metadata
tags:
- mteb
model-index:
- name: nomic_classification_50
results:
- task:
type: Classification
dataset:
type: None
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 67.26865671641791
- type: ap
value: 30.002473367582354
- type: f1
value: 61.1971953752801
- task:
type: Classification
dataset:
type: None
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 64.285825
- type: ap
value: 59.48909573055728
- type: f1
value: 63.9870581887586
- task:
type: Classification
dataset:
type: None
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 32.094
- type: f1
value: 31.58604218365913
- task:
type: Retrieval
dataset:
type: None
name: MTEB ArguAna
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 13.016
- type: map_at_10
value: 22.521
- type: map_at_100
value: 23.799
- type: map_at_1000
value: 23.883
- type: map_at_3
value: 19.381
- type: map_at_5
value: 20.928
- type: mrr_at_1
value: 13.442000000000002
- type: mrr_at_10
value: 22.667
- type: mrr_at_100
value: 23.944
- type: mrr_at_1000
value: 24.029
- type: mrr_at_3
value: 19.523
- type: mrr_at_5
value: 21.102
- type: ndcg_at_1
value: 13.016
- type: ndcg_at_10
value: 28.059
- type: ndcg_at_100
value: 34.812
- type: ndcg_at_1000
value: 37.074
- type: ndcg_at_3
value: 21.438
- type: ndcg_at_5
value: 24.238
- type: precision_at_1
value: 13.016
- type: precision_at_10
value: 4.595
- type: precision_at_100
value: 0.787
- type: precision_at_1000
value: 0.097
- type: precision_at_3
value: 9.128
- type: precision_at_5
value: 6.842
- type: recall_at_1
value: 13.016
- type: recall_at_10
value: 45.946
- type: recall_at_100
value: 78.73400000000001
- type: recall_at_1000
value: 96.515
- type: recall_at_3
value: 27.383000000000003
- type: recall_at_5
value: 34.211000000000006
- task:
type: Clustering
dataset:
type: None
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 25.72708581045921
- task:
type: Clustering
dataset:
type: None
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 17.273102202229808
- task:
type: Reranking
dataset:
type: None
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 48.99875215426555
- type: mrr
value: 60.91731521786923
- task:
type: STS
dataset:
type: None
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 67.57739420865997
- type: cos_sim_spearman
value: 68.8491591362424
- type: euclidean_pearson
value: 67.94540320514962
- type: euclidean_spearman
value: 68.8491591362424
- type: manhattan_pearson
value: 65.69150432274179
- type: manhattan_spearman
value: 66.33223431652344
- task:
type: Classification
dataset:
type: None
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 57.698051948051955
- type: f1
value: 56.00046616188858
- task:
type: Clustering
dataset:
type: None
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 24.472330529075432
- task:
type: Clustering
dataset:
type: None
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 15.20312280133779
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: f46a197baaae43b4f621051089b82a364682dfeb
metrics:
- type: map_at_1
value: 11.856
- type: map_at_10
value: 15.922
- type: map_at_100
value: 16.692999999999998
- type: map_at_1000
value: 16.844
- type: map_at_3
value: 14.233
- type: map_at_5
value: 15.315999999999999
- type: mrr_at_1
value: 14.449000000000002
- type: mrr_at_10
value: 19.359
- type: mrr_at_100
value: 20.095
- type: mrr_at_1000
value: 20.194000000000003
- type: mrr_at_3
value: 17.501
- type: mrr_at_5
value: 18.66
- type: ndcg_at_1
value: 14.449000000000002
- type: ndcg_at_10
value: 19.192999999999998
- type: ndcg_at_100
value: 23.237
- type: ndcg_at_1000
value: 27.032
- type: ndcg_at_3
value: 16.265
- type: ndcg_at_5
value: 17.863
- type: precision_at_1
value: 14.449000000000002
- type: precision_at_10
value: 3.662
- type: precision_at_100
value: 0.718
- type: precision_at_1000
value: 0.129
- type: precision_at_3
value: 7.630000000000001
- type: precision_at_5
value: 5.866
- type: recall_at_1
value: 11.856
- type: recall_at_10
value: 25.694
- type: recall_at_100
value: 44.003
- type: recall_at_1000
value: 71.039
- type: recall_at_3
value: 17.136000000000003
- type: recall_at_5
value: 21.393
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
metrics:
- type: map_at_1
value: 8.758000000000001
- type: map_at_10
value: 12.205
- type: map_at_100
value: 12.859000000000002
- type: map_at_1000
value: 12.967
- type: map_at_3
value: 11.196
- type: map_at_5
value: 11.676
- type: mrr_at_1
value: 11.21
- type: mrr_at_10
value: 15.062000000000001
- type: mrr_at_100
value: 15.720999999999998
- type: mrr_at_1000
value: 15.803
- type: mrr_at_3
value: 13.896
- type: mrr_at_5
value: 14.456
- type: ndcg_at_1
value: 11.21
- type: ndcg_at_10
value: 14.64
- type: ndcg_at_100
value: 18.163
- type: ndcg_at_1000
value: 21.15
- type: ndcg_at_3
value: 12.838
- type: ndcg_at_5
value: 13.475000000000001
- type: precision_at_1
value: 11.21
- type: precision_at_10
value: 2.79
- type: precision_at_100
value: 0.575
- type: precision_at_1000
value: 0.105
- type: precision_at_3
value: 6.306000000000001
- type: precision_at_5
value: 4.369
- type: recall_at_1
value: 8.758000000000001
- type: recall_at_10
value: 19.213
- type: recall_at_100
value: 35.434
- type: recall_at_1000
value: 56.720000000000006
- type: recall_at_3
value: 13.758999999999999
- type: recall_at_5
value: 15.618000000000002
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 11.655999999999999
- type: map_at_10
value: 15.429
