metadata
license: apache-2.0
pipeline_tag: sentence-similarity
inference: false
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
language: en
datasets:
- s2orc
- flax-sentence-embeddings/stackexchange_title_body_jsonl
- flax-sentence-embeddings/stackexchange_titlebody_best_voted_answer_jsonl
- flax-sentence-embeddings/stackexchange_title_best_voted_answer_jsonl
- >-
flax-sentence-embeddings/stackexchange_titlebody_best_and_down_voted_answer_jsonl
- sentence-transformers/reddit-title-body
- msmarco
- gooaq
- yahoo_answers_topics
- code_search_net
- search_qa
- eli5
- snli
- multi_nli
- wikihow
- natural_questions
- trivia_qa
- embedding-data/sentence-compression
- embedding-data/flickr30k-captions
- embedding-data/altlex
- embedding-data/simple-wiki
- embedding-data/QQP
- embedding-data/SPECTER
- embedding-data/PAQ_pairs
- embedding-data/WikiAnswers
- sentence-transformers/embedding-training-data
model-index:
- name: lodestone-base-4096-v1
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 69.7313432835821
- type: ap
value: 31.618259511417733
- type: f1
value: 63.30313825394228
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 86.89837499999999
- type: ap
value: 82.39500885672128
- type: f1
value: 86.87317947399657
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 44.05
- type: f1
value: 42.67624383248947
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.173999999999996
- type: map_at_10
value: 40.976
- type: map_at_100
value: 42.067
- type: map_at_1000
value: 42.075
- type: map_at_3
value: 35.917
- type: map_at_5
value: 38.656
- type: mrr_at_1
value: 26.814
- type: mrr_at_10
value: 41.252
- type: mrr_at_100
value: 42.337
- type: mrr_at_1000
value: 42.345
- type: mrr_at_3
value: 36.226
- type: mrr_at_5
value: 38.914
- type: ndcg_at_1
value: 26.173999999999996
- type: ndcg_at_10
value: 49.819
- type: ndcg_at_100
value: 54.403999999999996
- type: ndcg_at_1000
value: 54.59
- type: ndcg_at_3
value: 39.231
- type: ndcg_at_5
value: 44.189
- type: precision_at_1
value: 26.173999999999996
- type: precision_at_10
value: 7.838000000000001
- type: precision_at_100
value: 0.9820000000000001
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 16.287
- type: precision_at_5
value: 12.191
- type: recall_at_1
value: 26.173999999999996
- type: recall_at_10
value: 78.378
- type: recall_at_100
value: 98.222
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 48.862
- type: recall_at_5
value: 60.953
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 42.31689035788179
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 31.280245136660984
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 58.79109720839415
- type: mrr
value: 71.79615705931495
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 76.44918756608115
- type: cos_sim_spearman
value: 70.86607256286257
- type: euclidean_pearson
value: 74.12154678100815
- type: euclidean_spearman
value: 70.86607256286257
- type: manhattan_pearson
value: 74.0078626964417
- type: manhattan_spearman
value: 70.68353828321327
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 75.40584415584415
- type: f1
value: 74.29514617572676
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 37.41860080664014
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 29.319217023090705
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.595000000000002
- type: map_at_10
value: 36.556
- type: map_at_100
value: 37.984
- type: map_at_1000
value: 38.134
- type: map_at_3
value: 33.417
- type: map_at_5
value: 35.160000000000004
- type: mrr_at_1
value: 32.761
- type: mrr_at_10
value: 41.799
- type: mrr_at_100
value: 42.526
- type: mrr_at_1000
value: 42.582
- type: mrr_at_3
value: 39.39
- type: mrr_at_5
value: 40.727000000000004
- type: ndcg_at_1
value: 32.761
- type: ndcg_at_10
value: 42.549
- type: ndcg_at_100
value: 47.915
- type: ndcg_at_1000
value: 50.475
- type: ndcg_at_3
value: 37.93
- type: ndcg_at_5
value: 39.939
- type: precision_at_1
value: 32.761
- type: precision_at_10
value: 8.312
- type: precision_at_100
value: 1.403
- type: precision_at_1000
value: 0.197
- type: precision_at_3
value: 18.741
- type: precision_at_5
value: 13.447999999999999
- type: recall_at_1
value: 26.595000000000002
- type: recall_at_10
value: 54.332
- type: recall_at_100
value: 76.936
- type: recall_at_1000
value: 93.914
- type: recall_at_3
value: 40.666000000000004
- type: recall_at_5
value: 46.513
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.528000000000002
- type: map_at_10
value: 30.751
- type: map_at_100
value: 31.855
- type: map_at_1000
value: 31.972
- type: map_at_3
value: 28.465
- type: map_at_5
value: 29.738
- type: mrr_at_1
value: 28.662
- type: mrr_at_10
value: 35.912
- type: mrr_at_100
value: 36.726
- type: mrr_at_1000
value: 36.777
- type: mrr_at_3
value: 34.013
- type: mrr_at_5
value: 35.156
- type: ndcg_at_1
value: 28.662
- type: ndcg_at_10
value: 35.452
- type: ndcg_at_100
value: 40.1
- type: ndcg_at_1000
value: 42.323
- type: ndcg_at_3
value: 32.112
- type: ndcg_at_5
value: 33.638
- type: precision_at_1
value: 28.662
- type: precision_at_10
value: 6.688
- type: precision_at_100
value: 1.13
- type: precision_at_1000
