metadata
tags:
- mteb
model-index:
- name: nomic_classification_nignore30
results:
- task:
type: Classification
dataset:
type: None
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 74.02985074626865
- type: ap
value: 36.54755879675939
- type: f1
value: 67.84911428462374
- task:
type: Classification
dataset:
type: None
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 60.98745000000001
- type: ap
value: 56.79972495487593
- type: f1
value: 60.79607311981127
- task:
type: Classification
dataset:
type: None
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 31.606000000000005
- type: f1
value: 31.20575804283948
- task:
type: Retrieval
dataset:
type: None
name: MTEB ArguAna
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 21.266
- type: map_at_10
value: 35.579
- type: map_at_100
value: 36.867
- type: map_at_1000
value: 36.887
- type: map_at_3
value: 31.105
- type: map_at_5
value: 33.512
- type: mrr_at_1
value: 21.764
- type: mrr_at_10
value: 35.768
- type: mrr_at_100
value: 37.049
- type: mrr_at_1000
value: 37.069
- type: mrr_at_3
value: 31.354
- type: mrr_at_5
value: 33.694
- type: ndcg_at_1
value: 21.266
- type: ndcg_at_10
value: 43.697
- type: ndcg_at_100
value: 49.444
- type: ndcg_at_1000
value: 49.918
- type: ndcg_at_3
value: 34.415
- type: ndcg_at_5
value: 38.751999999999995
- type: precision_at_1
value: 21.266
- type: precision_at_10
value: 6.97
- type: precision_at_100
value: 0.954
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 14.674999999999999
- type: precision_at_5
value: 10.91
- type: recall_at_1
value: 21.266
- type: recall_at_10
value: 69.70100000000001
- type: recall_at_100
value: 95.448
- type: recall_at_1000
value: 99.075
- type: recall_at_3
value: 44.025999999999996
- type: recall_at_5
value: 54.552
- task:
type: Clustering
dataset:
type: None
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 35.45486521675564
- task:
type: Clustering
dataset:
type: None
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 24.270159650279354
- task:
type: Reranking
dataset:
type: None
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 53.62399843388994
- type: mrr
value: 68.1675680429143
- task:
type: STS
dataset:
type: None
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 83.62266587849676
- type: cos_sim_spearman
value: 80.48918339823612
- type: euclidean_pearson
value: 82.46661732971302
- type: euclidean_spearman
value: 80.48918339823612
- type: manhattan_pearson
value: 81.55398066885756
- type: manhattan_spearman
value: 80.27411825686711
- task:
type: Classification
dataset:
type: None
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 73.07142857142857
- type: f1
value: 72.39723822054579
- task:
type: Clustering
dataset:
type: None
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 32.426645848653045
- task:
type: Clustering
dataset:
type: None
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 23.54829160604571
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: f46a197baaae43b4f621051089b82a364682dfeb
metrics:
- type: map_at_1
value: 24.001
- type: map_at_10
value: 31.195
- type: map_at_100
value: 32.342999999999996
- type: map_at_1000
value: 32.489000000000004
- type: map_at_3
value: 28.814
- type: map_at_5
value: 30.014000000000003
- type: mrr_at_1
value: 30.186
- type: mrr_at_10
value: 37.034
- type: mrr_at_100
value: 37.881
- type: mrr_at_1000
value: 37.946000000000005
- type: mrr_at_3
value: 35.241
- type: mrr_at_5
value: 36.120999999999995
- type: ndcg_at_1
value: 30.186
- type: ndcg_at_10
value: 35.972
- type: ndcg_at_100
value: 41.25
- type: ndcg_at_1000
value: 44.171
- type: ndcg_at_3
value: 32.674
- type: ndcg_at_5
value: 33.833
- type: precision_at_1
value: 30.186
- type: precision_at_10
value: 6.723999999999999
- type: precision_at_100
value: 1.157
- type: precision_at_1000
value: 0.172
- type: precision_at_3
value: 15.451
- type: precision_at_5
value: 10.815
- type: recall_at_1
value: 24.001
- type: recall_at_10
value: 44.057
- type: recall_at_100
value: 67.72500000000001
- type: recall_at_1000
value: 87.464
- type: recall_at_3
value: 33.817
- type: recall_at_5
value: 37.684
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
metrics:
- type: map_at_1
value: 16.766000000000002
- type: map_at_10
value: 23.07
- type: map_at_100
value: 24.062
- type: map_at_1000
value: 24.178
- type: map_at_3
value: 21.364
- type: map_at_5
value: 22.3
- type: mrr_at_1
value: 21.146
- type: mrr_at_10
value: 27.24
- type: mrr_at_100
value: 28.092
- type: mrr_at_1000
value: 28.163
- type: mrr_at_3
value: 25.605
- type: mrr_at_5
value: 26.567
- type: ndcg_at_1
value: 21.146
- type: ndcg_at_10
value: 27.031
- type: ndcg_at_100
value: 31.430999999999997
- type: ndcg_at_1000
value: 34.086
- type: ndcg_at_3
value: 24.136
- type: ndcg_at_5
value: 25.462
- type: precision_at_1
value: 21.146
- type: precision_at_10
value: 5.006
- type: precision_at_100
value: 0.901
- type: precision_at_1000
value: 0.13699999999999998
- type: precision_at_3
value: 11.762
- type: precision_at_5
value: 8.229000000000001
- type: recall_at_1
value: 16.766000000000002
- type: recall_at_10
value: 34.55
- type: recall_at_100
value: 53.542
- type: recall_at_1000
value: 71.66900000000001
- type: recall_at_3
value: 26.205000000000002
- type: recall_at_5
value: 29.854000000000003
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 26.579000000000004
- type: map_at_10
value: 35.482
- type: map_at_100
