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docs: update org name to ggml-org
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---
tags:
- mteb
- Sentence Transformers
- sentence-similarity
- sentence-transformers
- llama-cpp
- gguf-my-repo
language:
- en
license: mit
base_model: intfloat/e5-small-v2
model-index:
- name: e5-small-v2
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 77.59701492537313
- type: ap
value: 41.67064885731708
- type: f1
value: 71.86465946398573
- task:
type: Classification
dataset:
name: MTEB AmazonPolarityClassification
type: mteb/amazon_polarity
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 91.265875
- type: ap
value: 87.67633085349644
- type: f1
value: 91.24297521425744
- task:
type: Classification
dataset:
name: MTEB AmazonReviewsClassification (en)
type: mteb/amazon_reviews_multi
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 45.882000000000005
- type: f1
value: 45.08058870381236
- task:
type: Retrieval
dataset:
name: MTEB ArguAna
type: arguana
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.697
- type: map_at_10
value: 33.975
- type: map_at_100
value: 35.223
- type: map_at_1000
value: 35.260000000000005
- type: map_at_3
value: 29.776999999999997
- type: map_at_5
value: 32.035000000000004
- type: mrr_at_1
value: 20.982
- type: mrr_at_10
value: 34.094
- type: mrr_at_100
value: 35.343
- type: mrr_at_1000
value: 35.38
- type: mrr_at_3
value: 29.884
- type: mrr_at_5
value: 32.141999999999996
- type: ndcg_at_1
value: 20.697
- type: ndcg_at_10
value: 41.668
- type: ndcg_at_100
value: 47.397
- type: ndcg_at_1000
value: 48.305
- type: ndcg_at_3
value: 32.928000000000004
- type: ndcg_at_5
value: 36.998999999999995
- type: precision_at_1
value: 20.697
- type: precision_at_10
value: 6.636
- type: precision_at_100
value: 0.924
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 14.035
- type: precision_at_5
value: 10.398
- type: recall_at_1
value: 20.697
- type: recall_at_10
value: 66.35799999999999
- type: recall_at_100
value: 92.39
- type: recall_at_1000
value: 99.36
- type: recall_at_3
value: 42.105
- type: recall_at_5
value: 51.991
- task:
type: Clustering
dataset:
name: MTEB ArxivClusteringP2P
type: mteb/arxiv-clustering-p2p
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 42.1169517447068
- task:
type: Clustering
dataset:
name: MTEB ArxivClusteringS2S
type: mteb/arxiv-clustering-s2s
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 34.79553720107097
- task:
type: Reranking
dataset:
name: MTEB AskUbuntuDupQuestions
type: mteb/askubuntudupquestions-reranking
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 58.10811337308168
- type: mrr
value: 71.56410763751482
- task:
type: STS
dataset:
name: MTEB BIOSSES
type: mteb/biosses-sts
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 78.46834918248696
- type: cos_sim_spearman
value: 79.4289182755206
- type: euclidean_pearson
value: 76.26662973727008
- type: euclidean_spearman
value: 78.11744260952536
- type: manhattan_pearson
value: 76.08175262609434
- type: manhattan_spearman
value: 78.29395265552289
- task:
type: Classification
dataset:
name: MTEB Banking77Classification
type: mteb/banking77
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 81.63636363636364
- type: f1
value: 81.55779952376953
- task:
type: Clustering
dataset:
name: MTEB BiorxivClusteringP2P
type: mteb/biorxiv-clustering-p2p
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 35.88541137137571
- task:
type: Clustering
dataset:
name: MTEB BiorxivClusteringS2S
type: mteb/biorxiv-clustering-s2s
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 30.05205685274407
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackAndroidRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 30.293999999999997
- type: map_at_10
value: 39.876
- type: map_at_100
value: 41.315000000000005
- type: map_at_1000
value: 41.451
- type: map_at_3
value: 37.194
- type: map_at_5
value: 38.728
- type: mrr_at_1
value: 37.053000000000004
- type: mrr_at_10
value: 45.281
- type: mrr_at_100
value: 46.188
- type: mrr_at_1000
value: 46.245999999999995
- type: mrr_at_3
value: 43.228
- type: mrr_at_5
value: 44.366
- type: ndcg_at_1
value: 37.053000000000004
- type: ndcg_at_10
value: 45.086
- type: ndcg_at_100
value: 50.756
- type: ndcg_at_1000
value: 53.123
- type: ndcg_at_3
value: 41.416
- type: ndcg_at_5
value: 43.098
- type: precision_at_1
value: 37.053000000000004
- type: precision_at_10
value: 8.34
- type: precision_at_100
value: 1.346
- type: precision_at_1000
value: 0.186
- type: precision_at_3
value: 19.647000000000002
- type: precision_at_5
value: 13.877
- type: recall_at_1
value: 30.293999999999997
- type: recall_at_10
value: 54.309
- type: recall_at_100
value: 78.59
- type: recall_at_1000
value: 93.82300000000001
- type: recall_at_3
value: 43.168
- type: recall_at_5
value: 48.192
- type: map_at_1
value: 28.738000000000003
- type: map_at_10
value: 36.925999999999995
- type: map_at_100
value: 38.017
- type: map_at_1000
value: 38.144
- type: map_at_3
value: 34.446
- type: map_at_5
value: 35.704
- type: mrr_at_1
value: 35.478
- type: mrr_at_10
value: 42.786
- type: mrr_at_100
value: 43.458999999999996
- type: mrr_at_1000
value: 43.507
- type: mrr_at_3
value: 40.648
- type: mrr_at_5
value: 41.804
- type: ndcg_at_1
value: 35.478
- type: ndcg_at_10
value: 42.044
- type: ndcg_at_100
value: 46.249
- type: ndcg_at_1000
value: 48.44
- type: ndcg_at_3
value: 38.314
- type: ndcg_at_5
value: 39.798
- type: precision_at_1
value: 35.478
- type: precision_at_10
value: 7.764
- type: precision_at_100
value: 1.253
- type: precision_at_1000
value: 0.174
- type: precision_at_3
value: 18.047
- type: precision_at_5
value: 12.637
- type: recall_at_1
value: 28.738000000000003