- type: map_at_100
value: 16.223000000000003
- type: map_at_1000
value: 16.334
- type: map_at_3
value: 14.069999999999999
- type: map_at_5
value: 14.815000000000001
- type: mrr_at_1
value: 13.48
- type: mrr_at_10
value: 17.421
- type: mrr_at_100
value: 18.195
- type: mrr_at_1000
value: 18.285
- type: mrr_at_3
value: 15.967
- type: mrr_at_5
value: 16.75
- type: ndcg_at_1
value: 13.48
- type: ndcg_at_10
value: 18.053
- type: ndcg_at_100
value: 22.471
- type: ndcg_at_1000
value: 25.689
- type: ndcg_at_3
value: 15.290000000000001
- type: ndcg_at_5
value: 16.536
- type: precision_at_1
value: 13.48
- type: precision_at_10
value: 2.991
- type: precision_at_100
value: 0.586
- type: precision_at_1000
value: 0.095
- type: precision_at_3
value: 6.729
- type: precision_at_5
value: 4.853
- type: recall_at_1
value: 11.655999999999999
- type: recall_at_10
value: 24.329
- type: recall_at_100
value: 45.178000000000004
- type: recall_at_1000
value: 69.83200000000001
- type: recall_at_3
value: 16.692
- type: recall_at_5
value: 19.767000000000003
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 5003b3064772da1887988e05400cf3806fe491f2
metrics:
- type: map_at_1
value: 3.672
- type: map_at_10
value: 5.507
- type: map_at_100
value: 5.853
- type: map_at_1000
value: 5.9319999999999995
- type: map_at_3
value: 4.648
- type: map_at_5
value: 5.087
- type: mrr_at_1
value: 4.0680000000000005
- type: mrr_at_10
value: 6.03
- type: mrr_at_100
value: 6.404999999999999
- type: mrr_at_1000
value: 6.485
- type: mrr_at_3
value: 5.16
- type: mrr_at_5
value: 5.595
- type: ndcg_at_1
value: 4.0680000000000005
- type: ndcg_at_10
value: 6.955
- type: ndcg_at_100
value: 9.059000000000001
- type: ndcg_at_1000
value: 11.916
- type: ndcg_at_3
value: 5.137
- type: ndcg_at_5
value: 5.912
- type: precision_at_1
value: 4.0680000000000005
- type: precision_at_10
value: 1.232
- type: precision_at_100
value: 0.246
- type: precision_at_1000
value: 0.053
- type: precision_at_3
value: 2.26
- type: precision_at_5
value: 1.763
- type: recall_at_1
value: 3.672
- type: recall_at_10
value: 11.149000000000001
- type: recall_at_100
value: 21.564
- type: recall_at_1000
value: 44.851
- type: recall_at_3
value: 6.008
- type: recall_at_5
value: 7.91
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
metrics:
- type: map_at_1
value: 2.308
- type: map_at_10
value: 3.431
- type: map_at_100
value: 3.8890000000000002
- type: map_at_1000
value: 3.988
- type: map_at_3
value: 2.896
- type: map_at_5
value: 3.182
- type: mrr_at_1
value: 2.9850000000000003
- type: mrr_at_10
value: 4.4110000000000005
- type: mrr_at_100
value: 4.925
- type: mrr_at_1000
value: 5.022
- type: mrr_at_3
value: 3.669
- type: mrr_at_5
value: 4.086
- type: ndcg_at_1
value: 2.9850000000000003
- type: ndcg_at_10
value: 4.463
- type: ndcg_at_100
value: 7.03
- type: ndcg_at_1000
value: 10.358
- type: ndcg_at_3
value: 3.3529999999999998
- type: ndcg_at_5
value: 3.866
- type: precision_at_1
value: 2.9850000000000003
- type: precision_at_10
value: 0.9079999999999999
- type: precision_at_100
value: 0.26
- type: precision_at_1000
value: 0.065
- type: precision_at_3
value: 1.575
- type: precision_at_5
value: 1.318
- type: recall_at_1
value: 2.308
- type: recall_at_10
value: 6.776999999999999
- type: recall_at_100
value: 18.618000000000002
- type: recall_at_1000
value: 44.175
- type: recall_at_3
value: 3.687
- type: recall_at_5
value: 4.948
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
metrics:
- type: map_at_1
value: 6.862
- type: map_at_10
value: 9.94
- type: map_at_100
value: 10.624
- type: map_at_1000
value: 10.742
- type: map_at_3
value: 8.690000000000001
- type: map_at_5
value: 9.372
- type: mrr_at_1
value: 8.469999999999999
- type: mrr_at_10
value: 12.328999999999999
- type: mrr_at_100
value: 13.035
- type: mrr_at_1000
value: 13.123999999999999
- type: mrr_at_3
value: 10.828
- type: mrr_at_5
value: 11.752
- type: ndcg_at_1
value: 8.469999999999999
- type: ndcg_at_10
value: 12.377
- type: ndcg_at_100
value: 16.151
- type: ndcg_at_1000
value: 19.580000000000002
- type: ndcg_at_3
value: 9.964
- type: ndcg_at_5
value: 11.137
- type: precision_at_1
value: 8.469999999999999
- type: precision_at_10
value: 2.4250000000000003
- type: precision_at_100
value: 0.5479999999999999
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 4.812
- type: precision_at_5
value: 3.7539999999999996
- type: recall_at_1
value: 6.862
- type: recall_at_10
value: 17.59
- type: recall_at_100
value: 34.557
- type: recall_at_1000
value: 59.78099999999999
- type: recall_at_3
value: 10.838000000000001
- type: recall_at_5
value: 13.8
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
metrics:
- type: map_at_1
value: 4.569
- type: map_at_10
value: 6.9190000000000005
- type: map_at_100
value: 7.435
- type: map_at_1000
value: 7.553999999999999
- type: map_at_3
value: 6.0409999999999995
- type: map_at_5
value: 6.4159999999999995
- type: mrr_at_1
value: 5.822
- type: mrr_at_10
value: 8.639
- type: mrr_at_100
value: 9.195
- type: mrr_at_1000
value: 9.292
- type: mrr_at_3
value: 7.571999999999999
- type: mrr_at_5
value: 8.04
- type: ndcg_at_1
value: 5.822
- type: ndcg_at_10
value: 8.808
- type: ndcg_at_100
value: 11.846
- type: ndcg_at_1000
value: 15.476
- type: ndcg_at_3
value: 6.995
- type: ndcg_at_5
value: 7.5920000000000005
- type: precision_at_1
value: 5.822
- type: precision_at_10
value: 1.7469999999999999
- type: precision_at_100
value: 0.398
- type: precision_at_1000
