10
value: 91.4
- type: precision_at_20
value: 87.7
- type: precision_at_30
value: 84.867
- type: precision_at_50
value: 80.24
- type: precision_at_70
value: 76.371
- type: precision_at_100
value: 71.08
- type: precision_at_200
value: 59.4
- type: precision_at_300
value: 51.459999999999994
- type: precision_at_500
value: 40.644000000000005
- type: precision_at_700
value: 33.889
- type: precision_at_1000
value: 27.250000000000004
- type: mrr_at_1
value: 96
- type: mrr_at_2
value: 98
- type: mrr_at_3
value: 98
- type: mrr_at_5
value: 98
- type: mrr_at_7
value: 98
- type: mrr_at_10
value: 98
- type: mrr_at_20
value: 98
- type: mrr_at_30
value: 98
- type: mrr_at_50
value: 98
- type: mrr_at_70
value: 98
- type: mrr_at_100
value: 98
- type: mrr_at_200
value: 98
- type: mrr_at_300
value: 98
- type: mrr_at_500
value: 98
- type: mrr_at_700
value: 98
- type: mrr_at_1000
value: 98
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: ndcg_at_1
value: 43.878
- type: ndcg_at_2
value: 37.956
- type: ndcg_at_3
value: 35.053
- type: ndcg_at_5
value: 32.59
- type: ndcg_at_7
value: 30.226
- type: ndcg_at_10
value: 29.005
- type: ndcg_at_20
value: 30.11
- type: ndcg_at_30
value: 32.019999999999996
- type: ndcg_at_50
value: 34.354
- type: ndcg_at_70
value: 36.665
- type: ndcg_at_100
value: 38.888
- type: ndcg_at_200
value: 43.435
- type: ndcg_at_300
value: 45.795
- type: ndcg_at_500
value: 48.699999999999996
- type: ndcg_at_700
value: 50.242
- type: ndcg_at_1000
value: 51.529
- type: map_at_1
value: 3.521
- type: map_at_2
value: 5.309
- type: map_at_3
value: 6.576
- type: map_at_5
value: 8.97
- type: map_at_7
value: 10.194
- type: map_at_10
value: 11.949
- type: map_at_20
value: 14.686
- type: map_at_30
value: 15.8
- type: map_at_50
value: 16.59
- type: map_at_70
value: 17.2
- type: map_at_100
value: 17.765
- type: map_at_200
value: 18.636
- type: map_at_300
value: 18.972
- type: map_at_500
value: 19.301
- type: map_at_700
value: 19.445
- type: map_at_1000
value: 19.546
- type: recall_at_1
value: 3.521
- type: recall_at_2
value: 5.848
- type: recall_at_3
value: 7.657
- type: recall_at_5
value: 11.368
- type: recall_at_7
value: 13.748
- type: recall_at_10
value: 18.061
- type: recall_at_20
value: 26.844
- type: recall_at_30
value: 31.186000000000003
- type: recall_at_50
value: 35.951
- type: recall_at_70
value: 40.961999999999996
- type: recall_at_100
value: 46.743
- type: recall_at_200
value: 58.483
- type: recall_at_300
value: 65.973
- type: recall_at_500
value: 75.233
- type: recall_at_700
value: 80.472
- type: recall_at_1000
value: 85.02
- type: precision_at_1
value: 46.939
- type: precision_at_2
value: 38.775999999999996
- type: precision_at_3
value: 34.694
- type: precision_at_5
value: 31.429000000000002
- type: precision_at_7
value: 27.697
- type: precision_at_10
value: 24.490000000000002
- type: precision_at_20
value: 18.776
- type: precision_at_30
value: 15.034
- type: precision_at_50
value: 10.857
- type: precision_at_70
value: 9.096
- type: precision_at_100
value: 7.51
- type: precision_at_200
value: 4.929
- type: precision_at_300
value: 3.7760000000000002
- type: precision_at_500
value: 2.6780000000000004
- type: precision_at_700
value: 2.085
- type: precision_at_1000
value: 1.5709999999999997
- type: mrr_at_1
value: 46.939
- type: mrr_at_2
value: 55.102
- type: mrr_at_3