- type: recall_at_10
value: 50.659
- type: recall_at_100
value: 68.76299999999999
- type: recall_at_1000
value: 82.811
- type: recall_at_3
value: 39.536
- type: recall_at_5
value: 43.763999999999996
- type: map_at_1
value: 38.565
- type: map_at_10
value: 50.168
- type: map_at_100
value: 51.11
- type: map_at_1000
value: 51.173
- type: map_at_3
value: 47.044000000000004
- type: map_at_5
value: 48.838
- type: mrr_at_1
value: 44.201
- type: mrr_at_10
value: 53.596999999999994
- type: mrr_at_100
value: 54.211
- type: mrr_at_1000
value: 54.247
- type: mrr_at_3
value: 51.202000000000005
- type: mrr_at_5
value: 52.608999999999995
- type: ndcg_at_1
value: 44.201
- type: ndcg_at_10
value: 55.694
- type: ndcg_at_100
value: 59.518
- type: ndcg_at_1000
value: 60.907
- type: ndcg_at_3
value: 50.395999999999994
- type: ndcg_at_5
value: 53.022999999999996
- type: precision_at_1
value: 44.201
- type: precision_at_10
value: 8.84
- type: precision_at_100
value: 1.162
- type: precision_at_1000
value: 0.133
- type: precision_at_3
value: 22.153
- type: precision_at_5
value: 15.260000000000002
- type: recall_at_1
value: 38.565
- type: recall_at_10
value: 68.65
- type: recall_at_100
value: 85.37400000000001
- type: recall_at_1000
value: 95.37400000000001
- type: recall_at_3
value: 54.645999999999994
- type: recall_at_5
value: 60.958
- type: map_at_1
value: 23.945
- type: map_at_10
value: 30.641000000000002
- type: map_at_100
value: 31.599
- type: map_at_1000
value: 31.691000000000003
- type: map_at_3
value: 28.405
- type: map_at_5
value: 29.704000000000004
- type: mrr_at_1
value: 25.537
- type: mrr_at_10
value: 32.22
- type: mrr_at_100
value: 33.138
- type: mrr_at_1000
value: 33.214
- type: mrr_at_3
value: 30.151
- type: mrr_at_5
value: 31.298
- type: ndcg_at_1
value: 25.537
- type: ndcg_at_10
value: 34.638000000000005
- type: ndcg_at_100
value: 39.486
- type: ndcg_at_1000
value: 41.936
- type: ndcg_at_3
value: 30.333
- type: ndcg_at_5
value: 32.482
- type: precision_at_1
value: 25.537
- type: precision_at_10
value: 5.153
- type: precision_at_100
value: 0.7929999999999999
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 12.429
- type: precision_at_5
value: 8.723
- type: recall_at_1
value: 23.945
- type: recall_at_10
value: 45.412
- type: recall_at_100
value: 67.836
- type: recall_at_1000
value: 86.467
- type: recall_at_3
value: 34.031
- type: recall_at_5
value: 39.039
- type: map_at_1
value: 14.419
- type: map_at_10
value: 20.858999999999998
- type: map_at_100
value: 22.067999999999998
- type: map_at_1000
value: 22.192
- type: map_at_3
value: 18.673000000000002
- type: map_at_5
value: 19.968
- type: mrr_at_1
value: 17.785999999999998
- type: mrr_at_10
value: 24.878
- type: mrr_at_100
value: 26.021
- type: mrr_at_1000
value: 26.095000000000002
- type: mrr_at_3
value: 22.616
- type: mrr_at_5
value: 23.785
- type: ndcg_at_1
value: 17.785999999999998
- type: ndcg_at_10
value: 25.153
- type: ndcg_at_100
value: 31.05
- type: ndcg_at_1000
value: 34.052
- type: ndcg_at_3
value: 21.117
- type: ndcg_at_5
value: 23.048
- type: precision_at_1
value: 17.785999999999998
- type: precision_at_10
value: 4.590000000000001
- type: precision_at_100
value: 0.864
- type: precision_at_1000
value: 0.125
- type: precision_at_3
value: 9.908999999999999
- type: precision_at_5
value: 7.313
- type: recall_at_1
value: 14.419
- type: recall_at_10
value: 34.477999999999994
- type: recall_at_100
value: 60.02499999999999
- type: recall_at_1000
value: 81.646
- type: recall_at_3
value: 23.515
- type: recall_at_5
value: 28.266999999999996
- type: map_at_1
value: 26.268
- type: map_at_10
value: 35.114000000000004
- type: map_at_100
value: 36.212
- type: map_at_1000
value: 36.333
- type: map_at_3
value: 32.436
- type: map_at_5
value: 33.992
- type: mrr_at_1
value: 31.761
- type: mrr_at_10
value: 40.355999999999995
- type: mrr_at_100
value: 41.125
- type: mrr_at_1000
value: 41.186
- type: mrr_at_3
value: 37.937
- type: mrr_at_5
value: 39.463
- type: ndcg_at_1
value: 31.761
- type: ndcg_at_10
value: 40.422000000000004
- type: ndcg_at_100
value: 45.458999999999996
- type: ndcg_at_1000
value: 47.951
- type: ndcg_at_3
value: 35.972
- type: ndcg_at_5
value: 38.272
- type: precision_at_1
value: 31.761
- type: precision_at_10
value: 7.103
- type: precision_at_100
value: 1.133
- type: precision_at_1000
value: 0.152
- type: precision_at_3
value: 16.779
- type: precision_at_5
value: 11.877
- type: recall_at_1
value: 26.268
- type: recall_at_10
value: 51.053000000000004
- type: recall_at_100
value: 72.702
- type: recall_at_1000
value: 89.521
- type: recall_at_3
value: 38.619
- type: recall_at_5
value: 44.671
- type: map_at_1
value: 25.230999999999998
- type: map_at_10
value: 34.227000000000004
- type: map_at_100
value: 35.370000000000005
- type: map_at_1000
value: 35.488
- type: map_at_3
value: 31.496000000000002
- type: map_at_5
value: 33.034
- type: mrr_at_1
value: 30.822
- type: mrr_at_10
value: 39.045
- type: mrr_at_100
value: 39.809
- type: mrr_at_1000
value: 39.873
- type: mrr_at_3
value: 36.663000000000004
- type: mrr_at_5
value: 37.964
- type: ndcg_at_1
value: 30.822
- type: ndcg_at_10
value: 39.472
- type: ndcg_at_100
value: 44.574999999999996
- type: ndcg_at_1000
value: 47.162
- type: ndcg_at_3
value: 34.929
- type: ndcg_at_5
value: 37.002
- type: precision_at_1
value: 30.822
- type: precision_at_10
value: 7.055
- type: precision_at_100
value: 1.124
- type: precision_at_1000
value: 0.152
- type: precision_at_3
value: 16.591
- type: precision_at_5
value: 11.667
- type: recall_at_1
value: 25.230999999999998
- type: recall_at_10
value: 50.42100000000001
- type: recall_at_100
value: 72.685
- type: recall_at_1000
value: 90.469
- type: recall_at_3
value: 37.503
- type: recall_at_5
value: 43.123