value: 0.16
- type: precision_at_3
value: 15.562999999999999
- type: precision_at_5
value: 11.019
- type: recall_at_1
value: 22.528000000000002
- type: recall_at_10
value: 43.748
- type: recall_at_100
value: 64.235
- type: recall_at_1000
value: 78.609
- type: recall_at_3
value: 33.937
- type: recall_at_5
value: 38.234
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 33.117999999999995
- type: map_at_10
value: 44.339
- type: map_at_100
value: 45.367000000000004
- type: map_at_1000
value: 45.437
- type: map_at_3
value: 41.195
- type: map_at_5
value: 42.922
- type: mrr_at_1
value: 38.37
- type: mrr_at_10
value: 47.786
- type: mrr_at_100
value: 48.522
- type: mrr_at_1000
value: 48.567
- type: mrr_at_3
value: 45.371
- type: mrr_at_5
value: 46.857
- type: ndcg_at_1
value: 38.37
- type: ndcg_at_10
value: 50.019999999999996
- type: ndcg_at_100
value: 54.36299999999999
- type: ndcg_at_1000
value: 55.897
- type: ndcg_at_3
value: 44.733000000000004
- type: ndcg_at_5
value: 47.292
- type: precision_at_1
value: 38.37
- type: precision_at_10
value: 8.288
- type: precision_at_100
value: 1.139
- type: precision_at_1000
value: 0.132
- type: precision_at_3
value: 20.293
- type: precision_at_5
value: 14.107
- type: recall_at_1
value: 33.117999999999995
- type: recall_at_10
value: 63.451
- type: recall_at_100
value: 82.767
- type: recall_at_1000
value: 93.786
- type: recall_at_3
value: 48.964999999999996
- type: recall_at_5
value: 55.358
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.028000000000002
- type: map_at_10
value: 23.186999999999998
- type: map_at_100
value: 24.236
- type: map_at_1000
value: 24.337
- type: map_at_3
value: 20.816000000000003
- type: map_at_5
value: 22.311
- type: mrr_at_1
value: 17.514
- type: mrr_at_10
value: 24.84
- type: mrr_at_100
value: 25.838
- type: mrr_at_1000
value: 25.924999999999997
- type: mrr_at_3
value: 22.542
- type: mrr_at_5
value: 24.04
- type: ndcg_at_1
value: 17.514
- type: ndcg_at_10
value: 27.391
- type: ndcg_at_100
value: 32.684999999999995
- type: ndcg_at_1000
value: 35.367
- type: ndcg_at_3
value: 22.820999999999998
- type: ndcg_at_5
value: 25.380999999999997
- type: precision_at_1
value: 17.514
- type: precision_at_10
value: 4.463
- type: precision_at_100
value: 0.745
- type: precision_at_1000
value: 0.101
- type: precision_at_3
value: 10.019
- type: precision_at_5
value: 7.457999999999999
- type: recall_at_1
value: 16.028000000000002
- type: recall_at_10
value: 38.81
- type: recall_at_100
value: 63.295
- type: recall_at_1000
value: 83.762
- type: recall_at_3
value: 26.604
- type: recall_at_5
value: 32.727000000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 11.962
- type: map_at_10
value: 17.218
- type: map_at_100
value: 18.321
- type: map_at_1000
value: 18.455
- type: map_at_3
value: 15.287999999999998
- type: map_at_5
value: 16.417
- type: mrr_at_1
value: 14.677000000000001
- type: mrr_at_10
value: 20.381
- type: mrr_at_100
value: 21.471999999999998
- type: mrr_at_1000
value: 21.566
- type: mrr_at_3
value: 18.448999999999998
- type: mrr_at_5
value: 19.587
- type: ndcg_at_1
value: 14.677000000000001
- type: ndcg_at_10
value: 20.86
- type: ndcg_at_100
value: 26.519
- type: ndcg_at_1000
value: 30.020000000000003
- type: ndcg_at_3
value: 17.208000000000002
- type: ndcg_at_5
value: 19.037000000000003
- type: precision_at_1
value: 14.677000000000001
- type: precision_at_10
value: 3.856
- type: precision_at_100
value: 0.7889999999999999
- type: precision_at_1000
value: 0.124
- type: precision_at_3
value: 8.043
- type: precision_at_5
value: 6.069999999999999
- type: recall_at_1
value: 11.962
- type: recall_at_10
value: 28.994999999999997
- type: recall_at_100
value: 54.071999999999996
- type: recall_at_1000
value: 79.309
- type: recall_at_3
value: 19.134999999999998
- type: recall_at_5
value: 23.727999999999998
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.764
- type: map_at_10
value: 31.744
- type: map_at_100
value: 33.037
- type: map_at_1000
value: 33.156
- type: map_at_3
value: 29.015
- type: map_at_5
value: 30.434
- type: mrr_at_1
value: 28.296
- type: mrr_at_10
value: 37.03
- type: mrr_at_100
value: 37.902
- type: mrr_at_1000
value: 37.966
- type: mrr_at_3
value: 34.568
- type: mrr_at_5
value: 35.786
- type: ndcg_at_1
value: 28.296
- type: ndcg_at_10
value: 37.289
- type: ndcg_at_100
value: 42.787
- type: ndcg_at_1000
value: 45.382
- type: ndcg_at_3
value: 32.598
- type: ndcg_at_5
value: 34.521
- type: precision_at_1
value: 28.296
- type: precision_at_10
value: 6.901
- type: precision_at_100
value: 1.135
- type: precision_at_1000
value: 0.152
- type: precision_at_3
value: 15.367
- type: precision_at_5
value: 11.03
- type: recall_at_1
value: 22.764
- type: recall_at_10
value: 48.807
- type: recall_at_100
value: 71.859
- type: recall_at_1000
value: 89.606
- type: recall_at_3
value: 35.594
- type: recall_at_5
value: 40.541
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.742
- type: map_at_10
value: 27.741
- type: map_at_100
value: 29.323
- type: map_at_1000
value: 29.438
- type: map_at_3
value: 25.217
- type: map_at_5
value: 26.583000000000002
- type: mrr_at_1
value: 24.657999999999998
- type: mrr_at_10