value: 36.564
- type: map_at_1000
value: 36.656
- type: map_at_3
value: 32.940999999999995
- type: map_at_5
value: 34.331
- type: mrr_at_1
value: 30.784
- type: mrr_at_10
value: 38.721
- type: mrr_at_100
value: 39.592
- type: mrr_at_1000
value: 39.653
- type: mrr_at_3
value: 36.468
- type: mrr_at_5
value: 37.688
- type: ndcg_at_1
value: 30.784
- type: ndcg_at_10
value: 40.351
- type: ndcg_at_100
value: 45.499
- type: ndcg_at_1000
value: 47.641
- type: ndcg_at_3
value: 35.605
- type: ndcg_at_5
value: 37.798
- type: precision_at_1
value: 30.784
- type: precision_at_10
value: 6.564
- type: precision_at_100
value: 1.004
- type: precision_at_1000
value: 0.126
- type: precision_at_3
value: 15.862000000000002
- type: precision_at_5
value: 11.008999999999999
- type: recall_at_1
value: 26.579000000000004
- type: recall_at_10
value: 51.978
- type: recall_at_100
value: 75.331
- type: recall_at_1000
value: 90.774
- type: recall_at_3
value: 39.149
- type: recall_at_5
value: 44.516
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 5003b3064772da1887988e05400cf3806fe491f2
metrics:
- type: map_at_1
value: 13.013
- type: map_at_10
value: 17.393
- type: map_at_100
value: 18.256
- type: map_at_1000
value: 18.364
- type: map_at_3
value: 15.812000000000001
- type: map_at_5
value: 16.601
- type: mrr_at_1
value: 14.237
- type: mrr_at_10
value: 18.706999999999997
- type: mrr_at_100
value: 19.553
- type: mrr_at_1000
value: 19.651
- type: mrr_at_3
value: 17.081
- type: mrr_at_5
value: 17.895
- type: ndcg_at_1
value: 14.237
- type: ndcg_at_10
value: 20.315
- type: ndcg_at_100
value: 24.914
- type: ndcg_at_1000
value: 28.244999999999997
- type: ndcg_at_3
value: 16.994
- type: ndcg_at_5
value: 18.396
- type: precision_at_1
value: 14.237
- type: precision_at_10
value: 3.198
- type: precision_at_100
value: 0.583
- type: precision_at_1000
value: 0.092
- type: precision_at_3
value: 7.0809999999999995
- type: precision_at_5
value: 4.994
- type: recall_at_1
value: 13.013
- type: recall_at_10
value: 28.297
- type: recall_at_100
value: 50.113
- type: recall_at_1000
value: 76.19500000000001
- type: recall_at_3
value: 19.062
- type: recall_at_5
value: 22.527
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
metrics:
- type: map_at_1
value: 6.783
- type: map_at_10
value: 10.439
- type: map_at_100
value: 11.26
- type: map_at_1000
value: 11.394
- type: map_at_3
value: 9.314
- type: map_at_5
value: 9.832
- type: mrr_at_1
value: 8.831
- type: mrr_at_10
value: 12.902
- type: mrr_at_100
value: 13.799
- type: mrr_at_1000
value: 13.901
- type: mrr_at_3
value: 11.692
- type: mrr_at_5
value: 12.200999999999999
- type: ndcg_at_1
value: 8.831
- type: ndcg_at_10
value: 12.973
- type: ndcg_at_100
value: 17.465
- type: ndcg_at_1000
value: 21.203
- type: ndcg_at_3
value: 10.778
- type: ndcg_at_5
value: 11.601
- type: precision_at_1
value: 8.831
- type: precision_at_10
value: 2.475
- type: precision_at_100
value: 0.553
- type: precision_at_1000
value: 0.101
- type: precision_at_3
value: 5.265000000000001
- type: precision_at_5
value: 3.781
- type: recall_at_1
value: 6.783
- type: recall_at_10
value: 18.386
- type: recall_at_100
value: 38.885999999999996
- type: recall_at_1000
value: 66.621
- type: recall_at_3
value: 12.235
- type: recall_at_5
value: 14.374999999999998
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
metrics:
- type: map_at_1
value: 17.946
- type: map_at_10
value: 24.188000000000002
- type: map_at_100
value: 25.402
- type: map_at_1000
value: 25.544
- type: map_at_3
value: 22.157
- type: map_at_5
value: 23.315
- type: mrr_at_1
value: 22.233
- type: mrr_at_10
value: 28.703
- type: mrr_at_100
value: 29.669
- type: mrr_at_1000
value: 29.748
- type: mrr_at_3
value: 26.676
- type: mrr_at_5
value: 27.894000000000002
- type: ndcg_at_1
value: 22.233
- type: ndcg_at_10
value: 28.483999999999998
- type: ndcg_at_100
value: 34.239999999999995
- type: ndcg_at_1000
value: 37.351
- type: ndcg_at_3
value: 25.018
- type: ndcg_at_5
value: 26.679000000000002
- type: precision_at_1
value: 22.233
- type: precision_at_10
value: 5.236
- type: precision_at_100
value: 0.962
- type: precision_at_1000
value: 0.14200000000000002
- type: precision_at_3
value: 11.806
- type: precision_at_5
value: 8.566
- type: recall_at_1
value: 17.946
- type: recall_at_10
value: 37.049
- type: recall_at_100
value: 62.473
- type: recall_at_1000
value: 83.829
- type: recall_at_3
value: 27.022000000000002
- type: recall_at_5
value: 31.435000000000002
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
metrics:
- type: map_at_1
value: 13.966000000000001
- type: map_at_10
value: 19.797
- type: map_at_100
value: 20.764
- type: map_at_1000
value: 20.913
- type: map_at_3
value: 17.688000000000002
- type: map_at_5
value: 18.796
- type: mrr_at_1
value: 17.122999999999998
- type: mrr_at_10
value: 23.277
- type: mrr_at_100
value: 24.095
- type: mrr_at_1000
value: 24.197
- type: mrr_at_3
value: 21.176000000000002
- type: mrr_at_5
value: 22.323
- type: ndcg_at_1
value: 17.122999999999998
- type: ndcg_at_10
value: 23.860999999999997
- type: ndcg_at_100
value: 28.669
- type: ndcg_at_1000
value: 32.375
- type: ndcg_at_3
value: 19.983999999999998
- type: ndcg_at_5
value: 21.647
- type: precision_at_1
value: 17.122999999999998
- type: precision_at_10
value: 4.623
- type: precision_at_100
value: 0.839
- type: precision_at_1000
value: 0.133
- type: precision_at_3
value: 9.551
- type: precision_at_5