- type: map_at_1
value: 24.604166666666664
- type: map_at_10
value: 32.427166666666665
- type: map_at_100
value: 33.51474999999999
- type: map_at_1000
value: 33.6345
- type: map_at_3
value: 30.02366666666667
- type: map_at_5
value: 31.382333333333328
- type: mrr_at_1
value: 29.001166666666666
- type: mrr_at_10
value: 36.3315
- type: mrr_at_100
value: 37.16683333333333
- type: mrr_at_1000
value: 37.23341666666668
- type: mrr_at_3
value: 34.19916666666667
- type: mrr_at_5
value: 35.40458333333334
- type: ndcg_at_1
value: 29.001166666666666
- type: ndcg_at_10
value: 37.06883333333334
- type: ndcg_at_100
value: 41.95816666666666
- type: ndcg_at_1000
value: 44.501583333333336
- type: ndcg_at_3
value: 32.973499999999994
- type: ndcg_at_5
value: 34.90833333333334
- type: precision_at_1
value: 29.001166666666666
- type: precision_at_10
value: 6.336
- type: precision_at_100
value: 1.0282499999999999
- type: precision_at_1000
value: 0.14391666666666664
- type: precision_at_3
value: 14.932499999999996
- type: precision_at_5
value: 10.50825
- type: recall_at_1
value: 24.604166666666664
- type: recall_at_10
value: 46.9525
- type: recall_at_100
value: 68.67816666666667
- type: recall_at_1000
value: 86.59783333333334
- type: recall_at_3
value: 35.49783333333333
- type: recall_at_5
value: 40.52525000000001
- type: map_at_1
value: 23.559
- type: map_at_10
value: 29.023
- type: map_at_100
value: 29.818
- type: map_at_1000
value: 29.909000000000002
- type: map_at_3
value: 27.037
- type: map_at_5
value: 28.225
- type: mrr_at_1
value: 26.994
- type: mrr_at_10
value: 31.962000000000003
- type: mrr_at_100
value: 32.726
- type: mrr_at_1000
value: 32.800000000000004
- type: mrr_at_3
value: 30.266
- type: mrr_at_5
value: 31.208999999999996
- type: ndcg_at_1
value: 26.994
- type: ndcg_at_10
value: 32.53
- type: ndcg_at_100
value: 36.758
- type: ndcg_at_1000
value: 39.362
- type: ndcg_at_3
value: 28.985
- type: ndcg_at_5
value: 30.757
- type: precision_at_1
value: 26.994
- type: precision_at_10
value: 4.968999999999999
- type: precision_at_100
value: 0.759
- type: precision_at_1000
value: 0.106
- type: precision_at_3
value: 12.219
- type: precision_at_5
value: 8.527999999999999
- type: recall_at_1
value: 23.559
- type: recall_at_10
value: 40.585
- type: recall_at_100
value: 60.306000000000004
- type: recall_at_1000
value: 80.11
- type: recall_at_3
value: 30.794
- type: recall_at_5
value: 35.186
- type: map_at_1
value: 16.384999999999998
- type: map_at_10
value: 22.142
- type: map_at_100
value: 23.057
- type: map_at_1000
value: 23.177
- type: map_at_3
value: 20.29
- type: map_at_5
value: 21.332
- type: mrr_at_1
value: 19.89
- type: mrr_at_10
value: 25.771
- type: mrr_at_100
value: 26.599
- type: mrr_at_1000
value: 26.680999999999997
- type: mrr_at_3
value: 23.962
- type: mrr_at_5
value: 24.934
- type: ndcg_at_1
value: 19.89
- type: ndcg_at_10
value: 25.97
- type: ndcg_at_100
value: 30.605
- type: ndcg_at_1000
value: 33.619
- type: ndcg_at_3
value: 22.704
- type: ndcg_at_5
value: 24.199
- type: precision_at_1
value: 19.89
- type: precision_at_10
value: 4.553
- type: precision_at_100
value: 0.8049999999999999
- type: precision_at_1000
value: 0.122
- type: precision_at_3
value: 10.541
- type: precision_at_5
value: 7.46
- type: recall_at_1
value: 16.384999999999998
- type: recall_at_10
value: 34.001
- type: recall_at_100
value: 55.17100000000001
- type: recall_at_1000
value: 77.125
- type: recall_at_3
value: 24.618000000000002
- type: recall_at_5
value: 28.695999999999998
- type: map_at_1
value: 23.726
- type: map_at_10
value: 31.227
- type: map_at_100
value: 32.311
- type: map_at_1000
value: 32.419
- type: map_at_3
value: 28.765
- type: map_at_5
value: 30.229
- type: mrr_at_1
value: 27.705000000000002
- type: mrr_at_10
value: 35.085
- type: mrr_at_100
value: 35.931000000000004
- type: mrr_at_1000
value: 36
- type: mrr_at_3
value: 32.603
- type: mrr_at_5
value: 34.117999999999995
- type: ndcg_at_1
value: 27.705000000000002
- type: ndcg_at_10
value: 35.968
- type: ndcg_at_100
value: 41.197
- type: ndcg_at_1000
value: 43.76
- type: ndcg_at_3
value: 31.304
- type: ndcg_at_5
value: 33.661
- type: precision_at_1
value: 27.705000000000002
- type: precision_at_10
value: 5.942
- type: precision_at_100
value: 0.964
- type: precision_at_1000
value: 0.13
- type: precision_at_3
value: 13.868
- type: precision_at_5
value: 9.944
- type: recall_at_1
value: 23.726
- type: recall_at_10
value: 46.786
- type: recall_at_100
value: 70.072
- type: recall_at_1000
value: 88.2
- type: recall_at_3
value: 33.981
- type: recall_at_5
value: 39.893
- type: map_at_1
value: 23.344
- type: map_at_10
value: 31.636999999999997
- type: map_at_100
value: 33.065
- type: map_at_1000
value: 33.300000000000004
- type: map_at_3
value: 29.351
- type: map_at_5
value: 30.432
- type: mrr_at_1
value: 27.866000000000003
- type: mrr_at_10
value: 35.587
- type: mrr_at_100
value: 36.52
- type: mrr_at_1000
value: 36.597
- type: mrr_at_3
value: 33.696
- type: mrr_at_5
value: 34.713
- type: ndcg_at_1
value: 27.866000000000003
- type: ndcg_at_10
value: 36.61
- type: ndcg_at_100
value: 41.88
- type: ndcg_at_1000
value: 45.105000000000004
- type: ndcg_at_3
value: 33.038000000000004
- type: ndcg_at_5
value: 34.331
- type: precision_at_1
value: 27.866000000000003
- type: precision_at_10
value: 6.917
- type: precision_at_100
value: 1.3599999999999999
- type: precision_at_1000
value: 0.233
- type: precision_at_3
value: 15.547
- type: precision_at_5
value: 10.791
- type: recall_at_1
value: 23.344
- type: recall_at_10
value: 45.782000000000004
- type: recall_at_100
value: 69.503
- type: recall_at_1000
value: 90.742
- type: recall_at_3
value: 35.160000000000004
- type: recall_at_5
value: 39.058
- type: map_at_1