value: 57.823
- type: mrr_at_5
value: 60.68
- type: mrr_at_7
value: 60.972
- type: mrr_at_10
value: 61.199000000000005
- type: mrr_at_20
value: 61.831
- type: mrr_at_30
value: 61.831
- type: mrr_at_50
value: 61.873
- type: mrr_at_70
value: 61.873
- type: mrr_at_100
value: 61.873
- type: mrr_at_200
value: 61.873
- type: mrr_at_300
value: 61.873
- type: mrr_at_500
value: 61.873
- type: mrr_at_700
value: 61.873
- type: mrr_at_1000
value: 61.873
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 69.3294
- type: ap
value: 14.561333393364736
- type: f1
value: 53.992309820496466
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 63.63893604980192
- type: f1
value: 63.92959380489434
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 56.270879258659775
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 88.71073493473207
- type: cos_sim_ap
value: 81.52392540284202
- type: cos_sim_f1
value: 74.71162377994676
- type: cos_sim_precision
value: 71.89558428885094
- type: cos_sim_recall
value: 77.75725593667546
- type: dot_accuracy
value: 88.71073493473207
- type: dot_ap
value: 81.52394754041109
- type: dot_f1
value: 74.71162377994676
- type: dot_precision
value: 71.89558428885094
- type: dot_recall
value: 77.75725593667546
- type: euclidean_accuracy
value: 88.71073493473207
- type: euclidean_ap
value: 81.52392035435321
- type: euclidean_f1
value: 74.71162377994676
- type: euclidean_precision
value: 71.89558428885094
- type: euclidean_recall
value: 77.75725593667546
- type: manhattan_accuracy
value: 88.47231328604637
- type: manhattan_ap
value: 81.22907439267321
- type: manhattan_f1
value: 74.3351571446749
- type: manhattan_precision
value: 71.78667977390022
- type: manhattan_recall
value: 77.0712401055409
- type: max_accuracy
value: 88.71073493473207
- type: max_ap
value: 81.52394754041109
- type: max_f1
value: 74.71162377994676
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 89.85136026700819
- type: cos_sim_ap
value: 87.7768002924216
- type: cos_sim_f1
value: 80.358908624794
- type: cos_sim_precision
value: 76.62918209122023
- type: cos_sim_recall
value: 84.47028025870034
- type: dot_accuracy
value: 89.85136026700819
- type: dot_ap
value: 87.77680027889778
- type: dot_f1
value: 80.358908624794
- type: dot_precision
value: 76.62918209122023
- type: dot_recall
value: 84.47028025870034
- type: euclidean_accuracy
value: 89.85136026700819
- type: euclidean_ap
value: 87.77680174697751
- type: euclidean_f1
value: 80.358908624794
- type: euclidean_precision
value: 76.62918209122023
- type: euclidean_recall
value: 84.47028025870034
- type: manhattan_accuracy
value: 89.86300306593705
- type: manhattan_ap
value: 87.78613271895861
- type: manhattan_f1
value: 80.31831016905645
- type: manhattan_precision
value: 76.68230516070304
- type: manhattan_recall
value: 84.3162919618109
- type: max_accuracy
value: 89.86300306593705
- type: max_ap
value: 87.78613271895861
- type: max_f1
value: 80.358908624794
language:
- en
license: cc-by-nc-4.0
Salesforce/SFR-Embedding-Mistral
SFR-Embedding by Salesforce Research.
The model is trained on top of E5-mistral-7b-instruct and Mistral-7B-v0.1. The model has 32 layers and the embedding size is 4096.
More technical details will be updated later.
SFR-Embedding Team
- Rui Meng
- Ye Liu
- Semih Yavuz
- Yingbo Zhou
- Caiming Xiong