value: 32.407000000000004
- type: mrr_at_100
value: 33.631
- type: mrr_at_1000
value: 33.686
- type: mrr_at_3
value: 30.194
- type: mrr_at_5
value: 31.444
- type: ndcg_at_1
value: 24.657999999999998
- type: ndcg_at_10
value: 32.614
- type: ndcg_at_100
value: 39.61
- type: ndcg_at_1000
value: 42.114000000000004
- type: ndcg_at_3
value: 28.516000000000002
- type: ndcg_at_5
value: 30.274
- type: precision_at_1
value: 24.657999999999998
- type: precision_at_10
value: 6.176
- type: precision_at_100
value: 1.1400000000000001
- type: precision_at_1000
value: 0.155
- type: precision_at_3
value: 13.927
- type: precision_at_5
value: 9.954
- type: recall_at_1
value: 19.742
- type: recall_at_10
value: 42.427
- type: recall_at_100
value: 72.687
- type: recall_at_1000
value: 89.89
- type: recall_at_3
value: 30.781
- type: recall_at_5
value: 35.606
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.72608333333333
- type: map_at_10
value: 27.165333333333336
- type: map_at_100
value: 28.292499999999997
- type: map_at_1000
value: 28.416333333333327
- type: map_at_3
value: 24.783833333333334
- type: map_at_5
value: 26.101750000000003
- type: mrr_at_1
value: 23.721500000000002
- type: mrr_at_10
value: 30.853333333333328
- type: mrr_at_100
value: 31.741750000000003
- type: mrr_at_1000
value: 31.812999999999995
- type: mrr_at_3
value: 28.732249999999997
- type: mrr_at_5
value: 29.945166666666665
- type: ndcg_at_1
value: 23.721500000000002
- type: ndcg_at_10
value: 31.74883333333333
- type: ndcg_at_100
value: 36.883583333333334
- type: ndcg_at_1000
value: 39.6145
- type: ndcg_at_3
value: 27.639583333333334
- type: ndcg_at_5
value: 29.543666666666667
- type: precision_at_1
value: 23.721500000000002
- type: precision_at_10
value: 5.709083333333333
- type: precision_at_100
value: 0.9859166666666666
- type: precision_at_1000
value: 0.1413333333333333
- type: precision_at_3
value: 12.85683333333333
- type: precision_at_5
value: 9.258166666666668
- type: recall_at_1
value: 19.72608333333333
- type: recall_at_10
value: 41.73583333333334
- type: recall_at_100
value: 64.66566666666668
- type: recall_at_1000
value: 84.09833333333336
- type: recall_at_3
value: 30.223083333333328
- type: recall_at_5
value: 35.153083333333335
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.582
- type: map_at_10
value: 22.803
- type: map_at_100
value: 23.503
- type: map_at_1000
value: 23.599999999999998
- type: map_at_3
value: 21.375
- type: map_at_5
value: 22.052
- type: mrr_at_1
value: 20.399
- type: mrr_at_10
value: 25.369999999999997
- type: mrr_at_100
value: 26.016000000000002
- type: mrr_at_1000
value: 26.090999999999998
- type: mrr_at_3
value: 23.952
- type: mrr_at_5
value: 24.619
- type: ndcg_at_1
value: 20.399
- type: ndcg_at_10
value: 25.964
- type: ndcg_at_100
value: 29.607
- type: ndcg_at_1000
value: 32.349
- type: ndcg_at_3
value: 23.177
- type: ndcg_at_5
value: 24.276
- type: precision_at_1
value: 20.399
- type: precision_at_10
value: 4.018
- type: precision_at_100
value: 0.629
- type: precision_at_1000
value: 0.093
- type: precision_at_3
value: 9.969
- type: precision_at_5
value: 6.748
- type: recall_at_1
value: 17.582
- type: recall_at_10
value: 33.35
- type: recall_at_100
value: 50.219
- type: recall_at_1000
value: 71.06099999999999
- type: recall_at_3
value: 25.619999999999997
- type: recall_at_5
value: 28.291
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 11.071
- type: map_at_10
value: 16.201999999999998
- type: map_at_100
value: 17.112
- type: map_at_1000
value: 17.238
- type: map_at_3
value: 14.508
- type: map_at_5
value: 15.440999999999999
- type: mrr_at_1
value: 13.833
- type: mrr_at_10
value: 19.235
- type: mrr_at_100
value: 20.108999999999998
- type: mrr_at_1000
value: 20.196
- type: mrr_at_3
value: 17.515
- type: mrr_at_5
value: 18.505
- type: ndcg_at_1
value: 13.833
- type: ndcg_at_10
value: 19.643
- type: ndcg_at_100
value: 24.298000000000002
- type: ndcg_at_1000
value: 27.614
- type: ndcg_at_3
value: 16.528000000000002
- type: ndcg_at_5
value: 17.991
- type: precision_at_1
value: 13.833
- type: precision_at_10
value: 3.6990000000000003
- type: precision_at_100
value: 0.713
- type: precision_at_1000
value: 0.116
- type: precision_at_3
value: 7.9030000000000005
- type: precision_at_5
value: 5.891
- type: recall_at_1
value: 11.071
- type: recall_at_10
value: 27.019
- type: recall_at_100
value: 48.404
- type: recall_at_1000
value: 72.641
- type: recall_at_3
value: 18.336
- type: recall_at_5
value: 21.991
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 18.573
- type: map_at_10
value: 25.008999999999997
- type: map_at_100
value: 26.015
- type: map_at_1000
value: 26.137
- type: map_at_3
value: 22.798
- type: map_at_5
value: 24.092
- type: mrr_at_1
value: 22.108
- type: mrr_at_10
value: 28.646
- type: mrr_at_100
value: 29.477999999999998
- type: mrr_at_1000
value: 29.57
- type: mrr_at_3
value: 26.415
- type: mrr_at_5
value: 27.693
- type: ndcg_at_1
value: 22.108
- type: ndcg_at_10
value: 29.42
- type: ndcg_at_100
value: 34.385
- type: ndcg_at_1000
value: 37.572
- type: ndcg_at_3
value: 25.274
- type: ndcg_at_5
value: 27.315
- type: precision_at_1
value: 22.108