value: 20.776
- type: map_at_10
value: 27.285999999999998
- type: map_at_100
value: 28.235
- type: map_at_1000
value: 28.337
- type: map_at_3
value: 25.147000000000002
- type: map_at_5
value: 26.401999999999997
- type: mrr_at_1
value: 22.921
- type: mrr_at_10
value: 29.409999999999997
- type: mrr_at_100
value: 30.275000000000002
- type: mrr_at_1000
value: 30.354999999999997
- type: mrr_at_3
value: 27.418
- type: mrr_at_5
value: 28.592000000000002
- type: ndcg_at_1
value: 22.921
- type: ndcg_at_10
value: 31.239
- type: ndcg_at_100
value: 35.965
- type: ndcg_at_1000
value: 38.602
- type: ndcg_at_3
value: 27.174
- type: ndcg_at_5
value: 29.229
- type: precision_at_1
value: 22.921
- type: precision_at_10
value: 4.806
- type: precision_at_100
value: 0.776
- type: precision_at_1000
value: 0.11
- type: precision_at_3
value: 11.459999999999999
- type: precision_at_5
value: 8.022
- type: recall_at_1
value: 20.776
- type: recall_at_10
value: 41.294
- type: recall_at_100
value: 63.111
- type: recall_at_1000
value: 82.88600000000001
- type: recall_at_3
value: 30.403000000000002
- type: recall_at_5
value: 35.455999999999996
- task:
type: Retrieval
dataset:
name: MTEB ClimateFEVER
type: climate-fever
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.376
- type: map_at_10
value: 15.926000000000002
- type: map_at_100
value: 17.585
- type: map_at_1000
value: 17.776
- type: map_at_3
value: 13.014000000000001
- type: map_at_5
value: 14.417
- type: mrr_at_1
value: 20.195
- type: mrr_at_10
value: 29.95
- type: mrr_at_100
value: 31.052000000000003
- type: mrr_at_1000
value: 31.108000000000004
- type: mrr_at_3
value: 26.667
- type: mrr_at_5
value: 28.458
- type: ndcg_at_1
value: 20.195
- type: ndcg_at_10
value: 22.871
- type: ndcg_at_100
value: 29.921999999999997
- type: ndcg_at_1000
value: 33.672999999999995
- type: ndcg_at_3
value: 17.782999999999998
- type: ndcg_at_5
value: 19.544
- type: precision_at_1
value: 20.195
- type: precision_at_10
value: 7.394
- type: precision_at_100
value: 1.493
- type: precision_at_1000
value: 0.218
- type: precision_at_3
value: 13.073
- type: precision_at_5
value: 10.436
- type: recall_at_1
value: 9.376
- type: recall_at_10
value: 28.544999999999998
- type: recall_at_100
value: 53.147999999999996
- type: recall_at_1000
value: 74.62
- type: recall_at_3
value: 16.464000000000002
- type: recall_at_5
value: 21.004
- task:
type: Retrieval
dataset:
name: MTEB DBPedia
type: dbpedia-entity
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.415000000000001
- type: map_at_10
value: 18.738
- type: map_at_100
value: 27.291999999999998
- type: map_at_1000
value: 28.992
- type: map_at_3
value: 13.196
- type: map_at_5
value: 15.539
- type: mrr_at_1
value: 66.5
- type: mrr_at_10
value: 74.518
- type: mrr_at_100
value: 74.86
- type: mrr_at_1000
value: 74.87
- type: mrr_at_3
value: 72.375
- type: mrr_at_5
value: 73.86200000000001
- type: ndcg_at_1
value: 54.37499999999999
- type: ndcg_at_10
value: 41.317
- type: ndcg_at_100
value: 45.845
- type: ndcg_at_1000
value: 52.92
- type: ndcg_at_3
value: 44.983000000000004
- type: ndcg_at_5
value: 42.989
- type: precision_at_1
value: 66.5
- type: precision_at_10
value: 33.6
- type: precision_at_100
value: 10.972999999999999
- type: precision_at_1000
value: 2.214
- type: precision_at_3
value: 48.583
- type: precision_at_5
value: 42.15
- type: recall_at_1
value: 8.415000000000001
- type: recall_at_10
value: 24.953
- type: recall_at_100
value: 52.48199999999999
- type: recall_at_1000
value: 75.093
- type: recall_at_3
value: 14.341000000000001
- type: recall_at_5
value: 18.468
- task:
type: Classification
dataset:
name: MTEB EmotionClassification
type: mteb/emotion
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 47.06499999999999
- type: f1
value: 41.439327599975385
- task:
type: Retrieval
dataset:
name: MTEB FEVER
type: fever
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 66.02
- type: map_at_10
value: 76.68599999999999
- type: map_at_100
value: 76.959
- type: map_at_1000
value: 76.972
- type: map_at_3
value: 75.024
- type: map_at_5
value: 76.153
- type: mrr_at_1
value: 71.197
- type: mrr_at_10
value: 81.105
- type: mrr_at_100
value: 81.232
- type: mrr_at_1000
value: 81.233
- type: mrr_at_3
value: 79.758
- type: mrr_at_5
value: 80.69
- type: ndcg_at_1
value: 71.197
- type: ndcg_at_10
value: 81.644
- type: ndcg_at_100
value: 82.645
- type: ndcg_at_1000
value: 82.879
- type: ndcg_at_3
value: 78.792
- type: ndcg_at_5
value: 80.528
- type: precision_at_1
value: 71.197
- type: precision_at_10
value: 10.206999999999999
- type: precision_at_100
value: 1.093
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 30.868000000000002
- type: precision_at_5
value: 19.559
- type: recall_at_1
value: 66.02
- type: recall_at_10
value: 92.50699999999999
- type: recall_at_100
value: 96.497
- type: recall_at_1000
value: 97.956
- type: recall_at_3
value: 84.866
- type: recall_at_5
value: 89.16199999999999
- task:
type: Retrieval
dataset:
name: MTEB FiQA2018
type: fiqa
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.948
- type: map_at_10
value: 29.833
- type: map_at_100
value: 31.487
- type: map_at_1000
value: 31.674000000000003
- type: map_at_3
value: 26.029999999999998
- type: map_at_5
value: 28.038999999999998
- type: mrr_at_1
value: 34.721999999999994
- type: mrr_at_10
value: 44.214999999999996
- type: mrr_at_100
value: 44.994
- type: mrr_at_1000
value: 45.051
- type: mrr_at_3
value: 41.667
- type: mrr_at_5
value: 43.032
- type: ndcg_at_1
value: 34.721999999999994
- type: ndcg_at_10
value: 37.434
- type: ndcg_at_100
value: 43.702000000000005
- type: ndcg_at_1000
value: 46.993
- type: ndcg_at_3
value: 33.56
- type: ndcg_at_5
value: 34.687
- type: precision_at_1
value: 34.721999999999994
