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1_Pooling/config.json

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+{
+  "word_embedding_dimension": 384,
+  "pooling_mode_cls_token": false,
+  "pooling_mode_mean_tokens": true,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false
+}

README.md

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+---
+tags:
+- mteb
+- sentence-similarity
+- sentence-transformers
+- Sentence Transformers
+model-index:
+- name: gte-small 
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 73.22388059701493
+    - type: ap
+      value: 36.09895941426988
+    - type: f1
+      value: 67.3205651539195
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 91.81894999999999
+    - type: ap
+      value: 88.5240138417305
+    - type: f1
+      value: 91.80367382706962
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 48.032
+    - type: f1
+      value: 47.4490665674719
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 30.725
+    - type: map_at_10
+      value: 46.604
+    - type: map_at_100
+      value: 47.535
+    - type: map_at_1000
+      value: 47.538000000000004
+    - type: map_at_3
+      value: 41.833
+    - type: map_at_5
+      value: 44.61
+    - type: mrr_at_1
+      value: 31.223
+    - type: mrr_at_10
+      value: 46.794000000000004
+    - type: mrr_at_100
+      value: 47.725
+    - type: mrr_at_1000
+      value: 47.727000000000004
+    - type: mrr_at_3
+      value: 42.07
+    - type: mrr_at_5
+      value: 44.812000000000005
+    - type: ndcg_at_1
+      value: 30.725
+    - type: ndcg_at_10
+      value: 55.440999999999995
+    - type: ndcg_at_100
+      value: 59.134
+    - type: ndcg_at_1000
+      value: 59.199
+    - type: ndcg_at_3
+      value: 45.599000000000004
+    - type: ndcg_at_5
+      value: 50.637
+    - type: precision_at_1
+      value: 30.725
+    - type: precision_at_10
+      value: 8.364
+    - type: precision_at_100
+      value: 0.991
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 18.848000000000003
+    - type: precision_at_5
+      value: 13.77
+    - type: recall_at_1
+      value: 30.725
+    - type: recall_at_10
+      value: 83.64200000000001
+    - type: recall_at_100
+      value: 99.14699999999999
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 56.543
+    - type: recall_at_5
+      value: 68.848
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 47.90178078197678
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 40.25728393431922
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 61.720297062897764
+    - type: mrr
+      value: 75.24139295607439
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 89.43527309184616
+    - type: cos_sim_spearman
+      value: 88.17128615100206
+    - type: euclidean_pearson
+      value: 87.89922623089282
+    - type: euclidean_spearman
+      value: 87.96104039655451
+    - type: manhattan_pearson
+      value: 87.9818290932077
+    - type: manhattan_spearman
+      value: 88.00923426576885
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 84.0844155844156
+    - type: f1
+      value: 84.01485017302213
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 38.36574769259432
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 35.4857033165287
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 30.261
+    - type: map_at_10
+      value: 42.419000000000004
+    - type: map_at_100
+      value: 43.927
+    - type: map_at_1000
+      value: 44.055
+    - type: map_at_3
+      value: 38.597
+    - type: map_at_5
+      value: 40.701
+    - type: mrr_at_1
+      value: 36.91
+    - type: mrr_at_10
+      value: 48.02
+    - type: mrr_at_100
+      value: 48.658
+    - type: mrr_at_1000
+      value: 48.708
+    - type: mrr_at_3
+      value: 44.945
+    - type: mrr_at_5
+      value: 46.705000000000005
+    - type: ndcg_at_1
+      value: 36.91
+    - type: ndcg_at_10
+      value: 49.353
+    - type: ndcg_at_100
+      value: 54.456
+    - type: ndcg_at_1000
+      value: 56.363
+    - type: ndcg_at_3
+      value: 43.483
+    - type: ndcg_at_5
+      value: 46.150999999999996
+    - type: precision_at_1
+      value: 36.91
+    - type: precision_at_10
+      value: 9.700000000000001
+    - type: precision_at_100
+      value: 1.557
+    - type: precision_at_1000
+      value: 0.202
+    - type: precision_at_3
+      value: 21.078
+    - type: precision_at_5
+      value: 15.421999999999999
+    - type: recall_at_1
+      value: 30.261
+    - type: recall_at_10
+      value: 63.242
+    - type: recall_at_100
+      value: 84.09100000000001
+    - type: recall_at_1000
+      value: 96.143
+    - type: recall_at_3
+      value: 46.478
+    - type: recall_at_5
+      value: 53.708
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 31.145
+    - type: map_at_10
+      value: 40.996
+    - type: map_at_100
+      value: 42.266999999999996
+    - type: map_at_1000
+      value: 42.397
+    - type: map_at_3
+      value: 38.005
+    - type: map_at_5
+      value: 39.628
+    - type: mrr_at_1
+      value: 38.344
+    - type: mrr_at_10
+      value: 46.827000000000005
+    - type: mrr_at_100
+      value: 47.446
+    - type: mrr_at_1000
+      value: 47.489
+    - type: mrr_at_3
+      value: 44.448
+    - type: mrr_at_5
+      value: 45.747
+    - type: ndcg_at_1
+      value: 38.344
+    - type: ndcg_at_10
+      value: 46.733000000000004
+    - type: ndcg_at_100
+      value: 51.103
+    - type: ndcg_at_1000
+      value: 53.075
+    - type: ndcg_at_3
+      value: 42.366
+    - type: ndcg_at_5
+      value: 44.242
+    - type: precision_at_1
+      value: 38.344
+    - type: precision_at_10
+      value: 8.822000000000001
+    - type: precision_at_100
+      value: 1.417
+    - type: precision_at_1000
+      value: 0.187
+    - type: precision_at_3
+      value: 20.403
+    - type: precision_at_5
+      value: 14.306
+    - type: recall_at_1
+      value: 31.145
+    - type: recall_at_10
+      value: 56.909
+    - type: recall_at_100
+      value: 75.274
+    - type: recall_at_1000
+      value: 87.629
+    - type: recall_at_3
+      value: 43.784
+    - type: recall_at_5
+      value: 49.338
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 38.83
+    - type: map_at_10
+      value: 51.553000000000004
+    - type: map_at_100
+      value: 52.581
+    - type: map_at_1000
+      value: 52.638
+    - type: map_at_3
+      value: 48.112
+    - type: map_at_5
+      value: 50.095
+    - type: mrr_at_1
+      value: 44.513999999999996