- type: precision_at_10
value: 5.093
- type: precision_at_100
value: 0.859
- type: precision_at_1000
value: 0.124
- type: precision_at_3
value: 11.474
- type: precision_at_5
value: 8.321000000000002
- type: recall_at_1
value: 18.573
- type: recall_at_10
value: 39.433
- type: recall_at_100
value: 61.597
- type: recall_at_1000
value: 84.69
- type: recall_at_3
value: 27.849
- type: recall_at_5
value: 33.202999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.807
- type: map_at_10
value: 30.014000000000003
- type: map_at_100
value: 31.422
- type: map_at_1000
value: 31.652
- type: map_at_3
value: 27.447
- type: map_at_5
value: 28.711
- type: mrr_at_1
value: 27.668
- type: mrr_at_10
value: 34.489
- type: mrr_at_100
value: 35.453
- type: mrr_at_1000
value: 35.526
- type: mrr_at_3
value: 32.477000000000004
- type: mrr_at_5
value: 33.603
- type: ndcg_at_1
value: 27.668
- type: ndcg_at_10
value: 34.983
- type: ndcg_at_100
value: 40.535
- type: ndcg_at_1000
value: 43.747
- type: ndcg_at_3
value: 31.026999999999997
- type: ndcg_at_5
value: 32.608
- type: precision_at_1
value: 27.668
- type: precision_at_10
value: 6.837999999999999
- type: precision_at_100
value: 1.411
- type: precision_at_1000
value: 0.23600000000000002
- type: precision_at_3
value: 14.295
- type: precision_at_5
value: 10.435
- type: recall_at_1
value: 22.807
- type: recall_at_10
value: 43.545
- type: recall_at_100
value: 69.39800000000001
- type: recall_at_1000
value: 90.706
- type: recall_at_3
value: 32.183
- type: recall_at_5
value: 36.563
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 13.943
- type: map_at_10
value: 20.419999999999998
- type: map_at_100
value: 21.335
- type: map_at_1000
value: 21.44
- type: map_at_3
value: 17.865000000000002
- type: map_at_5
value: 19.36
- type: mrr_at_1
value: 15.712000000000002
- type: mrr_at_10
value: 22.345000000000002
- type: mrr_at_100
value: 23.227999999999998
- type: mrr_at_1000
value: 23.304
- type: mrr_at_3
value: 19.901
- type: mrr_at_5
value: 21.325
- type: ndcg_at_1
value: 15.712000000000002
- type: ndcg_at_10
value: 24.801000000000002
- type: ndcg_at_100
value: 29.799
- type: ndcg_at_1000
value: 32.513999999999996
- type: ndcg_at_3
value: 19.750999999999998
- type: ndcg_at_5
value: 22.252
- type: precision_at_1
value: 15.712000000000002
- type: precision_at_10
value: 4.1770000000000005
- type: precision_at_100
value: 0.738
- type: precision_at_1000
value: 0.106
- type: precision_at_3
value: 8.688
- type: precision_at_5
value: 6.617000000000001
- type: recall_at_1
value: 13.943
- type: recall_at_10
value: 36.913000000000004
- type: recall_at_100
value: 60.519
- type: recall_at_1000
value: 81.206
- type: recall_at_3
value: 23.006999999999998
- type: recall_at_5
value: 29.082
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.468
- type: map_at_10
value: 16.029
- type: map_at_100
value: 17.693
- type: map_at_1000
value: 17.886
- type: map_at_3
value: 13.15
- type: map_at_5
value: 14.568
- type: mrr_at_1
value: 21.173000000000002
- type: mrr_at_10
value: 31.028
- type: mrr_at_100
value: 32.061
- type: mrr_at_1000
value: 32.119
- type: mrr_at_3
value: 27.534999999999997
- type: mrr_at_5
value: 29.431
- type: ndcg_at_1
value: 21.173000000000002
- type: ndcg_at_10
value: 23.224
- type: ndcg_at_100
value: 30.225
- type: ndcg_at_1000
value: 33.961000000000006
- type: ndcg_at_3
value: 18.174
- type: ndcg_at_5
value: 19.897000000000002
- type: precision_at_1
value: 21.173000000000002
- type: precision_at_10
value: 7.4719999999999995
- type: precision_at_100
value: 1.5010000000000001
- type: precision_at_1000
value: 0.219
- type: precision_at_3
value: 13.312
- type: precision_at_5
value: 10.619
- type: recall_at_1
value: 9.468
- type: recall_at_10
value: 28.823
- type: recall_at_100
value: 53.26499999999999
- type: recall_at_1000
value: 74.536
- type: recall_at_3
value: 16.672
- type: recall_at_5
value: 21.302
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 6.343
- type: map_at_10
value: 12.717
- type: map_at_100
value: 16.48
- type: map_at_1000
value: 17.381
- type: map_at_3
value: 9.568999999999999
- type: map_at_5
value: 11.125
- type: mrr_at_1
value: 48.75
- type: mrr_at_10
value: 58.425000000000004
- type: mrr_at_100
value: 59.075
- type: mrr_at_1000
value: 59.095
- type: mrr_at_3
value: 56.291999999999994
- type: mrr_at_5
value: 57.679
- type: ndcg_at_1
value: 37.875
- type: ndcg_at_10
value: 27.77
- type: ndcg_at_100
value: 30.288999999999998
- type: ndcg_at_1000
value: 36.187999999999995
- type: ndcg_at_3
value: 31.385999999999996
- type: ndcg_at_5
value: 29.923
- type: precision_at_1
value: 48.75
- type: precision_at_10
value: 22.375
- type: precision_at_100
value: 6.3420000000000005
- type: precision_at_1000
value: 1.4489999999999998
- type: precision_at_3
value: 35.5
- type: precision_at_5
value: 30.55
- type: recall_at_1
value: 6.343
- type: recall_at_10
value: 16.936
- type: recall_at_100
value: 35.955999999999996
- type: recall_at_1000
value: 55.787
- type: recall_at_3
value: 10.771
- type: recall_at_5
value: 13.669999999999998
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 41.99
- type: f1
value: 36.823402174564954