value: 7.1
- type: recall_at_1
value: 13.966000000000001
- type: recall_at_10
value: 32.629999999999995
- type: recall_at_100
value: 53.842
- type: recall_at_1000
value: 80.583
- type: recall_at_3
value: 21.804000000000002
- type: recall_at_5
value: 26.101999999999997
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 14.974750000000004
- type: map_at_10
value: 20.34575
- type: map_at_100
value: 21.290416666666665
- type: map_at_1000
value: 21.41825
- type: map_at_3
value: 18.576500000000003
- type: map_at_5
value: 19.546166666666668
- type: mrr_at_1
value: 18.049249999999997
- type: mrr_at_10
value: 23.45216666666667
- type: mrr_at_100
value: 24.29241666666667
- type: mrr_at_1000
value: 24.37841666666667
- type: mrr_at_3
value: 21.728749999999998
- type: mrr_at_5
value: 22.680916666666665
- type: ndcg_at_1
value: 18.049249999999997
- type: ndcg_at_10
value: 23.90125
- type: ndcg_at_100
value: 28.57325
- type: ndcg_at_1000
value: 31.747583333333335
- type: ndcg_at_3
value: 20.71783333333333
- type: ndcg_at_5
value: 22.17008333333333
- type: precision_at_1
value: 18.049249999999997
- type: precision_at_10
value: 4.257666666666667
- type: precision_at_100
value: 0.7843333333333332
- type: precision_at_1000
value: 0.12375000000000003
- type: precision_at_3
value: 9.573750000000002
- type: precision_at_5
value: 6.871666666666666
- type: recall_at_1
value: 14.974750000000004
- type: recall_at_10
value: 31.535416666666666
- type: recall_at_100
value: 52.869583333333324
- type: recall_at_1000
value: 75.93208333333334
- type: recall_at_3
value: 22.561833333333333
- type: recall_at_5
value: 26.351583333333334
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
metrics:
- type: map_at_1
value: 11.584
- type: map_at_10
value: 15.47
- type: map_at_100
value: 16.276
- type: map_at_1000
value: 16.361
- type: map_at_3
value: 14.022000000000002
- type: map_at_5
value: 14.884
- type: mrr_at_1
value: 13.65
- type: mrr_at_10
value: 17.566000000000003
- type: mrr_at_100
value: 18.335
- type: mrr_at_1000
value: 18.411
- type: mrr_at_3
value: 16.053
- type: mrr_at_5
value: 16.843
- type: ndcg_at_1
value: 13.65
- type: ndcg_at_10
value: 18.208
- type: ndcg_at_100
value: 22.352
- type: ndcg_at_1000
value: 24.969
- type: ndcg_at_3
value: 15.459
- type: ndcg_at_5
value: 16.817
- type: precision_at_1
value: 13.65
- type: precision_at_10
value: 3.083
- type: precision_at_100
value: 0.561
- type: precision_at_1000
value: 0.086
- type: precision_at_3
value: 6.902
- type: precision_at_5
value: 4.968999999999999
- type: recall_at_1
value: 11.584
- type: recall_at_10
value: 24.629
- type: recall_at_100
value: 43.963
- type: recall_at_1000
value: 63.944
- type: recall_at_3
value: 17.155
- type: recall_at_5
value: 20.598
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 7.792000000000001
- type: map_at_10
value: 11.246
- type: map_at_100
value: 11.955
- type: map_at_1000
value: 12.076
- type: map_at_3
value: 10.176
- type: map_at_5
value: 10.802
- type: mrr_at_1
value: 9.67
- type: mrr_at_10
value: 13.591000000000001
- type: mrr_at_100
value: 14.285999999999998
- type: mrr_at_1000
value: 14.385
- type: mrr_at_3
value: 12.394
- type: mrr_at_5
value: 13.104
- type: ndcg_at_1
value: 9.67
- type: ndcg_at_10
value: 13.645
- type: ndcg_at_100
value: 17.562
- type: ndcg_at_1000
value: 21.101
- type: ndcg_at_3
value: 11.635
- type: ndcg_at_5
value: 12.638
- type: precision_at_1
value: 9.67
- type: precision_at_10
value: 2.54
- type: precision_at_100
value: 0.538
- type: precision_at_1000
value: 0.101
- type: precision_at_3
value: 5.632000000000001
- type: precision_at_5
value: 4.136
- type: recall_at_1
value: 7.792000000000001
- type: recall_at_10
value: 18.63
- type: recall_at_100
value: 37.047999999999995
- type: recall_at_1000
value: 63.391
- type: recall_at_3
value: 12.956999999999999
- type: recall_at_5
value: 15.581
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
metrics:
- type: map_at_1
value: 13.358999999999998
- type: map_at_10
value: 18.154999999999998
- type: map_at_100
value: 19.008
- type: map_at_1000
value: 19.125
- type: map_at_3
value: 16.645
- type: map_at_5
value: 17.544999999999998
- type: mrr_at_1
value: 15.672
- type: mrr_at_10
value: 20.973
- type: mrr_at_100
value: 21.782
- type: mrr_at_1000
value: 21.88
- type: mrr_at_3
value: 19.356
- type: mrr_at_5
value: 20.28
- type: ndcg_at_1
value: 15.672
- type: ndcg_at_10
value: 21.391
- type: ndcg_at_100
value: 25.71
- type: ndcg_at_1000
value: 29.016
- type: ndcg_at_3
value: 18.489
- type: ndcg_at_5
value: 19.916
- type: precision_at_1
value: 15.672
- type: precision_at_10
value: 3.573
- type: precision_at_100
value: 0.636
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 8.488999999999999
- type: precision_at_5
value: 5.989
- type: recall_at_1
value: 13.358999999999998
- type: recall_at_10
value: 28.695999999999998
- type: recall_at_100
value: 48.165
- type: recall_at_1000
value: 72.64500000000001
- type: recall_at_3
value: 20.573
- type: recall_at_5
value: 24.284
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 15.881
- type: map_at_10
value: 21.754
- type: map_at_100
value: 22.88
- type: map_at_1000
value: 23.087
- type: map_at_3
value: 19.827
- type: map_at_5
value: 20.964
- type: mrr_at_1
value: 19.564999999999998
- type: mrr_at_10
value: 25.246000000000002
- type: mrr_at_100
value: 26.163999999999998
- type: mrr_at_1000
value: 26.240999999999996