+    - type: mrr_at_10
+      value: 54.998000000000005
+    - type: mrr_at_100
+      value: 55.650999999999996
+    - type: mrr_at_1000
+      value: 55.679
+    - type: mrr_at_3
+      value: 52.602000000000004
+    - type: mrr_at_5
+      value: 53.931
+    - type: ndcg_at_1
+      value: 44.513999999999996
+    - type: ndcg_at_10
+      value: 57.67400000000001
+    - type: ndcg_at_100
+      value: 61.663999999999994
+    - type: ndcg_at_1000
+      value: 62.743
+    - type: ndcg_at_3
+      value: 51.964
+    - type: ndcg_at_5
+      value: 54.773
+    - type: precision_at_1
+      value: 44.513999999999996
+    - type: precision_at_10
+      value: 9.423
+    - type: precision_at_100
+      value: 1.2309999999999999
+    - type: precision_at_1000
+      value: 0.13699999999999998
+    - type: precision_at_3
+      value: 23.323
+    - type: precision_at_5
+      value: 16.163
+    - type: recall_at_1
+      value: 38.83
+    - type: recall_at_10
+      value: 72.327
+    - type: recall_at_100
+      value: 89.519
+    - type: recall_at_1000
+      value: 97.041
+    - type: recall_at_3
+      value: 57.206
+    - type: recall_at_5
+      value: 63.88399999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.484
+    - type: map_at_10
+      value: 34.527
+    - type: map_at_100
+      value: 35.661
+    - type: map_at_1000
+      value: 35.739
+    - type: map_at_3
+      value: 32.199
+    - type: map_at_5
+      value: 33.632
+    - type: mrr_at_1
+      value: 27.458
+    - type: mrr_at_10
+      value: 36.543
+    - type: mrr_at_100
+      value: 37.482
+    - type: mrr_at_1000
+      value: 37.543
+    - type: mrr_at_3
+      value: 34.256
+    - type: mrr_at_5
+      value: 35.618
+    - type: ndcg_at_1
+      value: 27.458
+    - type: ndcg_at_10
+      value: 39.396
+    - type: ndcg_at_100
+      value: 44.742
+    - type: ndcg_at_1000
+      value: 46.708
+    - type: ndcg_at_3
+      value: 34.817
+    - type: ndcg_at_5
+      value: 37.247
+    - type: precision_at_1
+      value: 27.458
+    - type: precision_at_10
+      value: 5.976999999999999
+    - type: precision_at_100
+      value: 0.907
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 14.878
+    - type: precision_at_5
+      value: 10.35
+    - type: recall_at_1
+      value: 25.484
+    - type: recall_at_10
+      value: 52.317
+    - type: recall_at_100
+      value: 76.701
+    - type: recall_at_1000
+      value: 91.408
+    - type: recall_at_3
+      value: 40.043
+    - type: recall_at_5
+      value: 45.879
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.719
+    - type: map_at_10
+      value: 25.269000000000002
+    - type: map_at_100
+      value: 26.442
+    - type: map_at_1000
+      value: 26.557
+    - type: map_at_3
+      value: 22.56
+    - type: map_at_5
+      value: 24.082
+    - type: mrr_at_1
+      value: 20.896
+    - type: mrr_at_10
+      value: 29.982999999999997
+    - type: mrr_at_100
+      value: 30.895
+    - type: mrr_at_1000
+      value: 30.961
+    - type: mrr_at_3
+      value: 27.239
+    - type: mrr_at_5
+      value: 28.787000000000003
+    - type: ndcg_at_1
+      value: 20.896
+    - type: ndcg_at_10
+      value: 30.814000000000004
+    - type: ndcg_at_100
+      value: 36.418
+    - type: ndcg_at_1000
+      value: 39.182
+    - type: ndcg_at_3
+      value: 25.807999999999996
+    - type: ndcg_at_5
+      value: 28.143
+    - type: precision_at_1
+      value: 20.896
+    - type: precision_at_10
+      value: 5.821
+    - type: precision_at_100
+      value: 0.991
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 12.562000000000001
+    - type: precision_at_5
+      value: 9.254
+    - type: recall_at_1
+      value: 16.719
+    - type: recall_at_10
+      value: 43.155
+    - type: recall_at_100
+      value: 67.831
+    - type: recall_at_1000
+      value: 87.617
+    - type: recall_at_3
+      value: 29.259
+    - type: recall_at_5
+      value: 35.260999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 29.398999999999997
+    - type: map_at_10
+      value: 39.876
+    - type: map_at_100
+      value: 41.205999999999996
+    - type: map_at_1000
+      value: 41.321999999999996
+    - type: map_at_3
+      value: 36.588
+    - type: map_at_5
+      value: 38.538
+    - type: mrr_at_1
+      value: 35.9
+    - type: mrr_at_10
+      value: 45.528
+    - type: mrr_at_100
+      value: 46.343
+    - type: mrr_at_1000
+      value: 46.388
+    - type: mrr_at_3
+      value: 42.862
+    - type: mrr_at_5
+      value: 44.440000000000005
+    - type: ndcg_at_1
+      value: 35.9
+    - type: ndcg_at_10
+      value: 45.987
+    - type: ndcg_at_100
+      value: 51.370000000000005
+    - type: ndcg_at_1000
+      value: 53.400000000000006
+    - type: ndcg_at_3
+      value: 40.841
+    - type: ndcg_at_5
+      value: 43.447
+    - type: precision_at_1
+      value: 35.9
+    - type: precision_at_10
+      value: 8.393
+    - type: precision_at_100
+      value: 1.283
+    - type: precision_at_1000
+      value: 0.166
+    - type: precision_at_3
+      value: 19.538
+    - type: precision_at_5
+      value: 13.975000000000001
+    - type: recall_at_1
+      value: 29.398999999999997
+    - type: recall_at_10
+      value: 58.361
+    - type: recall_at_100
+      value: 81.081
+    - type: recall_at_1000
+      value: 94.004
+    - type: recall_at_3
+      value: 43.657000000000004
+    - type: recall_at_5
+      value: 50.519999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.589
+    - type: map_at_10
+      value: 31.608999999999998
+    - type: map_at_100
+      value: 33.128
+    - type: map_at_1000
+      value: 33.247
+    - type: map_at_3
+      value: 28.671999999999997
+    - type: map_at_5
+      value: 30.233999999999998
+    - type: mrr_at_1
+      value: 26.712000000000003
+    - type: mrr_at_10
+      value: 36.713
+    - type: mrr_at_100
+      value: 37.713
+    - type: mrr_at_1000
+      value: 37.771
+    - type: mrr_at_3
+      value: 34.075
+    - type: mrr_at_5
+      value: 35.451
+    - type: ndcg_at_1
+      value: 26.712000000000003
+    - type: ndcg_at_10
+      value: 37.519999999999996
+    - type: ndcg_at_100
+      value: 43.946000000000005
+    - type: ndcg_at_1000
+      value: 46.297
+    - type: ndcg_at_3
+      value: 32.551
+    - type: ndcg_at_5
+      value: 34.660999999999994
+    - type: precision_at_1
+      value: 26.712000000000003
+    - type: precision_at_10
+      value: 7.066