value: 0.08800000000000001
- type: precision_at_3
value: 3.4250000000000003
- type: precision_at_5
value: 2.489
- type: recall_at_1
value: 4.569
- type: recall_at_10
value: 13.035
- type: recall_at_100
value: 27.102999999999998
- type: recall_at_1000
value: 54.137
- type: recall_at_3
value: 7.839
- type: recall_at_5
value: 9.469
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 6.289666666666665
- type: map_at_10
value: 8.76325
- type: map_at_100
value: 9.314083333333333
- type: map_at_1000
value: 9.419
- type: map_at_3
value: 7.856916666666668
- type: map_at_5
value: 8.359333333333334
- type: mrr_at_1
value: 7.752333333333332
- type: mrr_at_10
value: 10.620333333333333
- type: mrr_at_100
value: 11.191083333333333
- type: mrr_at_1000
value: 11.2795
- type: mrr_at_3
value: 9.572916666666668
- type: mrr_at_5
value: 10.152499999999998
- type: ndcg_at_1
value: 7.752333333333332
- type: ndcg_at_10
value: 10.657000000000002
- type: ndcg_at_100
value: 13.755166666666666
- type: ndcg_at_1000
value: 16.9275
- type: ndcg_at_3
value: 8.904916666666665
- type: ndcg_at_5
value: 9.709083333333334
- type: precision_at_1
value: 7.752333333333332
- type: precision_at_10
value: 1.969166666666667
- type: precision_at_100
value: 0.42624999999999996
- type: precision_at_1000
value: 0.08475000000000002
- type: precision_at_3
value: 4.182
- type: precision_at_5
value: 3.0942499999999997
- type: recall_at_1
value: 6.289666666666665
- type: recall_at_10
value: 14.695083333333333
- type: recall_at_100
value: 29.238666666666663
- type: recall_at_1000
value: 53.20016666666667
- type: recall_at_3
value: 9.667
- type: recall_at_5
value: 11.766416666666666
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
metrics:
- type: map_at_1
value: 5.188000000000001
- type: map_at_10
value: 6.97
- type: map_at_100
value: 7.380000000000001
- type: map_at_1000
value: 7.446999999999999
- type: map_at_3
value: 6.357
- type: map_at_5
value: 6.736000000000001
- type: mrr_at_1
value: 6.748
- type: mrr_at_10
value: 8.885
- type: mrr_at_100
value: 9.285
- type: mrr_at_1000
value: 9.353
- type: mrr_at_3
value: 8.206
- type: mrr_at_5
value: 8.689
- type: ndcg_at_1
value: 6.748
- type: ndcg_at_10
value: 8.394
- type: ndcg_at_100
value: 10.554
- type: ndcg_at_1000
value: 12.786
- type: ndcg_at_3
value: 7.227
- type: ndcg_at_5
value: 7.878
- type: precision_at_1
value: 6.748
- type: precision_at_10
value: 1.442
- type: precision_at_100
value: 0.27799999999999997
- type: precision_at_1000
value: 0.052
- type: precision_at_3
value: 3.3230000000000004
- type: precision_at_5
value: 2.4539999999999997
- type: recall_at_1
value: 5.188000000000001
- type: recall_at_10
value: 11.109
- type: recall_at_100
value: 21.134
- type: recall_at_1000
value: 38.686
- type: recall_at_3
value: 7.795000000000001
- type: recall_at_5
value: 9.435
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 3.4070000000000005
- type: map_at_10
value: 4.735
- type: map_at_100
value: 5.083
- type: map_at_1000
value: 5.162
- type: map_at_3
value: 4.261
- type: map_at_5
value: 4.504
- type: mrr_at_1
value: 4.1290000000000004
- type: mrr_at_10
value: 5.792
- type: mrr_at_100
value: 6.209
- type: mrr_at_1000
value: 6.283999999999999
- type: mrr_at_3
value: 5.173
- type: mrr_at_5
value: 5.505
- type: ndcg_at_1
value: 4.1290000000000004
- type: ndcg_at_10
value: 5.8020000000000005
- type: ndcg_at_100
value: 7.861
- type: ndcg_at_1000
value: 10.495000000000001
- type: ndcg_at_3
value: 4.79
- type: ndcg_at_5
value: 5.2299999999999995
- type: precision_at_1
value: 4.1290000000000004
- type: precision_at_10
value: 1.084
- type: precision_at_100
value: 0.262
- type: precision_at_1000
value: 0.06
- type: precision_at_3
value: 2.237
- type: precision_at_5
value: 1.6789999999999998
- type: recall_at_1
value: 3.4070000000000005
- type: recall_at_10
value: 8.057
- type: recall_at_100
value: 17.662
- type: recall_at_1000
value: 37.738
- type: recall_at_3
value: 5.27
- type: recall_at_5
value: 6.314
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
metrics:
- type: map_at_1
value: 5.559
- type: map_at_10
value: 7.374
- type: map_at_100
value: 7.9159999999999995
- type: map_at_1000
value: 8.007
- type: map_at_3
value: 6.882000000000001
- type: map_at_5
value: 7.1209999999999996
- type: mrr_at_1
value: 6.622999999999999
- type: mrr_at_10
value: 8.873000000000001
- type: mrr_at_100
value: 9.478
- type: mrr_at_1000
value: 9.562
- type: mrr_at_3
value: 8.256
- type: mrr_at_5
value: 8.535
- type: ndcg_at_1
value: 6.622999999999999
- type: ndcg_at_10
value: 8.738999999999999
- type: ndcg_at_100
value: 11.931
- type: ndcg_at_1000
value: 14.862
- type: ndcg_at_3
value: 7.713
- type: ndcg_at_5
value: 8.116
- type: precision_at_1
value: 6.622999999999999
- type: precision_at_10
value: 1.493
- type: precision_at_100
value: 0.361
- type: precision_at_1000
value: 0.06899999999999999
- type: precision_at_3
value: 3.6069999999999998
- type: precision_at_5
value: 2.463
- type: recall_at_1
value: 5.559
- type: recall_at_10
value: 11.509
- type: recall_at_100
value: 26.573
- type: recall_at_1000
value: 49.16
- type: recall_at_3
value: 8.468
- type: recall_at_5
value: 9.64
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 7.291
- type: map_at_10
value: 9.99
- type: map_at_100
value: 10.659
- type: map_at_1000
value: 10.793999999999999
- type: map_at_3
value: 8.968
- type: map_at_5
value: 9.59
- type: mrr_at_1
value: 9.684
- type: mrr_at_10