- type: precision_at_10
value: 10.401
- type: precision_at_100
value: 1.7049999999999998
- type: precision_at_1000
value: 0.22799999999999998
- type: precision_at_3
value: 22.531000000000002
- type: precision_at_5
value: 16.42
- type: recall_at_1
value: 17.948
- type: recall_at_10
value: 45.062999999999995
- type: recall_at_100
value: 68.191
- type: recall_at_1000
value: 87.954
- type: recall_at_3
value: 31.112000000000002
- type: recall_at_5
value: 36.823
- task:
type: Retrieval
dataset:
name: MTEB HotpotQA
type: hotpotqa
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 36.644
- type: map_at_10
value: 57.658
- type: map_at_100
value: 58.562000000000005
- type: map_at_1000
value: 58.62500000000001
- type: map_at_3
value: 54.022999999999996
- type: map_at_5
value: 56.293000000000006
- type: mrr_at_1
value: 73.288
- type: mrr_at_10
value: 80.51700000000001
- type: mrr_at_100
value: 80.72
- type: mrr_at_1000
value: 80.728
- type: mrr_at_3
value: 79.33200000000001
- type: mrr_at_5
value: 80.085
- type: ndcg_at_1
value: 73.288
- type: ndcg_at_10
value: 66.61
- type: ndcg_at_100
value: 69.723
- type: ndcg_at_1000
value: 70.96000000000001
- type: ndcg_at_3
value: 61.358999999999995
- type: ndcg_at_5
value: 64.277
- type: precision_at_1
value: 73.288
- type: precision_at_10
value: 14.17
- type: precision_at_100
value: 1.659
- type: precision_at_1000
value: 0.182
- type: precision_at_3
value: 39.487
- type: precision_at_5
value: 25.999
- type: recall_at_1
value: 36.644
- type: recall_at_10
value: 70.851
- type: recall_at_100
value: 82.94399999999999
- type: recall_at_1000
value: 91.134
- type: recall_at_3
value: 59.230000000000004
- type: recall_at_5
value: 64.997
- task:
type: Classification
dataset:
name: MTEB ImdbClassification
type: mteb/imdb
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 86.00280000000001
- type: ap
value: 80.46302061021223
- type: f1
value: 85.9592921596419
- task:
type: Retrieval
dataset:
name: MTEB MSMARCO
type: msmarco
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 22.541
- type: map_at_10
value: 34.625
- type: map_at_100
value: 35.785
- type: map_at_1000
value: 35.831
- type: map_at_3
value: 30.823
- type: map_at_5
value: 32.967999999999996
- type: mrr_at_1
value: 23.180999999999997
- type: mrr_at_10
value: 35.207
- type: mrr_at_100
value: 36.315
- type: mrr_at_1000
value: 36.355
- type: mrr_at_3
value: 31.483
- type: mrr_at_5
value: 33.589999999999996
- type: ndcg_at_1
value: 23.195
- type: ndcg_at_10
value: 41.461
- type: ndcg_at_100
value: 47.032000000000004
- type: ndcg_at_1000
value: 48.199999999999996
- type: ndcg_at_3
value: 33.702
- type: ndcg_at_5
value: 37.522
- type: precision_at_1
value: 23.195
- type: precision_at_10
value: 6.526999999999999
- type: precision_at_100
value: 0.932
- type: precision_at_1000
value: 0.10300000000000001
- type: precision_at_3
value: 14.308000000000002
- type: precision_at_5
value: 10.507
- type: recall_at_1
value: 22.541
- type: recall_at_10
value: 62.524
- type: recall_at_100
value: 88.228
- type: recall_at_1000
value: 97.243
- type: recall_at_3
value: 41.38
- type: recall_at_5
value: 50.55
- task:
type: Classification
dataset:
name: MTEB MTOPDomainClassification (en)
type: mteb/mtop_domain
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 92.69949840401279
- type: f1
value: 92.54141471311786
- task:
type: Classification
dataset:
name: MTEB MTOPIntentClassification (en)
type: mteb/mtop_intent
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 72.56041951664386
- type: f1
value: 55.88499977508287
- task:
type: Classification
dataset:
name: MTEB MassiveIntentClassification (en)
type: mteb/amazon_massive_intent
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 71.62071284465365
- type: f1
value: 69.36717546572152
- task:
type: Classification
dataset:
name: MTEB MassiveScenarioClassification (en)
type: mteb/amazon_massive_scenario
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 76.35843981170142
- type: f1
value: 76.15496453538884
- task:
type: Clustering
dataset:
name: MTEB MedrxivClusteringP2P
type: mteb/medrxiv-clustering-p2p
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 31.33664956793118
- task:
type: Clustering
dataset:
name: MTEB MedrxivClusteringS2S
type: mteb/medrxiv-clustering-s2s
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 27.883839621715524
- task:
type: Reranking
dataset:
name: MTEB MindSmallReranking
type: mteb/mind_small
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 30.096874986740758
- type: mrr
value: 30.97300481932132
- task:
type: Retrieval
dataset:
name: MTEB NFCorpus
type: nfcorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.4
- type: map_at_10
value: 11.852
- type: map_at_100
value: 14.758
- type: map_at_1000
value: 16.134
- type: map_at_3
value: 8.558
- type: map_at_5
value: 10.087
- type: mrr_at_1
value: 44.272
- type: mrr_at_10
value: 52.05800000000001
- type: mrr_at_100
value: 52.689
- type: mrr_at_1000
value: 52.742999999999995
- type: mrr_at_3
value: 50.205999999999996
- type: mrr_at_5
value: 51.367
- type: ndcg_at_1
value: 42.57
- type: ndcg_at_10
value: 32.449
- type: ndcg_at_100
value: 29.596
- type: ndcg_at_1000
value: 38.351
- type: ndcg_at_3
value: 37.044
- type: ndcg_at_5
value: 35.275
- type: precision_at_1
value: 44.272
- type: precision_at_10
value: 23.87
- type: precision_at_100
value: 7.625
- type: precision_at_1000
value: 2.045
- type: precision_at_3
value: 34.365
- type: precision_at_5
value: 30.341
- type: recall_at_1
value: 5.4
- type: recall_at_10
value: 15.943999999999999
- type: recall_at_100
value: 29.805
- type: recall_at_1000
value: 61.695
- type: recall_at_3
value: 9.539
- type: recall_at_5
value: 12.127
- task:
type: Retrieval
dataset:
name: MTEB NQ