+    - type: precision_at_100
+      value: 1.216
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 15.906
+    - type: precision_at_5
+      value: 11.437999999999999
+    - type: recall_at_1
+      value: 21.589
+    - type: recall_at_10
+      value: 50.090999999999994
+    - type: recall_at_100
+      value: 77.43900000000001
+    - type: recall_at_1000
+      value: 93.35900000000001
+    - type: recall_at_3
+      value: 36.028999999999996
+    - type: recall_at_5
+      value: 41.698
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.121666666666663
+    - type: map_at_10
+      value: 34.46258333333334
+    - type: map_at_100
+      value: 35.710499999999996
+    - type: map_at_1000
+      value: 35.82691666666666
+    - type: map_at_3
+      value: 31.563249999999996
+    - type: map_at_5
+      value: 33.189750000000004
+    - type: mrr_at_1
+      value: 29.66441666666667
+    - type: mrr_at_10
+      value: 38.5455
+    - type: mrr_at_100
+      value: 39.39566666666667
+    - type: mrr_at_1000
+      value: 39.45325
+    - type: mrr_at_3
+      value: 36.003333333333345
+    - type: mrr_at_5
+      value: 37.440916666666666
+    - type: ndcg_at_1
+      value: 29.66441666666667
+    - type: ndcg_at_10
+      value: 39.978416666666675
+    - type: ndcg_at_100
+      value: 45.278666666666666
+    - type: ndcg_at_1000
+      value: 47.52275
+    - type: ndcg_at_3
+      value: 35.00058333333334
+    - type: ndcg_at_5
+      value: 37.34908333333333
+    - type: precision_at_1
+      value: 29.66441666666667
+    - type: precision_at_10
+      value: 7.094500000000001
+    - type: precision_at_100
+      value: 1.1523333333333332
+    - type: precision_at_1000
+      value: 0.15358333333333332
+    - type: precision_at_3
+      value: 16.184166666666663
+    - type: precision_at_5
+      value: 11.6005
+    - type: recall_at_1
+      value: 25.121666666666663
+    - type: recall_at_10
+      value: 52.23975000000001
+    - type: recall_at_100
+      value: 75.48408333333333
+    - type: recall_at_1000
+      value: 90.95316666666668
+    - type: recall_at_3
+      value: 38.38458333333333
+    - type: recall_at_5
+      value: 44.39933333333333
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.569000000000003
+    - type: map_at_10
+      value: 30.389
+    - type: map_at_100
+      value: 31.396
+    - type: map_at_1000
+      value: 31.493
+    - type: map_at_3
+      value: 28.276
+    - type: map_at_5
+      value: 29.459000000000003
+    - type: mrr_at_1
+      value: 26.534000000000002
+    - type: mrr_at_10
+      value: 33.217999999999996
+    - type: mrr_at_100
+      value: 34.054
+    - type: mrr_at_1000
+      value: 34.12
+    - type: mrr_at_3
+      value: 31.058000000000003
+    - type: mrr_at_5
+      value: 32.330999999999996
+    - type: ndcg_at_1
+      value: 26.534000000000002
+    - type: ndcg_at_10
+      value: 34.608
+    - type: ndcg_at_100
+      value: 39.391999999999996
+    - type: ndcg_at_1000
+      value: 41.837999999999994
+    - type: ndcg_at_3
+      value: 30.564999999999998
+    - type: ndcg_at_5
+      value: 32.509
+    - type: precision_at_1
+      value: 26.534000000000002
+    - type: precision_at_10
+      value: 5.414
+    - type: precision_at_100
+      value: 0.847
+    - type: precision_at_1000
+      value: 0.11399999999999999
+    - type: precision_at_3
+      value: 12.986
+    - type: precision_at_5
+      value: 9.202
+    - type: recall_at_1
+      value: 23.569000000000003
+    - type: recall_at_10
+      value: 44.896
+    - type: recall_at_100
+      value: 66.476
+    - type: recall_at_1000
+      value: 84.548
+    - type: recall_at_3
+      value: 33.79
+    - type: recall_at_5
+      value: 38.512
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.36
+    - type: map_at_10
+      value: 23.57
+    - type: map_at_100
+      value: 24.698999999999998
+    - type: map_at_1000
+      value: 24.834999999999997
+    - type: map_at_3
+      value: 21.093
+    - type: map_at_5
+      value: 22.418
+    - type: mrr_at_1
+      value: 19.718
+    - type: mrr_at_10
+      value: 27.139999999999997
+    - type: mrr_at_100
+      value: 28.097
+    - type: mrr_at_1000
+      value: 28.177999999999997
+    - type: mrr_at_3
+      value: 24.805
+    - type: mrr_at_5
+      value: 26.121
+    - type: ndcg_at_1
+      value: 19.718
+    - type: ndcg_at_10
+      value: 28.238999999999997
+    - type: ndcg_at_100
+      value: 33.663
+    - type: ndcg_at_1000
+      value: 36.763
+    - type: ndcg_at_3
+      value: 23.747
+    - type: ndcg_at_5
+      value: 25.796000000000003
+    - type: precision_at_1
+      value: 19.718
+    - type: precision_at_10
+      value: 5.282
+    - type: precision_at_100
+      value: 0.9390000000000001
+    - type: precision_at_1000
+      value: 0.13899999999999998
+    - type: precision_at_3
+      value: 11.264000000000001
+    - type: precision_at_5
+      value: 8.341
+    - type: recall_at_1
+      value: 16.36
+    - type: recall_at_10
+      value: 38.669
+    - type: recall_at_100
+      value: 63.184
+    - type: recall_at_1000
+      value: 85.33800000000001
+    - type: recall_at_3
+      value: 26.214
+    - type: recall_at_5
+      value: 31.423000000000002
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.618999999999996
+    - type: map_at_10
+      value: 34.361999999999995
+    - type: map_at_100
+      value: 35.534
+    - type: map_at_1000
+      value: 35.634
+    - type: map_at_3
+      value: 31.402
+    - type: map_at_5
+      value: 32.815
+    - type: mrr_at_1
+      value: 30.037000000000003
+    - type: mrr_at_10
+      value: 38.284
+    - type: mrr_at_100
+      value: 39.141999999999996
+    - type: mrr_at_1000
+      value: 39.2
+    - type: mrr_at_3
+      value: 35.603
+    - type: mrr_at_5
+      value: 36.867
+    - type: ndcg_at_1
+      value: 30.037000000000003
+    - type: ndcg_at_10
+      value: 39.87
+    - type: ndcg_at_100
+      value: 45.243
+    - type: ndcg_at_1000
+      value: 47.507
+    - type: ndcg_at_3
+      value: 34.371
+    - type: ndcg_at_5
+      value: 36.521
+    - type: precision_at_1
+      value: 30.037000000000003
+    - type: precision_at_10
+      value: 6.819
+    - type: precision_at_100
+      value: 1.0699999999999998
+    - type: precision_at_1000
+      value: 0.13699999999999998
+    - type: precision_at_3
+      value: 15.392
+    - type: precision_at_5
+      value: 10.821
+    - type: recall_at_1
+      value: 25.618999999999996