value: 12.812000000000001
- type: mrr_at_100
value: 13.482
- type: mrr_at_1000
value: 13.575999999999999
- type: mrr_at_3
value: 11.561
- type: mrr_at_5
value: 12.232999999999999
- type: ndcg_at_1
value: 9.684
- type: ndcg_at_10
value: 12.281
- type: ndcg_at_100
value: 15.994
- type: ndcg_at_1000
value: 19.578
- type: ndcg_at_3
value: 10.525
- type: ndcg_at_5
value: 11.349
- type: precision_at_1
value: 9.684
- type: precision_at_10
value: 2.451
- type: precision_at_100
value: 0.5910000000000001
- type: precision_at_1000
value: 0.132
- type: precision_at_3
value: 5.138
- type: precision_at_5
value: 3.794
- type: recall_at_1
value: 7.291
- type: recall_at_10
value: 16.28
- type: recall_at_100
value: 34.432
- type: recall_at_1000
value: 60.155
- type: recall_at_3
value: 10.767
- type: recall_at_5
value: 13.156
- task:
type: Retrieval
dataset:
type: None
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 4.35
- type: map_at_10
value: 6.737
- type: map_at_100
value: 7.155
- type: map_at_1000
value: 7.257
- type: map_at_3
value: 6.0409999999999995
- type: map_at_5
value: 6.497
- type: mrr_at_1
value: 5.36
- type: mrr_at_10
value: 7.831
- type: mrr_at_100
value: 8.268
- type: mrr_at_1000
value: 8.373999999999999
- type: mrr_at_3
value: 7.086
- type: mrr_at_5
value: 7.529
- type: ndcg_at_1
value: 5.36
- type: ndcg_at_10
value: 8.179
- type: ndcg_at_100
value: 10.764999999999999
- type: ndcg_at_1000
value: 14.208000000000002
- type: ndcg_at_3
value: 6.762
- type: ndcg_at_5
value: 7.555000000000001
- type: precision_at_1
value: 5.36
- type: precision_at_10
value: 1.405
- type: precision_at_100
value: 0.292
- type: precision_at_1000
value: 0.066
- type: precision_at_3
value: 3.1419999999999995
- type: precision_at_5
value: 2.329
- type: recall_at_1
value: 4.35
- type: recall_at_10
value: 11.599
- type: recall_at_100
value: 24.606
- type: recall_at_1000
value: 52.128
- type: recall_at_3
value: 7.745
- type: recall_at_5
value: 9.747
- task:
type: Retrieval
dataset:
type: None
name: MTEB ClimateFEVER
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 1.496
- type: map_at_10
value: 2.412
- type: map_at_100
value: 2.899
- type: map_at_1000
value: 2.996
- type: map_at_3
value: 1.9949999999999999
- type: map_at_5
value: 2.171
- type: mrr_at_1
value: 3.1919999999999997
- type: mrr_at_10
value: 5.2589999999999995
- type: mrr_at_100
value: 6.053
- type: mrr_at_1000
value: 6.142
- type: mrr_at_3
value: 4.376
- type: mrr_at_5
value: 4.793
- type: ndcg_at_1
value: 3.1919999999999997
- type: ndcg_at_10
value: 3.81
- type: ndcg_at_100
value: 6.822
- type: ndcg_at_1000
value: 9.649000000000001
- type: ndcg_at_3
value: 2.817
- type: ndcg_at_5
value: 3.114
- type: precision_at_1
value: 3.1919999999999997
- type: precision_at_10
value: 1.29
- type: precision_at_100
value: 0.45199999999999996
- type: precision_at_1000
value: 0.097
- type: precision_at_3
value: 2.085
- type: precision_at_5
value: 1.6680000000000001
- type: recall_at_1
value: 1.496
- type: recall_at_10
value: 5.053
- type: recall_at_100
value: 16.066
- type: recall_at_1000
value: 32.796
- type: recall_at_3
value: 2.662
- type: recall_at_5
value: 3.434
- task:
type: Retrieval
dataset:
type: None
name: MTEB DBPedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 0.473
- type: map_at_10
value: 1.149
- type: map_at_100
value: 1.614
- type: map_at_1000
value: 1.7760000000000002
- type: map_at_3
value: 0.808
- type: map_at_5
value: 0.9520000000000001
- type: mrr_at_1
value: 9
- type: mrr_at_10
value: 13.528
- type: mrr_at_100
value: 14.567
- type: mrr_at_1000
value: 14.648
- type: mrr_at_3
value: 12.417
- type: mrr_at_5
value: 13.129
- type: ndcg_at_1
value: 6.375
- type: ndcg_at_10
value: 4.561
- type: ndcg_at_100
value: 5.412
- type: ndcg_at_1000
value: 8.173
- type: ndcg_at_3
value: 5.882
- type: ndcg_at_5
value: 5.16
- type: precision_at_1
value: 9
- type: precision_at_10
value: 4.45
- type: precision_at_100
value: 1.53
- type: precision_at_1000
value: 0.41000000000000003
- type: precision_at_3
value: 7.667
- type: precision_at_5
value: 6.1
- type: recall_at_1
value: 0.473
- type: recall_at_10
value: 2.11
- type: recall_at_100
value: 6.957000000000001
- type: recall_at_1000
value: 16.188
- type: recall_at_3
value: 1.031
- type: recall_at_5
value: 1.447
- task:
type: Classification
dataset:
type: None
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 36.510000000000005
- type: f1
value: 32.55269059609507
- task:
type: Retrieval
dataset:
type: None
name: MTEB FEVER
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 1.735
- type: map_at_10
value: 2.7969999999999997
- type: map_at_100
value: 3.0300000000000002
- type: map_at_1000
value: 3.078
- type: map_at_3
value: 2.408
- type: map_at_5
value: 2.62
- type: mrr_at_1
value: 1.83
- type: mrr_at_10
value: 2.946
- type: mrr_at_100
value: 3.196
- type: mrr_at_1000
value: 3.2460000000000004
- type: mrr_at_3
value: 2.54
- type: mrr_at_5
value: 2.768
- type: ndcg_at_1
value: 1.83
- type: ndcg_at_10
value: 3.481
- type: ndcg_at_100
value: 4.9110000000000005
- type: ndcg_at_1000
value: 6.553000000000001
- type: ndcg_at_3
value: 2.661
- type: ndcg_at_5
value: 3.052
- type: precision_at_1
value: 1.83
- type: precision_at_10
value: 0.59
- type: precision_at_100
value: 0.13899999999999998
- type: precision_at_1000
value: 0.029
- type: precision_at_3
value: 1.16
- type: precision_at_5
value: 0.897
- type: recall_at_1
value: 1.735