type: nq
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 36.047000000000004
- type: map_at_10
value: 51.6
- type: map_at_100
value: 52.449999999999996
- type: map_at_1000
value: 52.476
- type: map_at_3
value: 47.452
- type: map_at_5
value: 49.964
- type: mrr_at_1
value: 40.382
- type: mrr_at_10
value: 54.273
- type: mrr_at_100
value: 54.859
- type: mrr_at_1000
value: 54.876000000000005
- type: mrr_at_3
value: 51.014
- type: mrr_at_5
value: 52.983999999999995
- type: ndcg_at_1
value: 40.353
- type: ndcg_at_10
value: 59.11300000000001
- type: ndcg_at_100
value: 62.604000000000006
- type: ndcg_at_1000
value: 63.187000000000005
- type: ndcg_at_3
value: 51.513
- type: ndcg_at_5
value: 55.576
- type: precision_at_1
value: 40.353
- type: precision_at_10
value: 9.418
- type: precision_at_100
value: 1.1440000000000001
- type: precision_at_1000
value: 0.12
- type: precision_at_3
value: 23.078000000000003
- type: precision_at_5
value: 16.250999999999998
- type: recall_at_1
value: 36.047000000000004
- type: recall_at_10
value: 79.22200000000001
- type: recall_at_100
value: 94.23
- type: recall_at_1000
value: 98.51100000000001
- type: recall_at_3
value: 59.678
- type: recall_at_5
value: 68.967
- task:
type: Retrieval
dataset:
name: MTEB QuoraRetrieval
type: quora
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 68.232
- type: map_at_10
value: 81.674
- type: map_at_100
value: 82.338
- type: map_at_1000
value: 82.36099999999999
- type: map_at_3
value: 78.833
- type: map_at_5
value: 80.58
- type: mrr_at_1
value: 78.64
- type: mrr_at_10
value: 85.164
- type: mrr_at_100
value: 85.317
- type: mrr_at_1000
value: 85.319
- type: mrr_at_3
value: 84.127
- type: mrr_at_5
value: 84.789
- type: ndcg_at_1
value: 78.63
- type: ndcg_at_10
value: 85.711
- type: ndcg_at_100
value: 87.238
- type: ndcg_at_1000
value: 87.444
- type: ndcg_at_3
value: 82.788
- type: ndcg_at_5
value: 84.313
- type: precision_at_1
value: 78.63
- type: precision_at_10
value: 12.977
- type: precision_at_100
value: 1.503
- type: precision_at_1000
value: 0.156
- type: precision_at_3
value: 36.113
- type: precision_at_5
value: 23.71
- type: recall_at_1
value: 68.232
- type: recall_at_10
value: 93.30199999999999
- type: recall_at_100
value: 98.799
- type: recall_at_1000
value: 99.885
- type: recall_at_3
value: 84.827
- type: recall_at_5
value: 89.188
- task:
type: Clustering
dataset:
name: MTEB RedditClustering
type: mteb/reddit-clustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 45.71879170816294
- task:
type: Clustering
dataset:
name: MTEB RedditClusteringP2P
type: mteb/reddit-clustering-p2p
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 59.65866311751794
- task:
type: Retrieval
dataset:
name: MTEB SCIDOCS
type: scidocs
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.218
- type: map_at_10
value: 10.337
- type: map_at_100
value: 12.131
- type: map_at_1000
value: 12.411
- type: map_at_3
value: 7.4270000000000005
- type: map_at_5
value: 8.913
- type: mrr_at_1
value: 20.8
- type: mrr_at_10
value: 30.868000000000002
- type: mrr_at_100
value: 31.903
- type: mrr_at_1000
value: 31.972
- type: mrr_at_3
value: 27.367
- type: mrr_at_5
value: 29.372
- type: ndcg_at_1
value: 20.8
- type: ndcg_at_10
value: 17.765
- type: ndcg_at_100
value: 24.914
- type: ndcg_at_1000
value: 30.206
- type: ndcg_at_3
value: 16.64
- type: ndcg_at_5
value: 14.712
- type: precision_at_1
value: 20.8
- type: precision_at_10
value: 9.24
- type: precision_at_100
value: 1.9560000000000002
- type: precision_at_1000
value: 0.32299999999999995
- type: precision_at_3
value: 15.467
- type: precision_at_5
value: 12.94
- type: recall_at_1
value: 4.218
- type: recall_at_10
value: 18.752
- type: recall_at_100
value: 39.7
- type: recall_at_1000
value: 65.57300000000001
- type: recall_at_3
value: 9.428
- type: recall_at_5
value: 13.133000000000001
- task:
type: STS
dataset:
name: MTEB SICK-R
type: mteb/sickr-sts
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 83.04338850207233
- type: cos_sim_spearman
value: 78.5054651430423
- type: euclidean_pearson
value: 80.30739451228612
- type: euclidean_spearman
value: 78.48377464299097
- type: manhattan_pearson
value: 80.40795049052781
- type: manhattan_spearman
value: 78.49506205443114
- task:
type: STS
dataset:
name: MTEB STS12
type: mteb/sts12-sts
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 84.11596224442962
- type: cos_sim_spearman
value: 76.20997388935461
- type: euclidean_pearson
value: 80.56858451349109
- type: euclidean_spearman
value: 75.92659183871186
- type: manhattan_pearson
value: 80.60246102203844
- type: manhattan_spearman
value: 76.03018971432664
- task:
type: STS
dataset:
name: MTEB STS13
type: mteb/sts13-sts
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 81.34691640755737
- type: cos_sim_spearman
value: 82.4018369631579
- type: euclidean_pearson
value: 81.87673092245366
- type: euclidean_spearman
value: 82.3671489960678
- type: manhattan_pearson
value: 81.88222387719948
- type: manhattan_spearman
value: 82.3816590344736
- task:
type: STS
dataset:
name: MTEB STS14
type: mteb/sts14-sts
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 81.2836092579524
- type: cos_sim_spearman
value: 78.99982781772064
- type: euclidean_pearson
value: 80.5184271010527
- type: euclidean_spearman
value: 78.89777392101904
- type: manhattan_pearson
value: 80.53585705018664
- type: manhattan_spearman
value: 78.92898405472994
- task:
type: STS
dataset:
name: MTEB STS15
type: mteb/sts15-sts
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 86.7349907750784
- type: cos_sim_spearman
value: 87.7611234446225
- type: euclidean_pearson
value: 86.98759326731624
- type: euclidean_spearman
value: 87.58321319424618
- type: manhattan_pearson
value: 87.03483090370842