+    - type: recall_at_10
+      value: 52.869
+    - type: recall_at_100
+      value: 76.395
+    - type: recall_at_1000
+      value: 92.19500000000001
+    - type: recall_at_3
+      value: 37.943
+    - type: recall_at_5
+      value: 43.342999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.283
+    - type: map_at_10
+      value: 32.155
+    - type: map_at_100
+      value: 33.724
+    - type: map_at_1000
+      value: 33.939
+    - type: map_at_3
+      value: 29.018
+    - type: map_at_5
+      value: 30.864000000000004
+    - type: mrr_at_1
+      value: 28.063
+    - type: mrr_at_10
+      value: 36.632
+    - type: mrr_at_100
+      value: 37.606
+    - type: mrr_at_1000
+      value: 37.671
+    - type: mrr_at_3
+      value: 33.992
+    - type: mrr_at_5
+      value: 35.613
+    - type: ndcg_at_1
+      value: 28.063
+    - type: ndcg_at_10
+      value: 38.024
+    - type: ndcg_at_100
+      value: 44.292
+    - type: ndcg_at_1000
+      value: 46.818
+    - type: ndcg_at_3
+      value: 32.965
+    - type: ndcg_at_5
+      value: 35.562
+    - type: precision_at_1
+      value: 28.063
+    - type: precision_at_10
+      value: 7.352
+    - type: precision_at_100
+      value: 1.514
+    - type: precision_at_1000
+      value: 0.23800000000000002
+    - type: precision_at_3
+      value: 15.481
+    - type: precision_at_5
+      value: 11.542
+    - type: recall_at_1
+      value: 23.283
+    - type: recall_at_10
+      value: 49.756
+    - type: recall_at_100
+      value: 78.05
+    - type: recall_at_1000
+      value: 93.854
+    - type: recall_at_3
+      value: 35.408
+    - type: recall_at_5
+      value: 42.187000000000005
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 19.201999999999998
+    - type: map_at_10
+      value: 26.826
+    - type: map_at_100
+      value: 27.961000000000002
+    - type: map_at_1000
+      value: 28.066999999999997
+    - type: map_at_3
+      value: 24.237000000000002
+    - type: map_at_5
+      value: 25.811
+    - type: mrr_at_1
+      value: 20.887
+    - type: mrr_at_10
+      value: 28.660000000000004
+    - type: mrr_at_100
+      value: 29.660999999999998
+    - type: mrr_at_1000
+      value: 29.731
+    - type: mrr_at_3
+      value: 26.155
+    - type: mrr_at_5
+      value: 27.68
+    - type: ndcg_at_1
+      value: 20.887
+    - type: ndcg_at_10
+      value: 31.523
+    - type: ndcg_at_100
+      value: 37.055
+    - type: ndcg_at_1000
+      value: 39.579
+    - type: ndcg_at_3
+      value: 26.529000000000003
+    - type: ndcg_at_5
+      value: 29.137
+    - type: precision_at_1
+      value: 20.887
+    - type: precision_at_10
+      value: 5.065
+    - type: precision_at_100
+      value: 0.856
+    - type: precision_at_1000
+      value: 0.11900000000000001
+    - type: precision_at_3
+      value: 11.399
+    - type: precision_at_5
+      value: 8.392
+    - type: recall_at_1
+      value: 19.201999999999998
+    - type: recall_at_10
+      value: 44.285000000000004
+    - type: recall_at_100
+      value: 69.768
+    - type: recall_at_1000
+      value: 88.302
+    - type: recall_at_3
+      value: 30.804
+    - type: recall_at_5
+      value: 37.039
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 11.244
+    - type: map_at_10
+      value: 18.956
+    - type: map_at_100
+      value: 20.674
+    - type: map_at_1000
+      value: 20.863
+    - type: map_at_3
+      value: 15.923000000000002
+    - type: map_at_5
+      value: 17.518
+    - type: mrr_at_1
+      value: 25.080999999999996
+    - type: mrr_at_10
+      value: 35.94
+    - type: mrr_at_100
+      value: 36.969
+    - type: mrr_at_1000
+      value: 37.013
+    - type: mrr_at_3
+      value: 32.617000000000004
+    - type: mrr_at_5
+      value: 34.682
+    - type: ndcg_at_1
+      value: 25.080999999999996
+    - type: ndcg_at_10
+      value: 26.539
+    - type: ndcg_at_100
+      value: 33.601
+    - type: ndcg_at_1000
+      value: 37.203
+    - type: ndcg_at_3
+      value: 21.695999999999998
+    - type: ndcg_at_5
+      value: 23.567
+    - type: precision_at_1
+      value: 25.080999999999996
+    - type: precision_at_10
+      value: 8.143
+    - type: precision_at_100
+      value: 1.5650000000000002
+    - type: precision_at_1000
+      value: 0.22300000000000003
+    - type: precision_at_3
+      value: 15.983
+    - type: precision_at_5
+      value: 12.417
+    - type: recall_at_1
+      value: 11.244
+    - type: recall_at_10
+      value: 31.457
+    - type: recall_at_100
+      value: 55.92
+    - type: recall_at_1000
+      value: 76.372
+    - type: recall_at_3
+      value: 19.784
+    - type: recall_at_5
+      value: 24.857000000000003
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 8.595
+    - type: map_at_10
+      value: 18.75
+    - type: map_at_100
+      value: 26.354
+    - type: map_at_1000
+      value: 27.912
+    - type: map_at_3
+      value: 13.794
+    - type: map_at_5
+      value: 16.021
+    - type: mrr_at_1
+      value: 65.75
+    - type: mrr_at_10
+      value: 73.837
+    - type: mrr_at_100
+      value: 74.22800000000001
+    - type: mrr_at_1000
+      value: 74.234
+    - type: mrr_at_3
+      value: 72.5
+    - type: mrr_at_5
+      value: 73.387
+    - type: ndcg_at_1
+      value: 52.625
+    - type: ndcg_at_10
+      value: 39.101
+    - type: ndcg_at_100
+      value: 43.836000000000006
+    - type: ndcg_at_1000
+      value: 51.086
+    - type: ndcg_at_3
+      value: 44.229
+    - type: ndcg_at_5
+      value: 41.555
+    - type: precision_at_1
+      value: 65.75
+    - type: precision_at_10
+      value: 30.45
+    - type: precision_at_100
+      value: 9.81
+    - type: precision_at_1000
+      value: 2.045
+    - type: precision_at_3
+      value: 48.667
+    - type: precision_at_5
+      value: 40.8
+    - type: recall_at_1
+      value: 8.595
+    - type: recall_at_10
+      value: 24.201
+    - type: recall_at_100
+      value: 50.096
+    - type: recall_at_1000
+      value: 72.677
+    - type: recall_at_3
+      value: 15.212
+    - type: recall_at_5
+      value: 18.745
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 46.565
+    - type: f1
+      value: 41.49914329345582
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 66.60000000000001
+    - type: map_at_10
+      value: 76.838
+    - type: map_at_100
+      value: 77.076
+    - type: map_at_1000
+      value: 77.09
+    - type: map_at_3
+      value: 75.545
+    - type: map_at_5
+      value: 76.39