- type: recall_at_10
value: 5.514
- type: recall_at_100
value: 12.671
- type: recall_at_1000
value: 26.081
- type: recall_at_3
value: 3.2649999999999997
- type: recall_at_5
value: 4.205
- task:
type: Retrieval
dataset:
type: None
name: MTEB FiQA2018
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 1.8519999999999999
- type: map_at_10
value: 3.3000000000000003
- type: map_at_100
value: 3.7699999999999996
- type: map_at_1000
value: 3.904
- type: map_at_3
value: 2.665
- type: map_at_5
value: 2.991
- type: mrr_at_1
value: 3.8580000000000005
- type: mrr_at_10
value: 6.611000000000001
- type: mrr_at_100
value: 7.244000000000001
- type: mrr_at_1000
value: 7.356999999999999
- type: mrr_at_3
value: 5.607
- type: mrr_at_5
value: 6.101
- type: ndcg_at_1
value: 3.8580000000000005
- type: ndcg_at_10
value: 5.081
- type: ndcg_at_100
value: 8.054
- type: ndcg_at_1000
value: 12.078999999999999
- type: ndcg_at_3
value: 3.934
- type: ndcg_at_5
value: 4.349
- type: precision_at_1
value: 3.8580000000000005
- type: precision_at_10
value: 1.6199999999999999
- type: precision_at_100
value: 0.477
- type: precision_at_1000
value: 0.11399999999999999
- type: precision_at_3
value: 2.881
- type: precision_at_5
value: 2.253
- type: recall_at_1
value: 1.8519999999999999
- type: recall_at_10
value: 7.109999999999999
- type: recall_at_100
value: 19.224
- type: recall_at_1000
value: 45.913
- type: recall_at_3
value: 3.6839999999999997
- type: recall_at_5
value: 4.999
- task:
type: Retrieval
dataset:
type: None
name: MTEB HotpotQA
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 1.789
- type: map_at_10
value: 2.761
- type: map_at_100
value: 2.997
- type: map_at_1000
value: 3.05
- type: map_at_3
value: 2.4330000000000003
- type: map_at_5
value: 2.612
- type: mrr_at_1
value: 3.579
- type: mrr_at_10
value: 5.311
- type: mrr_at_100
value: 5.692
- type: mrr_at_1000
value: 5.762
- type: mrr_at_3
value: 4.718
- type: mrr_at_5
value: 5.035
- type: ndcg_at_1
value: 3.579
- type: ndcg_at_10
value: 3.988
- type: ndcg_at_100
value: 5.508
- type: ndcg_at_1000
value: 7.3340000000000005
- type: ndcg_at_3
value: 3.183
- type: ndcg_at_5
value: 3.5589999999999997
- type: precision_at_1
value: 3.579
- type: precision_at_10
value: 1.002
- type: precision_at_100
value: 0.22599999999999998
- type: precision_at_1000
value: 0.047
- type: precision_at_3
value: 2.116
- type: precision_at_5
value: 1.569
- type: recall_at_1
value: 1.789
- type: recall_at_10
value: 5.01
- type: recall_at_100
value: 11.296000000000001
- type: recall_at_1000
value: 23.733999999999998
- type: recall_at_3
value: 3.174
- type: recall_at_5
value: 3.923
- task:
type: Classification
dataset:
type: None
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 64.362
- type: ap
value: 59.55580844913024
- type: f1
value: 64.25451691590179
- task:
type: Retrieval
dataset:
type: None
name: MTEB MSMARCO
config: default
split: dev
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 1.719
- type: map_at_10
value: 2.812
- type: map_at_100
value: 3.124
- type: map_at_1000
value: 3.18
- type: map_at_3
value: 2.4
- type: map_at_5
value: 2.598
- type: mrr_at_1
value: 1.7770000000000001
- type: mrr_at_10
value: 2.889
- type: mrr_at_100
value: 3.211
- type: mrr_at_1000
value: 3.2680000000000002
- type: mrr_at_3
value: 2.467
- type: mrr_at_5
value: 2.67
- type: ndcg_at_1
value: 1.762
- type: ndcg_at_10
value: 3.52
- type: ndcg_at_100
value: 5.343
- type: ndcg_at_1000
value: 7.217999999999999
- type: ndcg_at_3
value: 2.64
- type: ndcg_at_5
value: 2.9979999999999998
- type: precision_at_1
value: 1.762
- type: precision_at_10
value: 0.5950000000000001
- type: precision_at_100
value: 0.155
- type: precision_at_1000
value: 0.032
- type: precision_at_3
value: 1.127
- type: precision_at_5
value: 0.857
- type: recall_at_1
value: 1.719
- type: recall_at_10
value: 5.743
- type: recall_at_100
value: 14.89
- type: recall_at_1000
value: 30.267
- type: recall_at_3
value: 3.2779999999999996
- type: recall_at_5
value: 4.136
- task:
type: Classification
dataset:
type: None
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 80.50615595075239
- type: f1
value: 80.1136210996985
- task:
type: Classification
dataset:
type: None
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 54.031007751937985
- type: f1
value: 34.910049182212575
- task:
type: Classification
dataset:
type: None
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 54.96973772696705
- type: f1
value: 51.482021499786136
- task:
type: Classification
dataset:
type: None
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 63.19771351714862
- type: f1
value: 61.16551291933069
- task:
type: Clustering
dataset:
type: None
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 23.502491371355365
- task:
type: Clustering
dataset:
type: None
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 20.04508433667435
- task:
type: Reranking
dataset:
type: None
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 27.223268042111425
- type: mrr
value: 27.804265249287663
- task:
type: Retrieval
dataset:
type: None
name: MTEB NFCorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 0.438
- type: map_at_10
value: 1.414
- type: map_at_100
value: 2.027
- type: map_at_1000
value: 2.866
- type: map_at_3
value: 0.9690000000000001
- type: map_at_5
value: 1.214
- type: mrr_at_1
value: 8.978
- type: mrr_at_10
value: 16.274
- type: mrr_at_100
value: 17.544999999999998
- type: mrr_at_1000
value: 17.649