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 40.088
- type: map_at_10
value: 52.69200000000001
- type: map_at_100
value: 53.296
- type: map_at_1000
value: 53.325
- type: map_at_3
value: 49.905
- type: map_at_5
value: 51.617000000000004
- type: mrr_at_1
value: 43.009
- type: mrr_at_10
value: 56.203
- type: mrr_at_100
value: 56.75
- type: mrr_at_1000
value: 56.769000000000005
- type: mrr_at_3
value: 53.400000000000006
- type: mrr_at_5
value: 55.163
- type: ndcg_at_1
value: 43.009
- type: ndcg_at_10
value: 59.39
- type: ndcg_at_100
value: 62.129999999999995
- type: ndcg_at_1000
value: 62.793
- type: ndcg_at_3
value: 53.878
- type: ndcg_at_5
value: 56.887
- type: precision_at_1
value: 43.009
- type: precision_at_10
value: 8.366
- type: precision_at_100
value: 0.983
- type: precision_at_1000
value: 0.105
- type: precision_at_3
value: 22.377
- type: precision_at_5
value: 15.035000000000002
- type: recall_at_1
value: 40.088
- type: recall_at_10
value: 76.68700000000001
- type: recall_at_100
value: 88.91
- type: recall_at_1000
value: 93.782
- type: recall_at_3
value: 61.809999999999995
- type: recall_at_5
value: 69.131
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 10.817
- type: map_at_10
value: 18.9
- type: map_at_100
value: 20.448
- type: map_at_1000
value: 20.660999999999998
- type: map_at_3
value: 15.979
- type: map_at_5
value: 17.415
- type: mrr_at_1
value: 23.148
- type: mrr_at_10
value: 31.208000000000002
- type: mrr_at_100
value: 32.167
- type: mrr_at_1000
value: 32.242
- type: mrr_at_3
value: 28.498
- type: mrr_at_5
value: 29.964000000000002
- type: ndcg_at_1
value: 23.148
- type: ndcg_at_10
value: 25.325999999999997
- type: ndcg_at_100
value: 31.927
- type: ndcg_at_1000
value: 36.081
- type: ndcg_at_3
value: 21.647
- type: ndcg_at_5
value: 22.762999999999998
- type: precision_at_1
value: 23.148
- type: precision_at_10
value: 7.546
- type: precision_at_100
value: 1.415
- type: precision_at_1000
value: 0.216
- type: precision_at_3
value: 14.969
- type: precision_at_5
value: 11.327
- type: recall_at_1
value: 10.817
- type: recall_at_10
value: 32.164
- type: recall_at_100
value: 57.655
- type: recall_at_1000
value: 82.797
- type: recall_at_3
value: 19.709
- type: recall_at_5
value: 24.333
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.380999999999997
- type: map_at_10
value: 33.14
- type: map_at_100
value: 33.948
- type: map_at_1000
value: 34.028000000000006
- type: map_at_3
value: 31.019999999999996
- type: map_at_5
value: 32.23
- type: mrr_at_1
value: 50.763000000000005
- type: mrr_at_10
value: 57.899
- type: mrr_at_100
value: 58.426
- type: mrr_at_1000
value: 58.457
- type: mrr_at_3
value: 56.093
- type: mrr_at_5
value: 57.116
- type: ndcg_at_1
value: 50.763000000000005
- type: ndcg_at_10
value: 41.656
- type: ndcg_at_100
value: 45.079
- type: ndcg_at_1000
value: 46.916999999999994
- type: ndcg_at_3
value: 37.834
- type: ndcg_at_5
value: 39.732
- type: precision_at_1
value: 50.763000000000005
- type: precision_at_10
value: 8.648
- type: precision_at_100
value: 1.135
- type: precision_at_1000
value: 0.13799999999999998
- type: precision_at_3
value: 23.105999999999998
- type: precision_at_5
value: 15.363
- type: recall_at_1
value: 25.380999999999997
- type: recall_at_10
value: 43.241
- type: recall_at_100
value: 56.745000000000005
- type: recall_at_1000
value: 69.048
- type: recall_at_3
value: 34.659
- type: recall_at_5
value: 38.406
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 79.544
- type: ap
value: 73.82920133396664
- type: f1
value: 79.51048124883265
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 11.174000000000001
- type: map_at_10
value: 19.451999999999998
- type: map_at_100
value: 20.612
- type: map_at_1000
value: 20.703
- type: map_at_3
value: 16.444
- type: map_at_5
value: 18.083
- type: mrr_at_1
value: 11.447000000000001
- type: mrr_at_10
value: 19.808
- type: mrr_at_100
value: 20.958
- type: mrr_at_1000
value: 21.041999999999998
- type: mrr_at_3
value: 16.791
- type: mrr_at_5
value: 18.459
- type: ndcg_at_1
value: 11.447000000000001
- type: ndcg_at_10
value: 24.556
- type: ndcg_at_100
value: 30.637999999999998
- type: ndcg_at_1000
value: 33.14
- type: ndcg_at_3
value: 18.325
- type: ndcg_at_5
value: 21.278
- type: precision_at_1
value: 11.447000000000001
- type: precision_at_10
value: 4.215
- type: precision_at_100
value: 0.732
- type: precision_at_1000
value: 0.095
- type: precision_at_3
value: 8.052
- type: precision_at_5
value: 6.318
- type: recall_at_1
value: 11.174000000000001
- type: recall_at_10
value: 40.543
- type: recall_at_100
value: 69.699
- type: recall_at_1000
value: 89.403
- type: recall_at_3
value: 23.442
- type: recall_at_5
value: 30.536
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 89.6671226630187
- type: f1
value: 89.57660424361246
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 60.284997720018254
- type: f1
value: 40.30637400152823
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 63.33557498318763
- type: f1
value: 60.24039910680179
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 72.37390719569603
- type: f1
value: 72.33097333477316