- type: mrr_at_3
value: 23.352999999999998
- type: mrr_at_5
value: 24.587999999999997
- type: ndcg_at_1
value: 19.564999999999998
- type: ndcg_at_10
value: 25.740000000000002
- type: ndcg_at_100
value: 30.977
- type: ndcg_at_1000
value: 34.486
- type: ndcg_at_3
value: 22.625
- type: ndcg_at_5
value: 24.294
- type: precision_at_1
value: 19.564999999999998
- type: precision_at_10
value: 5.0200000000000005
- type: precision_at_100
value: 1.146
- type: precision_at_1000
value: 0.201
- type: precision_at_3
value: 10.738
- type: precision_at_5
value: 8.103
- type: recall_at_1
value: 15.881
- type: recall_at_10
value: 32.918
- type: recall_at_100
value: 58.184000000000005
- type: recall_at_1000
value: 81.76299999999999
- type: recall_at_3
value: 23.992
- type: recall_at_5
value: 28.265
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 12.027000000000001
- type: map_at_10
value: 15.959999999999999
- type: map_at_100
value: 16.715
- type: map_at_1000
value: 16.832
- type: map_at_3
value: 14.158000000000001
- type: map_at_5
value: 15.17
- type: mrr_at_1
value: 13.494
- type: mrr_at_10
value: 17.466
- type: mrr_at_100
value: 18.261
- type: mrr_at_1000
value: 18.365000000000002
- type: mrr_at_3
value: 15.65
- type: mrr_at_5
value: 16.667
- type: ndcg_at_1
value: 13.494
- type: ndcg_at_10
value: 18.844
- type: ndcg_at_100
value: 22.81
- type: ndcg_at_1000
value: 26.327
- type: ndcg_at_3
value: 15.217
- type: ndcg_at_5
value: 16.96
- type: precision_at_1
value: 13.494
- type: precision_at_10
value: 3.05
- type: precision_at_100
value: 0.532
- type: precision_at_1000
value: 0.091
- type: precision_at_3
value: 6.346
- type: precision_at_5
value: 4.769
- type: recall_at_1
value: 12.027000000000001
- type: recall_at_10
value: 26.605
- type: recall_at_100
value: 45.163
- type: recall_at_1000
value: 72.307
- type: recall_at_3
value: 16.771
- type: recall_at_5
value: 20.998
- task:
type: Retrieval
dataset:
type: None
name: MTEB ClimateFEVER
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 6.479
- type: map_at_10
value: 11.559
- type: map_at_100
value: 12.936
- type: map_at_1000
value: 13.120000000000001
- type: map_at_3
value: 9.377
- type: map_at_5
value: 10.494
- type: mrr_at_1
value: 14.396999999999998
- type: mrr_at_10
value: 23.039
- type: mrr_at_100
value: 24.141000000000002
- type: mrr_at_1000
value: 24.215999999999998
- type: mrr_at_3
value: 19.814999999999998
- type: mrr_at_5
value: 21.656
- type: ndcg_at_1
value: 14.396999999999998
- type: ndcg_at_10
value: 17.258000000000003
- type: ndcg_at_100
value: 23.615
- type: ndcg_at_1000
value: 27.605
- type: ndcg_at_3
value: 13.114999999999998
- type: ndcg_at_5
value: 14.698
- type: precision_at_1
value: 14.396999999999998
- type: precision_at_10
value: 5.713
- type: precision_at_100
value: 1.25
- type: precision_at_1000
value: 0.198
- type: precision_at_3
value: 9.924
- type: precision_at_5
value: 8.104
- type: recall_at_1
value: 6.479
- type: recall_at_10
value: 22.088
- type: recall_at_100
value: 44.681
- type: recall_at_1000
value: 67.869
- type: recall_at_3
value: 12.203
- type: recall_at_5
value: 16.275000000000002
- task:
type: Retrieval
dataset:
type: None
name: MTEB DBPedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 4.618
- type: map_at_10
value: 10.217
- type: map_at_100
value: 14.038999999999998
- type: map_at_1000
value: 15.03
- type: map_at_3
value: 7.523000000000001
- type: map_at_5
value: 8.688
- type: mrr_at_1
value: 41.75
- type: mrr_at_10
value: 51.991
- type: mrr_at_100
value: 52.711
- type: mrr_at_1000
value: 52.746
- type: mrr_at_3
value: 49.5
- type: mrr_at_5
value: 50.961999999999996
- type: ndcg_at_1
value: 30.875000000000004
- type: ndcg_at_10
value: 24.709999999999997
- type: ndcg_at_100
value: 27.584999999999997
- type: ndcg_at_1000
value: 34.508
- type: ndcg_at_3
value: 27.88
- type: ndcg_at_5
value: 26.168999999999997
- type: precision_at_1
value: 41.75
- type: precision_at_10
value: 21.45
- type: precision_at_100
value: 6.795
- type: precision_at_1000
value: 1.43
- type: precision_at_3
value: 33.083
- type: precision_at_5
value: 27.750000000000004
- type: recall_at_1
value: 4.618
- type: recall_at_10
value: 14.898
- type: recall_at_100
value: 33.027
- type: recall_at_1000
value: 57.036
- type: recall_at_3
value: 8.995000000000001
- type: recall_at_5
value: 11.23
- task:
type: Classification
dataset:
type: None
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 43.19499999999999
- type: f1
value: 40.60048839070268
- task:
type: Retrieval
dataset:
type: None
name: MTEB FEVER
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 17.11
- type: map_at_10
value: 25.478
- type: map_at_100
value: 26.436
- type: map_at_1000
value: 26.51
- type: map_at_3
value: 22.996
- type: map_at_5
value: 24.329
- type: mrr_at_1
value: 18.317
- type: mrr_at_10
value: 27.090999999999998
- type: mrr_at_100
value: 28.037
- type: mrr_at_1000
value: 28.102
- type: mrr_at_3
value: 24.532
- type: mrr_at_5
value: 25.918999999999997
- type: ndcg_at_1
value: 18.317
- type: ndcg_at_10
value: 30.448999999999998
- type: ndcg_at_100
value: 35.302
- type: ndcg_at_1000
value: 37.325
- type: ndcg_at_3
value: 25.326999999999998
- type: ndcg_at_5
value: 27.716
- type: precision_at_1
value: 18.317
- type: precision_at_10
value: 4.8469999999999995
- type: precision_at_100
value: 0.747
- type: precision_at_1000
value: 0.094
- type: precision_at_3
value: 10.975999999999999