+    - type: mrr_at_1
+      value: 71.707
+    - type: mrr_at_10
+      value: 81.514
+    - type: mrr_at_100
+      value: 81.64099999999999
+    - type: mrr_at_1000
+      value: 81.645
+    - type: mrr_at_3
+      value: 80.428
+    - type: mrr_at_5
+      value: 81.159
+    - type: ndcg_at_1
+      value: 71.707
+    - type: ndcg_at_10
+      value: 81.545
+    - type: ndcg_at_100
+      value: 82.477
+    - type: ndcg_at_1000
+      value: 82.73899999999999
+    - type: ndcg_at_3
+      value: 79.292
+    - type: ndcg_at_5
+      value: 80.599
+    - type: precision_at_1
+      value: 71.707
+    - type: precision_at_10
+      value: 10.035
+    - type: precision_at_100
+      value: 1.068
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 30.918
+    - type: precision_at_5
+      value: 19.328
+    - type: recall_at_1
+      value: 66.60000000000001
+    - type: recall_at_10
+      value: 91.353
+    - type: recall_at_100
+      value: 95.21
+    - type: recall_at_1000
+      value: 96.89999999999999
+    - type: recall_at_3
+      value: 85.188
+    - type: recall_at_5
+      value: 88.52
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 19.338
+    - type: map_at_10
+      value: 31.752000000000002
+    - type: map_at_100
+      value: 33.516
+    - type: map_at_1000
+      value: 33.694
+    - type: map_at_3
+      value: 27.716
+    - type: map_at_5
+      value: 29.67
+    - type: mrr_at_1
+      value: 38.117000000000004
+    - type: mrr_at_10
+      value: 47.323
+    - type: mrr_at_100
+      value: 48.13
+    - type: mrr_at_1000
+      value: 48.161
+    - type: mrr_at_3
+      value: 45.062000000000005
+    - type: mrr_at_5
+      value: 46.358
+    - type: ndcg_at_1
+      value: 38.117000000000004
+    - type: ndcg_at_10
+      value: 39.353
+    - type: ndcg_at_100
+      value: 46.044000000000004
+    - type: ndcg_at_1000
+      value: 49.083
+    - type: ndcg_at_3
+      value: 35.891
+    - type: ndcg_at_5
+      value: 36.661
+    - type: precision_at_1
+      value: 38.117000000000004
+    - type: precision_at_10
+      value: 11.187999999999999
+    - type: precision_at_100
+      value: 1.802
+    - type: precision_at_1000
+      value: 0.234
+    - type: precision_at_3
+      value: 24.126
+    - type: precision_at_5
+      value: 17.562
+    - type: recall_at_1
+      value: 19.338
+    - type: recall_at_10
+      value: 45.735
+    - type: recall_at_100
+      value: 71.281
+    - type: recall_at_1000
+      value: 89.537
+    - type: recall_at_3
+      value: 32.525
+    - type: recall_at_5
+      value: 37.671
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 36.995
+    - type: map_at_10
+      value: 55.032000000000004
+    - type: map_at_100
+      value: 55.86
+    - type: map_at_1000
+      value: 55.932
+    - type: map_at_3
+      value: 52.125
+    - type: map_at_5
+      value: 53.884
+    - type: mrr_at_1
+      value: 73.991
+    - type: mrr_at_10
+      value: 80.096
+    - type: mrr_at_100
+      value: 80.32000000000001
+    - type: mrr_at_1000
+      value: 80.331
+    - type: mrr_at_3
+      value: 79.037
+    - type: mrr_at_5
+      value: 79.719
+    - type: ndcg_at_1
+      value: 73.991
+    - type: ndcg_at_10
+      value: 63.786
+    - type: ndcg_at_100
+      value: 66.78
+    - type: ndcg_at_1000
+      value: 68.255
+    - type: ndcg_at_3
+      value: 59.501000000000005
+    - type: ndcg_at_5
+      value: 61.82299999999999
+    - type: precision_at_1
+      value: 73.991
+    - type: precision_at_10
+      value: 13.157
+    - type: precision_at_100
+      value: 1.552
+    - type: precision_at_1000
+      value: 0.17500000000000002
+    - type: precision_at_3
+      value: 37.519999999999996
+    - type: precision_at_5
+      value: 24.351
+    - type: recall_at_1
+      value: 36.995
+    - type: recall_at_10
+      value: 65.78699999999999
+    - type: recall_at_100
+      value: 77.583
+    - type: recall_at_1000
+      value: 87.421
+    - type: recall_at_3
+      value: 56.279999999999994
+    - type: recall_at_5
+      value: 60.878
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 86.80239999999999
+    - type: ap
+      value: 81.97305141128378
+    - type: f1
+      value: 86.76976305549273
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.166
+    - type: map_at_10
+      value: 33.396
+    - type: map_at_100
+      value: 34.588
+    - type: map_at_1000
+      value: 34.637
+    - type: map_at_3
+      value: 29.509999999999998
+    - type: map_at_5
+      value: 31.719
+    - type: mrr_at_1
+      value: 21.762
+    - type: mrr_at_10
+      value: 33.969
+    - type: mrr_at_100
+      value: 35.099000000000004
+    - type: mrr_at_1000
+      value: 35.141
+    - type: mrr_at_3
+      value: 30.148000000000003
+    - type: mrr_at_5
+      value: 32.324000000000005
+    - type: ndcg_at_1
+      value: 21.776999999999997
+    - type: ndcg_at_10
+      value: 40.306999999999995
+    - type: ndcg_at_100
+      value: 46.068
+    - type: ndcg_at_1000
+      value: 47.3
+    - type: ndcg_at_3
+      value: 32.416
+    - type: ndcg_at_5
+      value: 36.345
+    - type: precision_at_1
+      value: 21.776999999999997
+    - type: precision_at_10
+      value: 6.433
+    - type: precision_at_100
+      value: 0.932
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 13.897
+    - type: precision_at_5
+      value: 10.324
+    - type: recall_at_1
+      value: 21.166
+    - type: recall_at_10
+      value: 61.587
+    - type: recall_at_100
+      value: 88.251
+    - type: recall_at_1000
+      value: 97.727
+    - type: recall_at_3
+      value: 40.196
+    - type: recall_at_5
+      value: 49.611
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 93.04605563155496
+    - type: f1
+      value: 92.78007303978372
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 69.65116279069767
+    - type: f1
+      value: 52.75775172527262
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 70.34633490248822
+    - type: f1
+      value: 68.15345065392562
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 75.63887020847343
+    - type: f1
+      value: 76.08074680233685
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 33.77933406071333
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 32.06504927238196
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 32.20682480490871
+    - type: mrr
+      value: 33.41462721527003
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.548
+    - type: map_at_10