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 34.68158939060552
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 30.340061711905236
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.01814326295803
- type: mrr
value: 33.20555240055367
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.3910000000000005
- type: map_at_10
value: 7.7219999999999995
- type: map_at_100
value: 10.286
- type: map_at_1000
value: 11.668000000000001
- type: map_at_3
value: 5.552
- type: map_at_5
value: 6.468
- type: mrr_at_1
value: 34.365
- type: mrr_at_10
value: 42.555
- type: mrr_at_100
value: 43.295
- type: mrr_at_1000
value: 43.357
- type: mrr_at_3
value: 40.299
- type: mrr_at_5
value: 41.182
- type: ndcg_at_1
value: 31.424000000000003
- type: ndcg_at_10
value: 24.758
- type: ndcg_at_100
value: 23.677999999999997
- type: ndcg_at_1000
value: 33.377
- type: ndcg_at_3
value: 28.302
- type: ndcg_at_5
value: 26.342
- type: precision_at_1
value: 33.437
- type: precision_at_10
value: 19.256999999999998
- type: precision_at_100
value: 6.662999999999999
- type: precision_at_1000
value: 1.9900000000000002
- type: precision_at_3
value: 27.761000000000003
- type: precision_at_5
value: 23.715
- type: recall_at_1
value: 3.3910000000000005
- type: recall_at_10
value: 11.068
- type: recall_at_100
value: 25.878
- type: recall_at_1000
value: 60.19
- type: recall_at_3
value: 6.1690000000000005
- type: recall_at_5
value: 7.767
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 15.168000000000001
- type: map_at_10
value: 26.177
- type: map_at_100
value: 27.564
- type: map_at_1000
value: 27.628999999999998
- type: map_at_3
value: 22.03
- type: map_at_5
value: 24.276
- type: mrr_at_1
value: 17.439
- type: mrr_at_10
value: 28.205000000000002
- type: mrr_at_100
value: 29.357
- type: mrr_at_1000
value: 29.408
- type: mrr_at_3
value: 24.377
- type: mrr_at_5
value: 26.540000000000003
- type: ndcg_at_1
value: 17.41
- type: ndcg_at_10
value: 32.936
- type: ndcg_at_100
value: 39.196999999999996
- type: ndcg_at_1000
value: 40.892
- type: ndcg_at_3
value: 24.721
- type: ndcg_at_5
value: 28.615000000000002
- type: precision_at_1
value: 17.41
- type: precision_at_10
value: 6.199000000000001
- type: precision_at_100
value: 0.9690000000000001
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 11.790000000000001
- type: precision_at_5
value: 9.264
- type: recall_at_1
value: 15.168000000000001
- type: recall_at_10
value: 51.914
- type: recall_at_100
value: 79.804
- type: recall_at_1000
value: 92.75999999999999
- type: recall_at_3
value: 30.212
- type: recall_at_5
value: 39.204
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 67.306
- type: map_at_10
value: 80.634
- type: map_at_100
value: 81.349
- type: map_at_1000
value: 81.37299999999999
- type: map_at_3
value: 77.691
- type: map_at_5
value: 79.512
- type: mrr_at_1
value: 77.56
- type: mrr_at_10
value: 84.177
- type: mrr_at_100
value: 84.35000000000001
- type: mrr_at_1000
value: 84.353
- type: mrr_at_3
value: 83.003
- type: mrr_at_5
value: 83.799
- type: ndcg_at_1
value: 77.58
- type: ndcg_at_10
value: 84.782
- type: ndcg_at_100
value: 86.443
- type: ndcg_at_1000
value: 86.654
- type: ndcg_at_3
value: 81.67
- type: ndcg_at_5
value: 83.356
- type: precision_at_1
value: 77.58
- type: precision_at_10
value: 12.875
- type: precision_at_100
value: 1.503
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 35.63
- type: precision_at_5
value: 23.483999999999998
- type: recall_at_1
value: 67.306
- type: recall_at_10
value: 92.64
- type: recall_at_100
value: 98.681
- type: recall_at_1000
value: 99.79
- type: recall_at_3
value: 83.682
- type: recall_at_5
value: 88.424
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 50.76319866126382
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 55.024711941648995
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.9379999999999997
- type: map_at_10
value: 8.817
- type: map_at_100
value: 10.546999999999999
- type: map_at_1000
value: 10.852
- type: map_at_3
value: 6.351999999999999
- type: map_at_5
value: 7.453
- type: mrr_at_1
value: 19.400000000000002
- type: mrr_at_10
value: 27.371000000000002
- type: mrr_at_100
value: 28.671999999999997
- type: mrr_at_1000
value: 28.747
- type: mrr_at_3
value: 24.583
- type: mrr_at_5
value: 26.143
- type: ndcg_at_1
value: 19.400000000000002
- type: ndcg_at_10
value: 15.264
- type: ndcg_at_100
value: 22.63
- type: ndcg_at_1000
value: 28.559
- type: ndcg_at_3
value: 14.424999999999999
- type: ndcg_at_5
value: 12.520000000000001
- type: precision_at_1
value: 19.400000000000002
- type: precision_at_10
value: 7.8100000000000005
- type: precision_at_100
value: 1.854
- type: precision_at_1000
value: 0.329
- type: precision_at_3
value: 13.100000000000001
- type: precision_at_5
value: 10.68
- type: recall_at_1
value: 3.9379999999999997
- type: recall_at_10
value: 15.903
- type: recall_at_100
value: 37.645
- type: recall_at_1000
value: 66.86
- type: recall_at_3
value: 7.993
- type: recall_at_5
value: 10.885
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 80.12689060151425
- type: cos_sim_spearman
value: 70.46515535094771
- type: euclidean_pearson
value: 77.17160003557223
- type: euclidean_spearman