- type: precision_at_5
value: 7.846
- type: recall_at_1
value: 17.11
- type: recall_at_10
value: 44.466
- type: recall_at_100
value: 67.06299999999999
- type: recall_at_1000
value: 82.64200000000001
- type: recall_at_3
value: 30.509999999999998
- type: recall_at_5
value: 36.27
- task:
type: Retrieval
dataset:
type: None
name: MTEB FiQA2018
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 7.446999999999999
- type: map_at_10
value: 12.188
- type: map_at_100
value: 13.241
- type: map_at_1000
value: 13.450000000000001
- type: map_at_3
value: 10.184999999999999
- type: map_at_5
value: 11.266
- type: mrr_at_1
value: 15.123000000000001
- type: mrr_at_10
value: 21.397
- type: mrr_at_100
value: 22.303
- type: mrr_at_1000
value: 22.398
- type: mrr_at_3
value: 19.187
- type: mrr_at_5
value: 20.383000000000003
- type: ndcg_at_1
value: 15.123000000000001
- type: ndcg_at_10
value: 16.957
- type: ndcg_at_100
value: 22.147
- type: ndcg_at_1000
value: 26.759
- type: ndcg_at_3
value: 14.091000000000001
- type: ndcg_at_5
value: 15.135000000000002
- type: precision_at_1
value: 15.123000000000001
- type: precision_at_10
value: 4.938
- type: precision_at_100
value: 1.019
- type: precision_at_1000
value: 0.18
- type: precision_at_3
value: 9.568
- type: precision_at_5
value: 7.438000000000001
- type: recall_at_1
value: 7.446999999999999
- type: recall_at_10
value: 22.094
- type: recall_at_100
value: 42.397
- type: recall_at_1000
value: 71.15700000000001
- type: recall_at_3
value: 12.879
- type: recall_at_5
value: 16.49
- task:
type: Retrieval
dataset:
type: None
name: MTEB HotpotQA
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 18.285
- type: map_at_10
value: 25.703
- type: map_at_100
value: 26.634
- type: map_at_1000
value: 26.741999999999997
- type: map_at_3
value: 23.642
- type: map_at_5
value: 24.826
- type: mrr_at_1
value: 36.57
- type: mrr_at_10
value: 43.772
- type: mrr_at_100
value: 44.51
- type: mrr_at_1000
value: 44.561
- type: mrr_at_3
value: 41.787
- type: mrr_at_5
value: 42.964
- type: ndcg_at_1
value: 36.57
- type: ndcg_at_10
value: 32.763999999999996
- type: ndcg_at_100
value: 37.077
- type: ndcg_at_1000
value: 39.666000000000004
- type: ndcg_at_3
value: 28.906
- type: ndcg_at_5
value: 30.86
- type: precision_at_1
value: 36.57
- type: precision_at_10
value: 7.202
- type: precision_at_100
value: 1.065
- type: precision_at_1000
value: 0.14100000000000001
- type: precision_at_3
value: 18.231
- type: precision_at_5
value: 12.483
- type: recall_at_1
value: 18.285
- type: recall_at_10
value: 36.009
- type: recall_at_100
value: 53.27499999999999
- type: recall_at_1000
value: 70.635
- type: recall_at_3
value: 27.345999999999997
- type: recall_at_5
value: 31.208999999999996
- task:
type: Classification
dataset:
type: None
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 61.361999999999995
- type: ap
value: 57.09674595597791
- type: f1
value: 60.94720401382382
- task:
type: Retrieval
dataset:
type: None
name: MTEB MSMARCO
config: default
split: dev
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 6.686
- type: map_at_10
value: 11.454
- type: map_at_100
value: 12.342
- type: map_at_1000
value: 12.447
- type: map_at_3
value: 9.722
- type: map_at_5
value: 10.632
- type: mrr_at_1
value: 6.891
- type: mrr_at_10
value: 11.768
- type: mrr_at_100
value: 12.651000000000002
- type: mrr_at_1000
value: 12.753
- type: mrr_at_3
value: 10.001999999999999
- type: mrr_at_5
value: 10.918999999999999
- type: ndcg_at_1
value: 6.848
- type: ndcg_at_10
value: 14.466000000000001
- type: ndcg_at_100
value: 19.301
- type: ndcg_at_1000
value: 22.458
- type: ndcg_at_3
value: 10.836
- type: ndcg_at_5
value: 12.475
- type: precision_at_1
value: 6.848
- type: precision_at_10
value: 2.48
- type: precision_at_100
value: 0.49899999999999994
- type: precision_at_1000
value: 0.077
- type: precision_at_3
value: 4.766
- type: precision_at_5
value: 3.682
- type: recall_at_1
value: 6.686
- type: recall_at_10
value: 23.82
- type: recall_at_100
value: 47.349999999999994
- type: recall_at_1000
value: 72.66
- type: recall_at_3
value: 13.811000000000002
- type: recall_at_5
value: 17.76
- task:
type: Classification
dataset:
type: None
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 87.67213862289103
- type: f1
value: 86.45841301738238
- task:
type: Classification
dataset:
type: None
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 56.82170542635659
- type: f1
value: 39.12615117855274
- task:
type: Classification
dataset:
type: None
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 60.18829858776058
- type: f1
value: 58.617914607265064
- task:
type: Classification
dataset:
type: None
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 66.45595158036315
- type: f1
value: 64.9778374481982
- task:
type: Clustering
dataset:
type: None
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 29.531989286141012
- task:
type: Clustering
dataset:
type: None
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 26.070324322784792
- task:
type: Reranking
dataset:
type: None
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 29.516858081965257
- type: mrr
value: 30.51047930520146
- task:
type: Retrieval
dataset:
type: None
name: MTEB NFCorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 4.131
- type: map_at_10
value: 8.826
- type: map_at_100
value: 11.094999999999999
- type: map_at_1000
value: 12.484
- type: map_at_3
value: 6.723