+      value: 13.086999999999998
+    - type: map_at_100
+      value: 16.698
+    - type: map_at_1000
+      value: 18.151999999999997
+    - type: map_at_3
+      value: 9.576
+    - type: map_at_5
+      value: 11.175
+    - type: mrr_at_1
+      value: 44.272
+    - type: mrr_at_10
+      value: 53.635999999999996
+    - type: mrr_at_100
+      value: 54.228
+    - type: mrr_at_1000
+      value: 54.26499999999999
+    - type: mrr_at_3
+      value: 51.754
+    - type: mrr_at_5
+      value: 53.086
+    - type: ndcg_at_1
+      value: 42.724000000000004
+    - type: ndcg_at_10
+      value: 34.769
+    - type: ndcg_at_100
+      value: 32.283
+    - type: ndcg_at_1000
+      value: 40.843
+    - type: ndcg_at_3
+      value: 39.852
+    - type: ndcg_at_5
+      value: 37.858999999999995
+    - type: precision_at_1
+      value: 44.272
+    - type: precision_at_10
+      value: 26.068
+    - type: precision_at_100
+      value: 8.328000000000001
+    - type: precision_at_1000
+      value: 2.1
+    - type: precision_at_3
+      value: 37.874
+    - type: precision_at_5
+      value: 33.065
+    - type: recall_at_1
+      value: 5.548
+    - type: recall_at_10
+      value: 16.936999999999998
+    - type: recall_at_100
+      value: 33.72
+    - type: recall_at_1000
+      value: 64.348
+    - type: recall_at_3
+      value: 10.764999999999999
+    - type: recall_at_5
+      value: 13.361
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.008
+    - type: map_at_10
+      value: 42.675000000000004
+    - type: map_at_100
+      value: 43.85
+    - type: map_at_1000
+      value: 43.884
+    - type: map_at_3
+      value: 38.286
+    - type: map_at_5
+      value: 40.78
+    - type: mrr_at_1
+      value: 31.518
+    - type: mrr_at_10
+      value: 45.015
+    - type: mrr_at_100
+      value: 45.924
+    - type: mrr_at_1000
+      value: 45.946999999999996
+    - type: mrr_at_3
+      value: 41.348
+    - type: mrr_at_5
+      value: 43.428
+    - type: ndcg_at_1
+      value: 31.489
+    - type: ndcg_at_10
+      value: 50.285999999999994
+    - type: ndcg_at_100
+      value: 55.291999999999994
+    - type: ndcg_at_1000
+      value: 56.05
+    - type: ndcg_at_3
+      value: 41.976
+    - type: ndcg_at_5
+      value: 46.103
+    - type: precision_at_1
+      value: 31.489
+    - type: precision_at_10
+      value: 8.456
+    - type: precision_at_100
+      value: 1.125
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_3
+      value: 19.09
+    - type: precision_at_5
+      value: 13.841000000000001
+    - type: recall_at_1
+      value: 28.008
+    - type: recall_at_10
+      value: 71.21499999999999
+    - type: recall_at_100
+      value: 92.99
+    - type: recall_at_1000
+      value: 98.578
+    - type: recall_at_3
+      value: 49.604
+    - type: recall_at_5
+      value: 59.094
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 70.351
+    - type: map_at_10
+      value: 84.163
+    - type: map_at_100
+      value: 84.785
+    - type: map_at_1000
+      value: 84.801
+    - type: map_at_3
+      value: 81.16
+    - type: map_at_5
+      value: 83.031
+    - type: mrr_at_1
+      value: 80.96
+    - type: mrr_at_10
+      value: 87.241
+    - type: mrr_at_100
+      value: 87.346
+    - type: mrr_at_1000
+      value: 87.347
+    - type: mrr_at_3
+      value: 86.25699999999999
+    - type: mrr_at_5
+      value: 86.907
+    - type: ndcg_at_1
+      value: 80.97
+    - type: ndcg_at_10
+      value: 88.017
+    - type: ndcg_at_100
+      value: 89.241
+    - type: ndcg_at_1000
+      value: 89.34299999999999
+    - type: ndcg_at_3
+      value: 85.053
+    - type: ndcg_at_5
+      value: 86.663
+    - type: precision_at_1
+      value: 80.97
+    - type: precision_at_10
+      value: 13.358
+    - type: precision_at_100
+      value: 1.525
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 37.143
+    - type: precision_at_5
+      value: 24.451999999999998
+    - type: recall_at_1
+      value: 70.351
+    - type: recall_at_10
+      value: 95.39800000000001
+    - type: recall_at_100
+      value: 99.55199999999999
+    - type: recall_at_1000
+      value: 99.978
+    - type: recall_at_3
+      value: 86.913
+    - type: recall_at_5
+      value: 91.448
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 55.62406719814139
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 61.386700035141736
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.618
+    - type: map_at_10
+      value: 12.920000000000002
+    - type: map_at_100
+      value: 15.304
+    - type: map_at_1000
+      value: 15.656999999999998
+    - type: map_at_3
+      value: 9.187
+    - type: map_at_5
+      value: 10.937
+    - type: mrr_at_1
+      value: 22.8
+    - type: mrr_at_10
+      value: 35.13
+    - type: mrr_at_100
+      value: 36.239
+    - type: mrr_at_1000
+      value: 36.291000000000004
+    - type: mrr_at_3
+      value: 31.917
+    - type: mrr_at_5
+      value: 33.787
+    - type: ndcg_at_1
+      value: 22.8
+    - type: ndcg_at_10
+      value: 21.382
+    - type: ndcg_at_100
+      value: 30.257
+    - type: ndcg_at_1000
+      value: 36.001
+    - type: ndcg_at_3
+      value: 20.43
+    - type: ndcg_at_5
+      value: 17.622
+    - type: precision_at_1
+      value: 22.8
+    - type: precision_at_10
+      value: 11.26
+    - type: precision_at_100
+      value: 2.405
+    - type: precision_at_1000
+      value: 0.377
+    - type: precision_at_3
+      value: 19.633
+    - type: precision_at_5
+      value: 15.68
+    - type: recall_at_1
+      value: 4.618
+    - type: recall_at_10
+      value: 22.811999999999998
+    - type: recall_at_100
+      value: 48.787000000000006
+    - type: recall_at_1000
+      value: 76.63799999999999
+    - type: recall_at_3
+      value: 11.952
+    - type: recall_at_5
+      value: 15.892000000000001
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.01529458252244
+    - type: cos_sim_spearman
+      value: 77.92985224770254
+    - type: euclidean_pearson
+      value: 81.04251429422487
+    - type: euclidean_spearman
+      value: 77.92838490549133
+    - type: manhattan_pearson
+      value: 80.95892251458979
+    - type: manhattan_spearman
+      value: 77.81028089705941
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.97885282534388
+    - type: cos_sim_spearman
+      value: 75.1221970851712
+    - type: euclidean_pearson
+      value: 80.34455956720097
+    - type: euclidean_spearman
+      value: 74.5894274239938