- type: manhattan_spearman
value: 87.63278333060288
- task:
type: STS
dataset:
name: MTEB STS16
type: mteb/sts16-sts
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 81.75873694924825
- type: cos_sim_spearman
value: 83.80237999094724
- type: euclidean_pearson
value: 83.55023725861537
- type: euclidean_spearman
value: 84.12744338577744
- type: manhattan_pearson
value: 83.58816983036232
- type: manhattan_spearman
value: 84.18520748676501
- task:
type: STS
dataset:
name: MTEB STS17 (en-en)
type: mteb/sts17-crosslingual-sts
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 87.21630882940174
- type: cos_sim_spearman
value: 87.72382883437031
- type: euclidean_pearson
value: 88.69933350930333
- type: euclidean_spearman
value: 88.24660814383081
- type: manhattan_pearson
value: 88.77331018833499
- type: manhattan_spearman
value: 88.26109989380632
- task:
type: STS
dataset:
name: MTEB STS22 (en)
type: mteb/sts22-crosslingual-sts
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 61.11854063060489
- type: cos_sim_spearman
value: 63.14678634195072
- type: euclidean_pearson
value: 61.679090067000864
- type: euclidean_spearman
value: 62.28876589509653
- type: manhattan_pearson
value: 62.082324165511004
- type: manhattan_spearman
value: 62.56030932816679
- task:
type: STS
dataset:
name: MTEB STSBenchmark
type: mteb/stsbenchmark-sts
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 84.00319882832645
- type: cos_sim_spearman
value: 85.94529772647257
- type: euclidean_pearson
value: 85.6661390122756
- type: euclidean_spearman
value: 85.97747815545827
- type: manhattan_pearson
value: 85.58422770541893
- type: manhattan_spearman
value: 85.9237139181532
- task:
type: Reranking
dataset:
name: MTEB SciDocsRR
type: mteb/scidocs-reranking
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 79.16198731863916
- type: mrr
value: 94.25202702163487
- task:
type: Retrieval
dataset:
name: MTEB SciFact
type: scifact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 54.761
- type: map_at_10
value: 64.396
- type: map_at_100
value: 65.07
- type: map_at_1000
value: 65.09899999999999
- type: map_at_3
value: 61.846000000000004
- type: map_at_5
value: 63.284
- type: mrr_at_1
value: 57.667
- type: mrr_at_10
value: 65.83099999999999
- type: mrr_at_100
value: 66.36800000000001
- type: mrr_at_1000
value: 66.39399999999999
- type: mrr_at_3
value: 64.056
- type: mrr_at_5
value: 65.206
- type: ndcg_at_1
value: 57.667
- type: ndcg_at_10
value: 68.854
- type: ndcg_at_100
value: 71.59100000000001
- type: ndcg_at_1000
value: 72.383
- type: ndcg_at_3
value: 64.671
- type: ndcg_at_5
value: 66.796
- type: precision_at_1
value: 57.667
- type: precision_at_10
value: 9.167
- type: precision_at_100
value: 1.053
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 25.444
- type: precision_at_5
value: 16.667
- type: recall_at_1
value: 54.761
- type: recall_at_10
value: 80.9
- type: recall_at_100
value: 92.767
- type: recall_at_1000
value: 99
- type: recall_at_3
value: 69.672
- type: recall_at_5
value: 75.083
- task:
type: PairClassification
dataset:
name: MTEB SprintDuplicateQuestions
type: mteb/sprintduplicatequestions-pairclassification
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.8079207920792
- type: cos_sim_ap
value: 94.88470927617445
- type: cos_sim_f1
value: 90.08179959100204
- type: cos_sim_precision
value: 92.15481171548117
- type: cos_sim_recall
value: 88.1
- type: dot_accuracy
value: 99.58613861386138
- type: dot_ap
value: 82.94822578881316
- type: dot_f1
value: 77.33333333333333
- type: dot_precision
value: 79.36842105263158
- type: dot_recall
value: 75.4
- type: euclidean_accuracy
value: 99.8069306930693
- type: euclidean_ap
value: 94.81367858031837
- type: euclidean_f1
value: 90.01009081735621
- type: euclidean_precision
value: 90.83503054989816
- type: euclidean_recall
value: 89.2
- type: manhattan_accuracy
value: 99.81188118811882
- type: manhattan_ap
value: 94.91405337220161
- type: manhattan_f1
value: 90.2763561924258
- type: manhattan_precision
value: 92.45283018867924
- type: manhattan_recall
value: 88.2
- type: max_accuracy
value: 99.81188118811882
- type: max_ap
value: 94.91405337220161
- type: max_f1
value: 90.2763561924258
- task:
type: Clustering
dataset:
name: MTEB StackExchangeClustering
type: mteb/stackexchange-clustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 58.511599500053094
- task:
type: Clustering
dataset:
name: MTEB StackExchangeClusteringP2P
type: mteb/stackexchange-clustering-p2p
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 31.984728147814707
- task:
type: Reranking
dataset:
name: MTEB StackOverflowDupQuestions
type: mteb/stackoverflowdupquestions-reranking
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 49.93428193939015
- type: mrr
value: 50.916557911043206
- task:
type: Summarization
dataset:
name: MTEB SummEval
type: mteb/summeval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.562500894537145
- type: cos_sim_spearman
value: 31.162587976726307
- type: dot_pearson
value: 22.633662187735762
- type: dot_spearman
value: 22.723000282378962
- task:
type: Retrieval
dataset:
name: MTEB TRECCOVID
type: trec-covid
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.219
- type: map_at_10
value: 1.871
- type: map_at_100
value: 10.487
- type: map_at_1000
value: 25.122
- type: map_at_3
value: 0.657
- type: map_at_5
value: 1.0699999999999998
- type: mrr_at_1
value: 84
- type: mrr_at_10
value: 89.567
- type: mrr_at_100
value: 89.748
- type: mrr_at_1000
value: 89.748
- type: mrr_at_3
value: 88.667
- type: mrr_at_5
value: 89.567
- type: ndcg_at_1
value: 80
- type: ndcg_at_10
value: 74.533
- type: ndcg_at_100
value: 55.839000000000006
- type: ndcg_at_1000
value: 49.748
- type: ndcg_at_3