- type: map_at_5
value: 7.683
- type: mrr_at_1
value: 34.985
- type: mrr_at_10
value: 44.921
- type: mrr_at_100
value: 45.62
- type: mrr_at_1000
value: 45.676
- type: mrr_at_3
value: 42.931000000000004
- type: mrr_at_5
value: 44.385999999999996
- type: ndcg_at_1
value: 32.507999999999996
- type: ndcg_at_10
value: 26.773000000000003
- type: ndcg_at_100
value: 24.751
- type: ndcg_at_1000
value: 34.19
- type: ndcg_at_3
value: 31.213
- type: ndcg_at_5
value: 29.249000000000002
- type: precision_at_1
value: 34.985
- type: precision_at_10
value: 20.247999999999998
- type: precision_at_100
value: 6.907000000000001
- type: precision_at_1000
value: 2.031
- type: precision_at_3
value: 30.341
- type: precision_at_5
value: 25.759
- type: recall_at_1
value: 4.131
- type: recall_at_10
value: 12.465
- type: recall_at_100
value: 25.776
- type: recall_at_1000
value: 59.876
- type: recall_at_3
value: 7.968
- type: recall_at_5
value: 9.968
- task:
type: Retrieval
dataset:
type: None
name: MTEB NQ
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 9.277000000000001
- type: map_at_10
value: 15.709999999999999
- type: map_at_100
value: 16.980999999999998
- type: map_at_1000
value: 17.074
- type: map_at_3
value: 13.157
- type: map_at_5
value: 14.571000000000002
- type: mrr_at_1
value: 10.574
- type: mrr_at_10
value: 17.344
- type: mrr_at_100
value: 18.506
- type: mrr_at_1000
value: 18.584999999999997
- type: mrr_at_3
value: 14.677000000000001
- type: mrr_at_5
value: 16.213
- type: ndcg_at_1
value: 10.574
- type: ndcg_at_10
value: 20.044
- type: ndcg_at_100
value: 26.447
- type: ndcg_at_1000
value: 29.084
- type: ndcg_at_3
value: 14.787
- type: ndcg_at_5
value: 17.362
- type: precision_at_1
value: 10.574
- type: precision_at_10
value: 3.7600000000000002
- type: precision_at_100
value: 0.738
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 6.933
- type: precision_at_5
value: 5.608
- type: recall_at_1
value: 9.277000000000001
- type: recall_at_10
value: 31.948
- type: recall_at_100
value: 61.708
- type: recall_at_1000
value: 82.07799999999999
- type: recall_at_3
value: 18.045
- type: recall_at_5
value: 24.038999999999998
- task:
type: Retrieval
dataset:
type: None
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 64.268
- type: map_at_10
value: 77.19500000000001
- type: map_at_100
value: 77.95299999999999
- type: map_at_1000
value: 77.986
- type: map_at_3
value: 74.30499999999999
- type: map_at_5
value: 76.054
- type: mrr_at_1
value: 74.09
- type: mrr_at_10
value: 81.384
- type: mrr_at_100
value: 81.592
- type: mrr_at_1000
value: 81.597
- type: mrr_at_3
value: 80.00500000000001
- type: mrr_at_5
value: 80.876
- type: ndcg_at_1
value: 74.16
- type: ndcg_at_10
value: 81.813
- type: ndcg_at_100
value: 83.787
- type: ndcg_at_1000
value: 84.11800000000001
- type: ndcg_at_3
value: 78.389
- type: ndcg_at_5
value: 80.123
- type: precision_at_1
value: 74.16
- type: precision_at_10
value: 12.35
- type: precision_at_100
value: 1.466
- type: precision_at_1000
value: 0.155
- type: precision_at_3
value: 34.067
- type: precision_at_5
value: 22.442
- type: recall_at_1
value: 64.268
- type: recall_at_10
value: 90.67
- type: recall_at_100
value: 97.935
- type: recall_at_1000
value: 99.703
- type: recall_at_3
value: 80.752
- type: recall_at_5
value: 85.63300000000001
- task:
type: Clustering
dataset:
type: None
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 39.191626251430044
- task:
type: Clustering
dataset:
type: None
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 47.00784930616429
- task:
type: Retrieval
dataset:
type: None
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.948
- type: map_at_10
value: 7.126
- type: map_at_100
value: 8.462
- type: map_at_1000
value: 8.713
- type: map_at_3
value: 5.143
- type: map_at_5
value: 6.117
- type: mrr_at_1
value: 14.499999999999998
- type: mrr_at_10
value: 22.455
- type: mrr_at_100
value: 23.666
- type: mrr_at_1000
value: 23.745
- type: mrr_at_3
value: 19.417
- type: mrr_at_5
value: 21.117
- type: ndcg_at_1
value: 14.499999999999998
- type: ndcg_at_10
value: 12.666
- type: ndcg_at_100
value: 18.993
- type: ndcg_at_1000
value: 24.09
- type: ndcg_at_3
value: 11.655999999999999
- type: ndcg_at_5
value: 10.342
- type: precision_at_1
value: 14.499999999999998
- type: precision_at_10
value: 6.65
- type: precision_at_100
value: 1.598
- type: precision_at_1000
value: 0.28300000000000003
- type: precision_at_3
value: 10.8
- type: precision_at_5
value: 9.1
- type: recall_at_1
value: 2.948
- type: recall_at_10
value: 13.492
- type: recall_at_100
value: 32.448
- type: recall_at_1000
value: 57.553
- type: recall_at_3
value: 6.578
- type: recall_at_5
value: 9.242
- task:
type: STS
dataset:
type: None
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 75.38146213095916
- type: cos_sim_spearman
value: 65.36914729991646
- type: euclidean_pearson
value: 70.34893420889419
- type: euclidean_spearman
value: 65.36925972117625
- type: manhattan_pearson
value: 68.16816720045782
- type: manhattan_spearman
value: 64.0884396246228
- task:
type: STS
dataset:
type: None
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 74.45813185900207
- type: cos_sim_spearman
value: 68.03206487736479
- type: euclidean_pearson
value: 70.55331228911669
- type: euclidean_spearman
value: 68.03330456319067
- type: manhattan_pearson
value: 68.32513309931606
- type: manhattan_spearman
value: 66.90519361570585
- task:
type: STS