+    - type: manhattan_pearson
+      value: 80.38999766325465
+    - type: manhattan_spearman
+      value: 74.68524557166975
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.95746064915672
+    - type: cos_sim_spearman
+      value: 85.08683458043946
+    - type: euclidean_pearson
+      value: 84.56699492836385
+    - type: euclidean_spearman
+      value: 85.66089116133713
+    - type: manhattan_pearson
+      value: 84.47553323458541
+    - type: manhattan_spearman
+      value: 85.56142206781472
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.71377893595067
+    - type: cos_sim_spearman
+      value: 81.03453291428589
+    - type: euclidean_pearson
+      value: 82.57136298308613
+    - type: euclidean_spearman
+      value: 81.15839961890875
+    - type: manhattan_pearson
+      value: 82.55157879373837
+    - type: manhattan_spearman
+      value: 81.1540163767054
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.64197832372373
+    - type: cos_sim_spearman
+      value: 88.31966852492485
+    - type: euclidean_pearson
+      value: 87.98692129976983
+    - type: euclidean_spearman
+      value: 88.6247340837856
+    - type: manhattan_pearson
+      value: 87.90437827826412
+    - type: manhattan_spearman
+      value: 88.56278787131457
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.84159950146693
+    - type: cos_sim_spearman
+      value: 83.90678384140168
+    - type: euclidean_pearson
+      value: 83.19005018860221
+    - type: euclidean_spearman
+      value: 84.16260415876295
+    - type: manhattan_pearson
+      value: 83.05030612994494
+    - type: manhattan_spearman
+      value: 83.99605629718336
+  - 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: 87.49935350176666
+    - type: cos_sim_spearman
+      value: 87.59086606735383
+    - type: euclidean_pearson
+      value: 88.06537181129983
+    - type: euclidean_spearman
+      value: 87.6687448086014
+    - type: manhattan_pearson
+      value: 87.96599131972935
+    - type: manhattan_spearman
+      value: 87.63295748969642
+  - 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: 67.68232799482763
+    - type: cos_sim_spearman
+      value: 67.99930378085793
+    - type: euclidean_pearson
+      value: 68.50275360001696
+    - type: euclidean_spearman
+      value: 67.81588179309259
+    - type: manhattan_pearson
+      value: 68.5892154749763
+    - type: manhattan_spearman
+      value: 67.84357259640682
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.37049618406554
+    - type: cos_sim_spearman
+      value: 85.57014313159492
+    - type: euclidean_pearson
+      value: 85.57469513908282
+    - type: euclidean_spearman
+      value: 85.661948135258
+    - type: manhattan_pearson
+      value: 85.36866831229028
+    - type: manhattan_spearman
+      value: 85.5043455368843
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 84.83259065376154
+    - type: mrr
+      value: 95.58455433455433
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 58.817
+    - type: map_at_10
+      value: 68.459
+    - type: map_at_100
+      value: 68.951
+    - type: map_at_1000
+      value: 68.979
+    - type: map_at_3
+      value: 65.791
+    - type: map_at_5
+      value: 67.583
+    - type: mrr_at_1
+      value: 61.667
+    - type: mrr_at_10
+      value: 69.368
+    - type: mrr_at_100
+      value: 69.721
+    - type: mrr_at_1000
+      value: 69.744
+    - type: mrr_at_3
+      value: 67.278
+    - type: mrr_at_5
+      value: 68.611
+    - type: ndcg_at_1
+      value: 61.667
+    - type: ndcg_at_10
+      value: 72.70100000000001
+    - type: ndcg_at_100
+      value: 74.928
+    - type: ndcg_at_1000
+      value: 75.553
+    - type: ndcg_at_3
+      value: 68.203
+    - type: ndcg_at_5
+      value: 70.804
+    - type: precision_at_1
+      value: 61.667
+    - type: precision_at_10
+      value: 9.533
+    - type: precision_at_100
+      value: 1.077
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 26.444000000000003
+    - type: precision_at_5
+      value: 17.599999999999998
+    - type: recall_at_1
+      value: 58.817
+    - type: recall_at_10
+      value: 84.789
+    - type: recall_at_100
+      value: 95.0
+    - type: recall_at_1000
+      value: 99.667
+    - type: recall_at_3
+      value: 72.8
+    - type: recall_at_5
+      value: 79.294
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.8108910891089
+    - type: cos_sim_ap
+      value: 95.5743678558349
+    - type: cos_sim_f1
+      value: 90.43133366385722
+    - type: cos_sim_precision
+      value: 89.67551622418878
+    - type: cos_sim_recall
+      value: 91.2
+    - type: dot_accuracy
+      value: 99.75841584158415
+    - type: dot_ap
+      value: 94.00786363627253
+    - type: dot_f1
+      value: 87.51910341314316
+    - type: dot_precision
+      value: 89.20041536863967
+    - type: dot_recall
+      value: 85.9
+    - type: euclidean_accuracy
+      value: 99.81485148514851
+    - type: euclidean_ap
+      value: 95.4752113136905
+    - type: euclidean_f1
+      value: 90.44334975369456
+    - type: euclidean_precision
+      value: 89.126213592233
+    - type: euclidean_recall
+      value: 91.8
+    - type: manhattan_accuracy
+      value: 99.81584158415842
+    - type: manhattan_ap
+      value: 95.5163172682464
+    - type: manhattan_f1
+      value: 90.51987767584097
+    - type: manhattan_precision
+      value: 92.3076923076923
+    - type: manhattan_recall
+      value: 88.8
+    - type: max_accuracy
+      value: 99.81584158415842
+    - type: max_ap
+      value: 95.5743678558349
+    - type: max_f1
+      value: 90.51987767584097
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 62.63235986949449
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 36.334795589585575
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 52.02955214518782
+    - type: mrr
+      value: 52.8004838298956
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.63769566275453
+    - type: cos_sim_spearman
+      value: 30.422379185989335
+    - type: dot_pearson
+      value: 26.88493071882256
+    - type: dot_spearman
+      value: 26.505249740971305
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.21
+    - type: map_at_10
+      value: 1.654
+    - type: map_at_100
+      value: 10.095
+    - type: map_at_1000
+      value: 25.808999999999997
+    - type: map_at_3
+      value: 0.594
+    - type: map_at_5
+      value: 0.9289999999999999
+    - type: mrr_at_1
+      value: 78.0
+    - type: mrr_at_10
+      value: 87.019