- type: mrr_at_3
value: 13.674
- type: mrr_at_5
value: 15.021
- type: ndcg_at_1
value: 8.514
- type: ndcg_at_10
value: 7.301
- type: ndcg_at_100
value: 8.613999999999999
- type: ndcg_at_1000
value: 18.851000000000003
- type: ndcg_at_3
value: 8.193
- type: ndcg_at_5
value: 7.747999999999999
- type: precision_at_1
value: 8.978
- type: precision_at_10
value: 5.913
- type: precision_at_100
value: 3.198
- type: precision_at_1000
value: 1.6
- type: precision_at_3
value: 8.256
- type: precision_at_5
value: 7.1209999999999996
- type: recall_at_1
value: 0.438
- type: recall_at_10
value: 3.5360000000000005
- type: recall_at_100
value: 12.414
- type: recall_at_1000
value: 47.949000000000005
- type: recall_at_3
value: 1.462
- type: recall_at_5
value: 2.4299999999999997
- task:
type: Retrieval
dataset:
type: None
name: MTEB NQ
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 2.2640000000000002
- type: map_at_10
value: 3.6859999999999995
- type: map_at_100
value: 4.071000000000001
- type: map_at_1000
value: 4.141
- type: map_at_3
value: 3.136
- type: map_at_5
value: 3.4130000000000003
- type: mrr_at_1
value: 2.52
- type: mrr_at_10
value: 4.093
- type: mrr_at_100
value: 4.51
- type: mrr_at_1000
value: 4.583
- type: mrr_at_3
value: 3.4909999999999997
- type: mrr_at_5
value: 3.791
- type: ndcg_at_1
value: 2.52
- type: ndcg_at_10
value: 4.696
- type: ndcg_at_100
value: 6.914
- type: ndcg_at_1000
value: 9.264999999999999
- type: ndcg_at_3
value: 3.5159999999999996
- type: ndcg_at_5
value: 4.026
- type: precision_at_1
value: 2.52
- type: precision_at_10
value: 0.855
- type: precision_at_100
value: 0.211
- type: precision_at_1000
value: 0.044000000000000004
- type: precision_at_3
value: 1.6420000000000001
- type: precision_at_5
value: 1.257
- type: recall_at_1
value: 2.2640000000000002
- type: recall_at_10
value: 7.478999999999999
- type: recall_at_100
value: 18.163
- type: recall_at_1000
value: 36.846000000000004
- type: recall_at_3
value: 4.268000000000001
- type: recall_at_5
value: 5.485
- task:
type: Retrieval
dataset:
type: None
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 44.559
- type: map_at_10
value: 53.623
- type: map_at_100
value: 54.513999999999996
- type: map_at_1000
value: 54.584999999999994
- type: map_at_3
value: 51.229
- type: map_at_5
value: 52.635
- type: mrr_at_1
value: 51.23
- type: mrr_at_10
value: 58.431999999999995
- type: mrr_at_100
value: 59.00300000000001
- type: mrr_at_1000
value: 59.036
- type: mrr_at_3
value: 56.61000000000001
- type: mrr_at_5
value: 57.730000000000004
- type: ndcg_at_1
value: 51.28
- type: ndcg_at_10
value: 58.306000000000004
- type: ndcg_at_100
value: 61.915
- type: ndcg_at_1000
value: 63.343
- type: ndcg_at_3
value: 54.608000000000004
- type: ndcg_at_5
value: 56.431
- type: precision_at_1
value: 51.28
- type: precision_at_10
value: 8.755
- type: precision_at_100
value: 1.17
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 23.297
- type: precision_at_5
value: 15.598
- type: recall_at_1
value: 44.559
- type: recall_at_10
value: 67.491
- type: recall_at_100
value: 82.938
- type: recall_at_1000
value: 92.72200000000001
- type: recall_at_3
value: 56.952999999999996
- type: recall_at_5
value: 61.83
- task:
type: Clustering
dataset:
type: None
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 22.705180109905008
- task:
type: Clustering
dataset:
type: None
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 34.83434688813055
- task:
type: Retrieval
dataset:
type: None
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.13
- type: map_at_10
value: 2.4570000000000003
- type: map_at_100
value: 3.048
- type: map_at_1000
value: 3.234
- type: map_at_3
value: 1.802
- type: map_at_5
value: 2.078
- type: mrr_at_1
value: 5.6000000000000005
- type: mrr_at_10
value: 9.468
- type: mrr_at_100
value: 10.472
- type: mrr_at_1000
value: 10.605
- type: mrr_at_3
value: 7.7829999999999995
- type: mrr_at_5
value: 8.468
- type: ndcg_at_1
value: 5.6000000000000005
- type: ndcg_at_10
value: 4.936999999999999
- type: ndcg_at_100
value: 8.597000000000001
- type: ndcg_at_1000
value: 13.508999999999999
- type: ndcg_at_3
value: 4.345000000000001
- type: ndcg_at_5
value: 3.782
- type: precision_at_1
value: 5.6000000000000005
- type: precision_at_10
value: 2.68
- type: precision_at_100
value: 0.814
- type: precision_at_1000
value: 0.201
- type: precision_at_3
value: 4
- type: precision_at_5
value: 3.2800000000000002
- type: recall_at_1
value: 1.13
- type: recall_at_10
value: 5.457999999999999
- type: recall_at_100
value: 16.533
- type: recall_at_1000
value: 40.983000000000004
- type: recall_at_3
value: 2.44
- type: recall_at_5
value: 3.343
- task:
type: STS
dataset:
type: None
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 73.60605619256489
- type: cos_sim_spearman
value: 67.90225840700592
- type: euclidean_pearson
value: 72.33353541178548
- type: euclidean_spearman
value: 67.9022659941869
- type: manhattan_pearson
value: 72.05976338595539
- type: manhattan_spearman
value: 67.56691734710643
- task:
type: STS
dataset:
type: None
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 64.53970557195757
- type: cos_sim_spearman
value: 57.30488503100292
- type: euclidean_pearson
value: 61.892226450716926
- type: euclidean_spearman
value: 57.30614347479237
- type: manhattan_pearson
value: 62.211926976767394
- type: manhattan_spearman
value: 57.68789726090663
- task:
type: STS
dataset:
type: None