value: 70.4651757047438
- type: manhattan_pearson
value: 77.18129609281937
- type: manhattan_spearman
value: 70.46610403752913
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 70.451157033355
- type: cos_sim_spearman
value: 63.99899601697852
- type: euclidean_pearson
value: 67.46985359967678
- type: euclidean_spearman
value: 64.00001637764805
- type: manhattan_pearson
value: 67.56534741780037
- type: manhattan_spearman
value: 64.06533893575366
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 77.65086614464292
- type: cos_sim_spearman
value: 78.20169706921848
- type: euclidean_pearson
value: 77.77758172155283
- type: euclidean_spearman
value: 78.20169706921848
- type: manhattan_pearson
value: 77.75077884860052
- type: manhattan_spearman
value: 78.16875216484164
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 76.26381598259717
- type: cos_sim_spearman
value: 70.78377709313477
- type: euclidean_pearson
value: 74.82646556532096
- type: euclidean_spearman
value: 70.78377658155212
- type: manhattan_pearson
value: 74.81784766108225
- type: manhattan_spearman
value: 70.79351454692176
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 79.00532026789739
- type: cos_sim_spearman
value: 80.02708383244838
- type: euclidean_pearson
value: 79.48345422610525
- type: euclidean_spearman
value: 80.02708383244838
- type: manhattan_pearson
value: 79.44519739854803
- type: manhattan_spearman
value: 79.98344094559687
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 77.32783048164805
- type: cos_sim_spearman
value: 78.79729961288045
- type: euclidean_pearson
value: 78.72111945793154
- type: euclidean_spearman
value: 78.79729904606872
- type: manhattan_pearson
value: 78.72464311117116
- type: manhattan_spearman
value: 78.822591248334
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 82.04318630630854
- type: cos_sim_spearman
value: 83.87886389259836
- type: euclidean_pearson
value: 83.40385877895086
- type: euclidean_spearman
value: 83.87886389259836
- type: manhattan_pearson
value: 83.46337128901547
- type: manhattan_spearman
value: 83.9723106941644
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 63.003511169944595
- type: cos_sim_spearman
value: 64.39318805580227
- type: euclidean_pearson
value: 65.4797990735967
- type: euclidean_spearman
value: 64.39318805580227
- type: manhattan_pearson
value: 65.44604544280844
- type: manhattan_spearman
value: 64.38742899984233
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 76.63101237585029
- type: cos_sim_spearman
value: 75.57446967644269
- type: euclidean_pearson
value: 76.93491768734478
- type: euclidean_spearman
value: 75.57446967644269
- type: manhattan_pearson
value: 76.92187567800636
- type: manhattan_spearman
value: 75.57239337194585
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 78.5376604868993
- type: mrr
value: 92.94422897364073
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 38.872
- type: map_at_10
value: 50.417
- type: map_at_100
value: 51.202000000000005
- type: map_at_1000
value: 51.25999999999999
- type: map_at_3
value: 47.02
- type: map_at_5
value: 49.326
- type: mrr_at_1
value: 41
- type: mrr_at_10
value: 51.674
- type: mrr_at_100
value: 52.32599999999999
- type: mrr_at_1000
value: 52.376999999999995
- type: mrr_at_3
value: 48.778
- type: mrr_at_5
value: 50.744
- type: ndcg_at_1
value: 41
- type: ndcg_at_10
value: 56.027
- type: ndcg_at_100
value: 59.362
- type: ndcg_at_1000
value: 60.839
- type: ndcg_at_3
value: 50.019999999999996
- type: ndcg_at_5
value: 53.644999999999996
- type: precision_at_1
value: 41
- type: precision_at_10
value: 8.1
- type: precision_at_100
value: 0.987
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 20.444000000000003
- type: precision_at_5
value: 14.466999999999999
- type: recall_at_1
value: 38.872
- type: recall_at_10
value: 71.906
- type: recall_at_100
value: 86.367
- type: recall_at_1000
value: 98
- type: recall_at_3
value: 56.206
- type: recall_at_5
value: 65.05
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.7039603960396
- type: cos_sim_ap
value: 90.40809844250262
- type: cos_sim_f1
value: 84.53181583031557
- type: cos_sim_precision
value: 87.56698821007502
- type: cos_sim_recall
value: 81.69999999999999
- type: dot_accuracy
value: 99.7039603960396
- type: dot_ap
value: 90.40809844250262
- type: dot_f1
value: 84.53181583031557
- type: dot_precision
value: 87.56698821007502
- type: dot_recall
value: 81.69999999999999
- type: euclidean_accuracy
value: 99.7039603960396
- type: euclidean_ap
value: 90.4080982863383
- type: euclidean_f1
value: 84.53181583031557
- type: euclidean_precision
value: 87.56698821007502
- type: euclidean_recall
value: 81.69999999999999
- type: manhattan_accuracy
value: 99.7
- type: manhattan_ap
value: 90.39771161966652
- type: manhattan_f1
value: 84.32989690721648
- type: manhattan_precision
value: 87.02127659574468
- type: manhattan_recall
value: 81.8
- type: max_accuracy
value: 99.7039603960396
- type: max_ap
value: 90.40809844250262
- type: max_f1
value: 84.53181583031557
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 59.663210666678715
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 32.107791216468776