value: 79.53099999999999
- type: ndcg_at_5
value: 78.245
- type: precision_at_1
value: 84
- type: precision_at_10
value: 78.4
- type: precision_at_100
value: 56.99999999999999
- type: precision_at_1000
value: 21.98
- type: precision_at_3
value: 85.333
- type: precision_at_5
value: 84.8
- type: recall_at_1
value: 0.219
- type: recall_at_10
value: 2.02
- type: recall_at_100
value: 13.555
- type: recall_at_1000
value: 46.739999999999995
- type: recall_at_3
value: 0.685
- type: recall_at_5
value: 1.13
- task:
type: Retrieval
dataset:
name: MTEB Touche2020
type: webis-touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.5029999999999997
- type: map_at_10
value: 11.042
- type: map_at_100
value: 16.326999999999998
- type: map_at_1000
value: 17.836
- type: map_at_3
value: 6.174
- type: map_at_5
value: 7.979
- type: mrr_at_1
value: 42.857
- type: mrr_at_10
value: 52.617000000000004
- type: mrr_at_100
value: 53.351000000000006
- type: mrr_at_1000
value: 53.351000000000006
- type: mrr_at_3
value: 46.939
- type: mrr_at_5
value: 50.714000000000006
- type: ndcg_at_1
value: 38.775999999999996
- type: ndcg_at_10
value: 27.125
- type: ndcg_at_100
value: 35.845
- type: ndcg_at_1000
value: 47.377
- type: ndcg_at_3
value: 29.633
- type: ndcg_at_5
value: 28.378999999999998
- type: precision_at_1
value: 42.857
- type: precision_at_10
value: 24.082
- type: precision_at_100
value: 6.877999999999999
- type: precision_at_1000
value: 1.463
- type: precision_at_3
value: 29.932
- type: precision_at_5
value: 28.571
- type: recall_at_1
value: 3.5029999999999997
- type: recall_at_10
value: 17.068
- type: recall_at_100
value: 43.361
- type: recall_at_1000
value: 78.835
- type: recall_at_3
value: 6.821000000000001
- type: recall_at_5
value: 10.357
- task:
type: Classification
dataset:
name: MTEB ToxicConversationsClassification
type: mteb/toxic_conversations_50k
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 71.0954
- type: ap
value: 14.216844153511959
- type: f1
value: 54.63687418565117
- task:
type: Classification
dataset:
name: MTEB TweetSentimentExtractionClassification
type: mteb/tweet_sentiment_extraction
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 61.46293152235427
- type: f1
value: 61.744177921638645
- task:
type: Clustering
dataset:
name: MTEB TwentyNewsgroupsClustering
type: mteb/twentynewsgroups-clustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 41.12708617788644
- task:
type: PairClassification
dataset:
name: MTEB TwitterSemEval2015
type: mteb/twittersemeval2015-pairclassification
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 85.75430649102938
- type: cos_sim_ap
value: 73.34252536948081
- type: cos_sim_f1
value: 67.53758935173774
- type: cos_sim_precision
value: 63.3672525439408
- type: cos_sim_recall
value: 72.29551451187335
- type: dot_accuracy
value: 81.71305954580676
- type: dot_ap
value: 59.5532209082386
- type: dot_f1
value: 56.18466898954705
- type: dot_precision
value: 47.830923248053395
- type: dot_recall
value: 68.07387862796834
- type: euclidean_accuracy
value: 85.81987244441795
- type: euclidean_ap
value: 73.34325409809446
- type: euclidean_f1
value: 67.83451360417443
- type: euclidean_precision
value: 64.09955388588871
- type: euclidean_recall
value: 72.0316622691293
- type: manhattan_accuracy
value: 85.68277999642368
- type: manhattan_ap
value: 73.1535450121903
- type: manhattan_f1
value: 67.928237896289
- type: manhattan_precision
value: 63.56945722171113
- type: manhattan_recall
value: 72.9287598944591
- type: max_accuracy
value: 85.81987244441795
- type: max_ap
value: 73.34325409809446
- type: max_f1
value: 67.928237896289
- task:
type: PairClassification
dataset:
name: MTEB TwitterURLCorpus
type: mteb/twitterurlcorpus-pairclassification
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.90441262079403
- type: cos_sim_ap
value: 85.79331880741438
- type: cos_sim_f1
value: 78.31563529842548
- type: cos_sim_precision
value: 74.6683424102779
- type: cos_sim_recall
value: 82.33754234678165
- type: dot_accuracy
value: 84.89928978926534
- type: dot_ap
value: 75.25819218316
- type: dot_f1
value: 69.88730119720536
- type: dot_precision
value: 64.23362374959665
- type: dot_recall
value: 76.63227594702803
- type: euclidean_accuracy
value: 89.01695967710637
- type: euclidean_ap
value: 85.98986606038852
- type: euclidean_f1
value: 78.5277880014722
- type: euclidean_precision
value: 75.22211253701876
- type: euclidean_recall
value: 82.13735756082538
- type: manhattan_accuracy
value: 88.99561454573679
- type: manhattan_ap
value: 85.92262421793953
- type: manhattan_f1
value: 78.38866094740769
- type: manhattan_precision
value: 76.02373028505282
- type: manhattan_recall
value: 80.9054511857099
- type: max_accuracy
value: 89.01695967710637
- type: max_ap
value: 85.98986606038852
- type: max_f1
value: 78.5277880014722
---
# ggml-org/e5-small-v2-Q8_0-GGUF
This model was converted to GGUF format from [`intfloat/e5-small-v2`](https://huggingface.co/intfloat/e5-small-v2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/intfloat/e5-small-v2) for more details on the model.
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
```bash
brew install llama.cpp
```
Invoke the llama.cpp server or the CLI.
### CLI:
```bash
llama-cli --hf-repo ggml-org/e5-small-v2-Q8_0-GGUF --hf-file e5-small-v2-q8_0.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo ggml-org/e5-small-v2-Q8_0-GGUF --hf-file e5-small-v2-q8_0.gguf -c 2048
```
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```
Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo ggml-org/e5-small-v2-Q8_0-GGUF --hf-file e5-small-v2-q8_0.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo ggml-org/e5-small-v2-Q8_0-GGUF --hf-file e5-small-v2-q8_0.gguf -c 2048
```