dataset:
type: None
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 77.32203252223916
- type: cos_sim_spearman
value: 78.44952447167366
- type: euclidean_pearson
value: 78.18870184193474
- type: euclidean_spearman
value: 78.44956228059971
- type: manhattan_pearson
value: 77.82417744157945
- type: manhattan_spearman
value: 78.17317129725184
- task:
type: STS
dataset:
type: None
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 77.98515479114604
- type: cos_sim_spearman
value: 74.70914230860409
- type: euclidean_pearson
value: 76.81874418213698
- type: euclidean_spearman
value: 74.70913261737951
- type: manhattan_pearson
value: 75.54410520012546
- type: manhattan_spearman
value: 73.74596322038998
- task:
type: STS
dataset:
type: None
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 81.34912352314105
- type: cos_sim_spearman
value: 82.13479378308254
- type: euclidean_pearson
value: 82.07291865315551
- type: euclidean_spearman
value: 82.13479226815167
- type: manhattan_pearson
value: 81.51909627091456
- type: manhattan_spearman
value: 81.70075499671213
- task:
type: STS
dataset:
type: None
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 76.1116492955691
- type: cos_sim_spearman
value: 77.19800116078945
- type: euclidean_pearson
value: 76.8231316467101
- type: euclidean_spearman
value: 77.19883015620502
- type: manhattan_pearson
value: 77.10588536013977
- type: manhattan_spearman
value: 77.50215416532438
- task:
type: STS
dataset:
type: None
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 84.10770264372314
- type: cos_sim_spearman
value: 84.97403648808209
- type: euclidean_pearson
value: 84.41825024902698
- type: euclidean_spearman
value: 84.97491009412074
- type: manhattan_pearson
value: 84.16827578787243
- type: manhattan_spearman
value: 84.92739867128569
- task:
type: STS
dataset:
type: None
name: MTEB STS22 (en)
config: en
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson
value: 62.91807215204278
- type: cos_sim_spearman
value: 59.61282196137074
- type: euclidean_pearson
value: 62.702286829442436
- type: euclidean_spearman
value: 59.61282196137074
- type: manhattan_pearson
value: 62.26491120673072
- type: manhattan_spearman
value: 59.7161013914999
- task:
type: STS
dataset:
type: None
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 78.43114398442724
- type: cos_sim_spearman
value: 77.35423527756463
- type: euclidean_pearson
value: 78.2269102978861
- type: euclidean_spearman
value: 77.35428366374488
- type: manhattan_pearson
value: 77.26973789544932
- type: manhattan_spearman
value: 76.58307796792111
- task:
type: Reranking
dataset:
type: None
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 72.61932743075317
- type: mrr
value: 91.38920810489437
- task:
type: Retrieval
dataset:
type: None
name: MTEB SciFact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 36.861
- type: map_at_10
value: 45.93
- type: map_at_100
value: 46.861000000000004
- type: map_at_1000
value: 46.924
- type: map_at_3
value: 43.283
- type: map_at_5
value: 44.675
- type: mrr_at_1
value: 39.333
- type: mrr_at_10
value: 47.906
- type: mrr_at_100
value: 48.665000000000006
- type: mrr_at_1000
value: 48.722
- type: mrr_at_3
value: 45.611000000000004
- type: mrr_at_5
value: 46.778
- type: ndcg_at_1
value: 39.333
- type: ndcg_at_10
value: 50.970000000000006
- type: ndcg_at_100
value: 55.491
- type: ndcg_at_1000
value: 57.099
- type: ndcg_at_3
value: 45.837
- type: ndcg_at_5
value: 48.081
- type: precision_at_1
value: 39.333
- type: precision_at_10
value: 7.199999999999999
- type: precision_at_100
value: 0.9730000000000001
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 18.333
- type: precision_at_5
value: 12.4
- type: recall_at_1
value: 36.861
- type: recall_at_10
value: 64.839
- type: recall_at_100
value: 85.983
- type: recall_at_1000
value: 98.467
- type: recall_at_3
value: 50.678
- type: recall_at_5
value: 56.24400000000001
- task:
type: PairClassification
dataset:
type: None
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.75742574257426
- type: cos_sim_ap
value: 93.4938177052363
- type: cos_sim_f1
value: 87.45019920318725
- type: cos_sim_precision
value: 87.10317460317461
- type: cos_sim_recall
value: 87.8
- type: dot_accuracy
value: 99.75742574257426
- type: dot_ap
value: 93.4938177052363
- type: dot_f1
value: 87.45019920318725
- type: dot_precision
value: 87.10317460317461
- type: dot_recall
value: 87.8
- type: euclidean_accuracy
value: 99.75742574257426
- type: euclidean_ap
value: 93.4938177052363
- type: euclidean_f1
value: 87.45019920318725
- type: euclidean_precision
value: 87.10317460317461
- type: euclidean_recall
value: 87.8
- type: manhattan_accuracy
value: 99.77425742574258
- type: manhattan_ap
value: 94.11582049960462
- type: manhattan_f1
value: 88.3367139959432
- type: manhattan_precision
value: 89.60905349794238
- type: manhattan_recall
value: 87.1
- type: max_accuracy
value: 99.77425742574258
- type: max_ap
value: 94.11582049960462
- type: max_f1
value: 88.3367139959432
- task:
type: Clustering
dataset:
type: None
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 40.69098529569445
- task:
type: Clustering
dataset:
type: None
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 29.68544212745689
- task:
type: Reranking
dataset:
type: None
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 43.065922067847836
- type: mrr
value: 43.64432136490961
- task:
type: Summarization