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 71.42835803449617
- type: cos_sim_spearman
value: 73.427655387467
- type: euclidean_pearson
value: 72.95603876012058
- type: euclidean_spearman
value: 73.42766761221965
- type: manhattan_pearson
value: 72.95156508487149
- type: manhattan_spearman
value: 73.50217040506452
- task:
type: STS
dataset:
type: None
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 68.76336169760297
- type: cos_sim_spearman
value: 65.84204583356208
- type: euclidean_pearson
value: 68.43410821913582
- type: euclidean_spearman
value: 65.84203615293073
- type: manhattan_pearson
value: 68.31068072556376
- type: manhattan_spearman
value: 65.83052670300172
- task:
type: STS
dataset:
type: None
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 70.72278060206496
- type: cos_sim_spearman
value: 72.94488223638993
- type: euclidean_pearson
value: 72.87272723558824
- type: euclidean_spearman
value: 72.9448808909619
- type: manhattan_pearson
value: 73.14312374863987
- type: manhattan_spearman
value: 73.17094226040652
- task:
type: STS
dataset:
type: None
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 67.38872313741369
- type: cos_sim_spearman
value: 69.39591053377866
- type: euclidean_pearson
value: 69.51934754021094
- type: euclidean_spearman
value: 69.39674025878926
- type: manhattan_pearson
value: 69.45552921345616
- type: manhattan_spearman
value: 69.43073792027799
- task:
type: STS
dataset:
type: None
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 74.8928962240664
- type: cos_sim_spearman
value: 78.20100249603948
- type: euclidean_pearson
value: 78.32388609298962
- type: euclidean_spearman
value: 78.20188000341075
- type: manhattan_pearson
value: 78.4500539248116
- type: manhattan_spearman
value: 78.19642157133745
- task:
type: STS
dataset:
type: None
name: MTEB STS22 (en)
config: en
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson
value: 58.85262050940674
- type: cos_sim_spearman
value: 58.37965417152291
- type: euclidean_pearson
value: 59.76016227940433
- type: euclidean_spearman
value: 58.37965417152291
- type: manhattan_pearson
value: 60.2166257965911
- type: manhattan_spearman
value: 58.747276855442045
- task:
type: STS
dataset:
type: None
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 65.88908703880968
- type: cos_sim_spearman
value: 64.7638356299519
- type: euclidean_pearson
value: 66.43284083997051
- type: euclidean_spearman
value: 64.76388404493919
- type: manhattan_pearson
value: 66.54689278447367
- type: manhattan_spearman
value: 64.76609191059656
- task:
type: Reranking
dataset:
type: None
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 62.39526919052546
- type: mrr
value: 83.57624673801143
- task:
type: Retrieval
dataset:
type: None
name: MTEB SciFact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 11.472
- type: map_at_10
value: 15.892000000000001
- type: map_at_100
value: 16.75
- type: map_at_1000
value: 16.898
- type: map_at_3
value: 14.167
- type: map_at_5
value: 15
- type: mrr_at_1
value: 12.667
- type: mrr_at_10
value: 17.065
- type: mrr_at_100
value: 17.899
- type: mrr_at_1000
value: 18.035999999999998
- type: mrr_at_3
value: 15.443999999999999
- type: mrr_at_5
value: 16.228
- type: ndcg_at_1
value: 12.667
- type: ndcg_at_10
value: 18.856
- type: ndcg_at_100
value: 23.555999999999997
- type: ndcg_at_1000
value: 28.138
- type: ndcg_at_3
value: 15.360999999999999
- type: ndcg_at_5
value: 16.712
- type: precision_at_1
value: 12.667
- type: precision_at_10
value: 3.033
- type: precision_at_100
value: 0.563
- type: precision_at_1000
value: 0.098
- type: precision_at_3
value: 6.444
- type: precision_at_5
value: 4.6
- type: recall_at_1
value: 11.472
- type: recall_at_10
value: 27.278000000000002
- type: recall_at_100
value: 49.917
- type: recall_at_1000
value: 86.75
- type: recall_at_3
value: 17.416999999999998
- type: recall_at_5
value: 20.75
- task:
type: PairClassification
dataset:
type: None
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.31683168316832
- type: cos_sim_ap
value: 61.13034379900418
- type: cos_sim_f1
value: 58.92957746478873
- type: cos_sim_precision
value: 67.48387096774194
- type: cos_sim_recall
value: 52.300000000000004
- type: dot_accuracy
value: 99.31683168316832
- type: dot_ap
value: 61.13034379900418
- type: dot_f1
value: 58.92957746478873
- type: dot_precision
value: 67.48387096774194
- type: dot_recall
value: 52.300000000000004
- type: euclidean_accuracy
value: 99.31683168316832
- type: euclidean_ap
value: 61.13034379900418
- type: euclidean_f1
value: 58.92957746478873
- type: euclidean_precision
value: 67.48387096774194
- type: euclidean_recall
value: 52.300000000000004
- type: manhattan_accuracy
value: 99.34554455445544
- type: manhattan_ap
value: 63.09142729872116
- type: manhattan_f1
value: 61.02425876010782
- type: manhattan_precision
value: 66.19883040935673
- type: manhattan_recall
value: 56.599999999999994
- type: max_accuracy
value: 99.34554455445544
- type: max_ap
value: 63.09142729872116
- type: max_f1
value: 61.02425876010782
- task:
type: Clustering
dataset:
type: None
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 31.859456190950397
- task:
type: Clustering
dataset:
type: None
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 29.22083488612398
- task:
type: Reranking
dataset:
type: None
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 38.763497690161216
- type: mrr
value: 38.9332134368899
- task:
type: Summarization
dataset:
type: None
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.037408929578664
- type: cos_sim_spearman
value: 29.62877340560356
- type: dot_pearson
value: 31.037408876961713
- type: dot_spearman
value: 29.578544636218147
- task:
type: Retrieval
dataset:
type: None
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.055999999999999994
- type: map_at_10
value: 0.292
- type: map_at_100
value: 1.335
- type: map_at_1000
value: 3.074
- type: map_at_3
value: 0.123
- type: map_at_5
value: 0.191
- type: mrr_at_1
value: 28.000000000000004
- type: mrr_at_10
value: 38.879999999999995
- type: mrr_at_100
value: 39.953
- type: mrr_at_1000
value: 39.978
- type: mrr_at_3
value: 33.333
- type: mrr_at_5
value: 37.233
- type: ndcg_at_1
value: 22
- type: ndcg_at_10
value: 19.601
- type: ndcg_at_100
value: 14.735000000000001
- type: ndcg_at_1000
value: 14.915000000000001
- type: ndcg_at_3
value: 20.358
- type: ndcg_at_5
value: 21.543
- type: precision_at_1
value: 28.000000000000004
- type: precision_at_10
value: 21.2
- type: precision_at_100
value: 15.5
- type: precision_at_1000
value: 7.417999999999999
- type: precision_at_3
value: 22.667
- type: precision_at_5
value: 24.4
- type: recall_at_1
value: 0.055999999999999994
- type: recall_at_10
value: 0.44799999999999995
- type: recall_at_100
value: 3.3070000000000004
- type: recall_at_1000
value: 15.334
- type: recall_at_3
value: 0.13699999999999998
- type: recall_at_5
value: 0.27499999999999997
- task:
type: Retrieval
dataset:
type: None
name: MTEB Touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 1.66
- type: map_at_10
value: 4.183
- type: map_at_100
value: 5.748
- type: map_at_1000
value: 6.645
- type: map_at_3
value: 3.024
- type: map_at_5
value: 3.711
- type: mrr_at_1
value: 24.490000000000002
- type: mrr_at_10
value: 30.226
- type: mrr_at_100
value: 31.849
- type: mrr_at_1000
value: 31.915
- type: mrr_at_3
value: 27.211000000000002
- type: mrr_at_5
value: 29.048000000000002
- type: ndcg_at_1
value: 23.469
- type: ndcg_at_10
value: 12.527
- type: ndcg_at_100
value: 17.624000000000002
- type: ndcg_at_1000
value: 28.534
- type: ndcg_at_3
value: 18.118000000000002
- type: ndcg_at_5
value: 15.520999999999999
- type: precision_at_1
value: 24.490000000000002
- type: precision_at_10
value: 9.592
- type: precision_at_100
value: 3.653
- type: precision_at_1000
value: 1.006
- type: precision_at_3
value: 17.687
- type: precision_at_5
value: 14.285999999999998
- type: recall_at_1
value: 1.66
- type: recall_at_10
value: 6.419
- type: recall_at_100
value: 20.97
- type: recall_at_1000
value: 55.001
- type: recall_at_3
value: 3.37
- type: recall_at_5
value: 4.855
- task:
type: Classification
dataset:
type: None
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 64.55300000000001
- type: ap
value: 11.51171190900715
- type: f1
value: 49.64107076870409
- task:
type: Classification
dataset:
type: None
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 52.857951329937755
- type: f1
value: 52.984245378050296
- task:
type: Clustering
dataset:
type: None
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 25.391338056888934
- task:
type: PairClassification
dataset:
type: None
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 83.24491863861239
- type: cos_sim_ap
value: 63.21977665263634
- type: cos_sim_f1
value: 60.90813587019961
- type: cos_sim_precision
value: 54.61586769939293
- type: cos_sim_recall
value: 68.83905013192611
- type: dot_accuracy
value: 83.24491863861239
- type: dot_ap
value: 63.21977665263634
- type: dot_f1
value: 60.90813587019961
- type: dot_precision
value: 54.61586769939293
- type: dot_recall
value: 68.83905013192611
- type: euclidean_accuracy
value: 83.24491863861239
- type: euclidean_ap
value: 63.21977665263634
- type: euclidean_f1
value: 60.90813587019961
- type: euclidean_precision
value: 54.61586769939293
- type: euclidean_recall
value: 68.83905013192611
- type: manhattan_accuracy
value: 83.05418131966383
- type: manhattan_ap
value: 62.73044800285885
- type: manhattan_f1
value: 60.47024246877296
- type: manhattan_precision
value: 56.42138939670932
- type: manhattan_recall
value: 65.14511873350924
- type: max_accuracy
value: 83.24491863861239
- type: max_ap
value: 63.21977665263634
- type: max_f1
value: 60.90813587019961
- task:
type: PairClassification
dataset:
type: None
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 85.89086816470679
- type: cos_sim_ap
value: 78.81106183704443
- type: cos_sim_f1
value: 71.13646466143133
- type: cos_sim_precision
value: 68.54654483152484
- type: cos_sim_recall
value: 73.92978133661842
- type: dot_accuracy
value: 85.89086816470679
- type: dot_ap
value: 78.81106438949705
- type: dot_f1
value: 71.13646466143133
- type: dot_precision
value: 68.54654483152484
- type: dot_recall
value: 73.92978133661842
- type: euclidean_accuracy
value: 85.89086816470679
- type: euclidean_ap
value: 78.81106117828325
- type: euclidean_f1
value: 71.13646466143133
- type: euclidean_precision
value: 68.54654483152484
- type: euclidean_recall
value: 73.92978133661842
- type: manhattan_accuracy
value: 85.89474909768309
- type: manhattan_ap
value: 78.67476153897563
- type: manhattan_f1
value: 70.78659868900219
- type: manhattan_precision
value: 67.15726920950802
- type: manhattan_recall
value: 74.83061287342161
- type: max_accuracy
value: 85.89474909768309
- type: max_ap
value: 78.81106438949705
- type: max_f1
value: 71.13646466143133