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 46.440691925067604
- type: mrr
value: 47.03390257618199
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.067177519784074
- type: cos_sim_spearman
value: 31.234728424648967
- type: dot_pearson
value: 31.06717083018107
- type: dot_spearman
value: 31.234728424648967
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.136
- type: map_at_10
value: 0.767
- type: map_at_100
value: 3.3689999999999998
- type: map_at_1000
value: 8.613999999999999
- type: map_at_3
value: 0.369
- type: map_at_5
value: 0.514
- type: mrr_at_1
value: 48
- type: mrr_at_10
value: 63.908
- type: mrr_at_100
value: 64.615
- type: mrr_at_1000
value: 64.615
- type: mrr_at_3
value: 62
- type: mrr_at_5
value: 63.4
- type: ndcg_at_1
value: 44
- type: ndcg_at_10
value: 38.579
- type: ndcg_at_100
value: 26.409
- type: ndcg_at_1000
value: 26.858999999999998
- type: ndcg_at_3
value: 47.134
- type: ndcg_at_5
value: 43.287
- type: precision_at_1
value: 48
- type: precision_at_10
value: 40.400000000000006
- type: precision_at_100
value: 26.640000000000004
- type: precision_at_1000
value: 12.04
- type: precision_at_3
value: 52.666999999999994
- type: precision_at_5
value: 46.800000000000004
- type: recall_at_1
value: 0.136
- type: recall_at_10
value: 1.0070000000000001
- type: recall_at_100
value: 6.318
- type: recall_at_1000
value: 26.522000000000002
- type: recall_at_3
value: 0.41700000000000004
- type: recall_at_5
value: 0.606
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.9949999999999999
- type: map_at_10
value: 8.304
- type: map_at_100
value: 13.644
- type: map_at_1000
value: 15.43
- type: map_at_3
value: 4.788
- type: map_at_5
value: 6.22
- type: mrr_at_1
value: 22.448999999999998
- type: mrr_at_10
value: 37.658
- type: mrr_at_100
value: 38.491
- type: mrr_at_1000
value: 38.503
- type: mrr_at_3
value: 32.312999999999995
- type: mrr_at_5
value: 35.68
- type: ndcg_at_1
value: 21.429000000000002
- type: ndcg_at_10
value: 18.995
- type: ndcg_at_100
value: 32.029999999999994
- type: ndcg_at_1000
value: 44.852
- type: ndcg_at_3
value: 19.464000000000002
- type: ndcg_at_5
value: 19.172
- type: precision_at_1
value: 22.448999999999998
- type: precision_at_10
value: 17.143
- type: precision_at_100
value: 6.877999999999999
- type: precision_at_1000
value: 1.524
- type: precision_at_3
value: 21.769
- type: precision_at_5
value: 20
- type: recall_at_1
value: 1.9949999999999999
- type: recall_at_10
value: 13.395999999999999
- type: recall_at_100
value: 44.348
- type: recall_at_1000
value: 82.622
- type: recall_at_3
value: 5.896
- type: recall_at_5
value: 8.554
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 67.9394
- type: ap
value: 12.943337263423334
- type: f1
value: 52.28243093094156
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 56.414827391058296
- type: f1
value: 56.666412409573105
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 47.009746255495465
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 84.02574953805807
- type: cos_sim_ap
value: 67.66599910763128
- type: cos_sim_f1
value: 63.491277990844985
- type: cos_sim_precision
value: 59.77172140694154
- type: cos_sim_recall
value: 67.70448548812665
- type: dot_accuracy
value: 84.02574953805807
- type: dot_ap
value: 67.66600090945406
- type: dot_f1
value: 63.491277990844985
- type: dot_precision
value: 59.77172140694154
- type: dot_recall
value: 67.70448548812665
- type: euclidean_accuracy
value: 84.02574953805807
- type: euclidean_ap
value: 67.6659842364448
- type: euclidean_f1
value: 63.491277990844985
- type: euclidean_precision
value: 59.77172140694154
- type: euclidean_recall
value: 67.70448548812665
- type: manhattan_accuracy
value: 84.0317100792752
- type: manhattan_ap
value: 67.66351692448987
- type: manhattan_f1
value: 63.48610948306178
- type: manhattan_precision
value: 57.11875131828729
- type: manhattan_recall
value: 71.45118733509234
- type: max_accuracy
value: 84.0317100792752
- type: max_ap
value: 67.66600090945406
- type: max_f1
value: 63.491277990844985
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 87.53832421314084
- type: cos_sim_ap
value: 83.11416594316626
- type: cos_sim_f1
value: 75.41118114347518
- type: cos_sim_precision
value: 73.12839059674504
- type: cos_sim_recall
value: 77.8410840776101
- type: dot_accuracy
value: 87.53832421314084
- type: dot_ap
value: 83.11416226342155
- type: dot_f1
value: 75.41118114347518
- type: dot_precision
value: 73.12839059674504
- type: dot_recall
value: 77.8410840776101
- type: euclidean_accuracy
value: 87.53832421314084
- type: euclidean_ap
value: 83.11416284455395
- type: euclidean_f1
value: 75.41118114347518
- type: euclidean_precision
value: 73.12839059674504
- type: euclidean_recall
value: 77.8410840776101
- type: manhattan_accuracy
value: 87.49369348391353
- type: manhattan_ap
value: 83.08066812574694
- type: manhattan_f1
value: 75.36561228603892
- type: manhattan_precision
value: 71.9202518363064
- type: manhattan_recall
value: 79.15768401601478
- type: max_accuracy
value: 87.53832421314084
- type: max_ap
value: 83.11416594316626
- type: max_f1
value: 75.41118114347518