dataset:
type: None
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 29.750957237960492
- type: cos_sim_spearman
value: 30.099771071145582
- type: dot_pearson
value: 29.75095720371408
- type: dot_spearman
value: 30.128683537072114
- task:
type: Retrieval
dataset:
type: None
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.129
- type: map_at_10
value: 0.6890000000000001
- type: map_at_100
value: 3.511
- type: map_at_1000
value: 8.943
- type: map_at_3
value: 0.304
- type: map_at_5
value: 0.42700000000000005
- type: mrr_at_1
value: 56.00000000000001
- type: mrr_at_10
value: 65.908
- type: mrr_at_100
value: 66.60199999999999
- type: mrr_at_1000
value: 66.60199999999999
- type: mrr_at_3
value: 63.333
- type: mrr_at_5
value: 64.23299999999999
- type: ndcg_at_1
value: 51
- type: ndcg_at_10
value: 39.304
- type: ndcg_at_100
value: 29.392000000000003
- type: ndcg_at_1000
value: 26.044
- type: ndcg_at_3
value: 45.408
- type: ndcg_at_5
value: 41.997
- type: precision_at_1
value: 56.00000000000001
- type: precision_at_10
value: 40.8
- type: precision_at_100
value: 30.48
- type: precision_at_1000
value: 12.692
- type: precision_at_3
value: 48
- type: precision_at_5
value: 43.6
- type: recall_at_1
value: 0.129
- type: recall_at_10
value: 0.893
- type: recall_at_100
value: 6.324000000000001
- type: recall_at_1000
value: 24.964
- type: recall_at_3
value: 0.33999999999999997
- type: recall_at_5
value: 0.505
- task:
type: Retrieval
dataset:
type: None
name: MTEB Touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 1.6179999999999999
- type: map_at_10
value: 8.232000000000001
- type: map_at_100
value: 14.643999999999998
- type: map_at_1000
value: 16.259
- type: map_at_3
value: 4.2090000000000005
- type: map_at_5
value: 5.401
- type: mrr_at_1
value: 24.490000000000002
- type: mrr_at_10
value: 43.963
- type: mrr_at_100
value: 45.022
- type: mrr_at_1000
value: 45.039
- type: mrr_at_3
value: 42.177
- type: mrr_at_5
value: 42.687000000000005
- type: ndcg_at_1
value: 23.469
- type: ndcg_at_10
value: 22.526
- type: ndcg_at_100
value: 36.411
- type: ndcg_at_1000
value: 47.461
- type: ndcg_at_3
value: 27.176000000000002
- type: ndcg_at_5
value: 23.787
- type: precision_at_1
value: 24.490000000000002
- type: precision_at_10
value: 20
- type: precision_at_100
value: 8.286
- type: precision_at_1000
value: 1.543
- type: precision_at_3
value: 29.252
- type: precision_at_5
value: 23.265
- type: recall_at_1
value: 1.6179999999999999
- type: recall_at_10
value: 14.443
- type: recall_at_100
value: 50.073
- type: recall_at_1000
value: 83.56700000000001
- type: recall_at_3
value: 5.831
- type: recall_at_5
value: 7.797
- task:
type: Classification
dataset:
type: None
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 69.5932
- type: ap
value: 13.748287764670659
- type: f1
value: 53.6121537777008
- task:
type: Classification
dataset:
type: None
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 48.60498019241653
- type: f1
value: 48.8190614849162
- task:
type: Clustering
dataset:
type: None
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 37.40279692338929
- task:
type: PairClassification
dataset:
type: None
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 83.11378673183525
- type: cos_sim_ap
value: 63.412004464549696
- type: cos_sim_f1
value: 60.880921286952386
- type: cos_sim_precision
value: 55.34211094323332
- type: cos_sim_recall
value: 67.65171503957784
- type: dot_accuracy
value: 83.11378673183525
- type: dot_ap
value: 63.412004464549696
- type: dot_f1
value: 60.880921286952386
- type: dot_precision
value: 55.34211094323332
- type: dot_recall
value: 67.65171503957784
- type: euclidean_accuracy
value: 83.11378673183525
- type: euclidean_ap
value: 63.412004464549696
- type: euclidean_f1
value: 60.880921286952386
- type: euclidean_precision
value: 55.34211094323332
- type: euclidean_recall
value: 67.65171503957784
- type: manhattan_accuracy
value: 82.13625797222389
- type: manhattan_ap
value: 60.704142220415335
- type: manhattan_f1
value: 58.10686319668357
- type: manhattan_precision
value: 51.55292194523907
- type: manhattan_recall
value: 66.56992084432719
- type: max_accuracy
value: 83.11378673183525
- type: max_ap
value: 63.412004464549696
- type: max_f1
value: 60.880921286952386
- task:
type: PairClassification
dataset:
type: None
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 87.48593161796096
- type: cos_sim_ap
value: 83.09276630048417
- type: cos_sim_f1
value: 75.22376690154258
- type: cos_sim_precision
value: 74.4328031958996
- type: cos_sim_recall
value: 76.03172158915923
- type: dot_accuracy
value: 87.48593161796096
- type: dot_ap
value: 83.09276630048417
- type: dot_f1
value: 75.22376690154258
- type: dot_precision
value: 74.4328031958996
- type: dot_recall
value: 76.03172158915923
- type: euclidean_accuracy
value: 87.48593161796096
- type: euclidean_ap
value: 83.09276683624702
- type: euclidean_f1
value: 75.22376690154258
- type: euclidean_precision
value: 74.4328031958996
- type: euclidean_recall
value: 76.03172158915923
- type: manhattan_accuracy
value: 87.49369348391353
- type: manhattan_ap
value: 82.94869347657408
- type: manhattan_f1
value: 74.95875695376942
- type: manhattan_precision
value: 74.70367821365757
- type: manhattan_recall
value: 75.21558361564522
- type: max_accuracy
value: 87.49369348391353
- type: max_ap
value: 83.09276683624702
- type: max_f1
value: 75.22376690154258