+    - type: mrr_at_100
+      value: 87.019
+    - type: mrr_at_1000
+      value: 87.019
+    - type: mrr_at_3
+      value: 86.333
+    - type: mrr_at_5
+      value: 86.733
+    - type: ndcg_at_1
+      value: 73.0
+    - type: ndcg_at_10
+      value: 66.52900000000001
+    - type: ndcg_at_100
+      value: 53.433
+    - type: ndcg_at_1000
+      value: 51.324000000000005
+    - type: ndcg_at_3
+      value: 72.02199999999999
+    - type: ndcg_at_5
+      value: 69.696
+    - type: precision_at_1
+      value: 78.0
+    - type: precision_at_10
+      value: 70.39999999999999
+    - type: precision_at_100
+      value: 55.46
+    - type: precision_at_1000
+      value: 22.758
+    - type: precision_at_3
+      value: 76.667
+    - type: precision_at_5
+      value: 74.0
+    - type: recall_at_1
+      value: 0.21
+    - type: recall_at_10
+      value: 1.8849999999999998
+    - type: recall_at_100
+      value: 13.801
+    - type: recall_at_1000
+      value: 49.649
+    - type: recall_at_3
+      value: 0.632
+    - type: recall_at_5
+      value: 1.009
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 1.797
+    - type: map_at_10
+      value: 9.01
+    - type: map_at_100
+      value: 14.682
+    - type: map_at_1000
+      value: 16.336000000000002
+    - type: map_at_3
+      value: 4.546
+    - type: map_at_5
+      value: 5.9270000000000005
+    - type: mrr_at_1
+      value: 24.490000000000002
+    - type: mrr_at_10
+      value: 41.156
+    - type: mrr_at_100
+      value: 42.392
+    - type: mrr_at_1000
+      value: 42.408
+    - type: mrr_at_3
+      value: 38.775999999999996
+    - type: mrr_at_5
+      value: 40.102
+    - type: ndcg_at_1
+      value: 21.429000000000002
+    - type: ndcg_at_10
+      value: 22.222
+    - type: ndcg_at_100
+      value: 34.405
+    - type: ndcg_at_1000
+      value: 46.599000000000004
+    - type: ndcg_at_3
+      value: 25.261
+    - type: ndcg_at_5
+      value: 22.695999999999998
+    - type: precision_at_1
+      value: 24.490000000000002
+    - type: precision_at_10
+      value: 19.796
+    - type: precision_at_100
+      value: 7.306
+    - type: precision_at_1000
+      value: 1.5350000000000001
+    - type: precision_at_3
+      value: 27.211000000000002
+    - type: precision_at_5
+      value: 22.857
+    - type: recall_at_1
+      value: 1.797
+    - type: recall_at_10
+      value: 15.706000000000001
+    - type: recall_at_100
+      value: 46.412
+    - type: recall_at_1000
+      value: 83.159
+    - type: recall_at_3
+      value: 6.1370000000000005
+    - type: recall_at_5
+      value: 8.599
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 70.3302
+    - type: ap
+      value: 14.169121204575601
+    - type: f1
+      value: 54.229345975274235
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 58.22297679683077
+    - type: f1
+      value: 58.62984908377875
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 49.952922428464255
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 84.68140907194373
+    - type: cos_sim_ap
+      value: 70.12180123666836
+    - type: cos_sim_f1
+      value: 65.77501791258658
+    - type: cos_sim_precision
+      value: 60.07853403141361
+    - type: cos_sim_recall
+      value: 72.66490765171504
+    - type: dot_accuracy
+      value: 81.92167848840674
+    - type: dot_ap
+      value: 60.49837581423469
+    - type: dot_f1
+      value: 58.44186046511628
+    - type: dot_precision
+      value: 52.24532224532224
+    - type: dot_recall
+      value: 66.3060686015831
+    - type: euclidean_accuracy
+      value: 84.73505394289802
+    - type: euclidean_ap
+      value: 70.3278904593286
+    - type: euclidean_f1
+      value: 65.98851124940161
+    - type: euclidean_precision
+      value: 60.38107752956636
+    - type: euclidean_recall
+      value: 72.74406332453826
+    - type: manhattan_accuracy
+      value: 84.73505394289802
+    - type: manhattan_ap
+      value: 70.00737738537337
+    - type: manhattan_f1
+      value: 65.80150784822642
+    - type: manhattan_precision
+      value: 61.892583120204606
+    - type: manhattan_recall
+      value: 70.23746701846966
+    - type: max_accuracy
+      value: 84.73505394289802
+    - type: max_ap
+      value: 70.3278904593286
+    - type: max_f1
+      value: 65.98851124940161
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.44258159661582
+    - type: cos_sim_ap
+      value: 84.91926704880888
+    - type: cos_sim_f1
+      value: 77.07651086632926
+    - type: cos_sim_precision
+      value: 74.5894554883319
+    - type: cos_sim_recall
+      value: 79.73514012935017
+    - type: dot_accuracy
+      value: 85.88116583226608
+    - type: dot_ap
+      value: 78.9753854779923
+    - type: dot_f1
+      value: 72.17757637979255
+    - type: dot_precision
+      value: 66.80647486729143
+    - type: dot_recall
+      value: 78.48783492454572
+    - type: euclidean_accuracy
+      value: 88.5299025885823
+    - type: euclidean_ap
+      value: 85.08006075642194
+    - type: euclidean_f1
+      value: 77.29637336504163
+    - type: euclidean_precision
+      value: 74.69836253950014
+    - type: euclidean_recall
+      value: 80.08161379735141
+    - type: manhattan_accuracy
+      value: 88.55124771995187
+    - type: manhattan_ap
+      value: 85.00941529932851
+    - type: manhattan_f1
+      value: 77.33100233100232
+    - type: manhattan_precision
+      value: 73.37572573956317
+    - type: manhattan_recall
+      value: 81.73698798891284
+    - type: max_accuracy
+      value: 88.55124771995187
+    - type: max_ap
+      value: 85.08006075642194
+    - type: max_f1
+      value: 77.33100233100232
+language:
+- en
+license: mit
+---
+
+# gte-small
+
+General Text Embeddings (GTE) model. [Towards General Text Embeddings with Multi-stage Contrastive Learning](https://arxiv.org/abs/2308.03281)
+
+The GTE models are trained by Alibaba DAMO Academy. They are mainly based on the BERT framework and currently offer three different sizes of models, including [GTE-large](https://huggingface.co/thenlper/gte-large), [GTE-base](https://huggingface.co/thenlper/gte-base), and [GTE-small](https://huggingface.co/thenlper/gte-small). The GTE models are trained on a large-scale corpus of relevance text pairs, covering a wide range of domains and scenarios. This enables the GTE models to be applied to various downstream tasks of text embeddings, including **information retrieval**, **semantic textual similarity**, **text reranking**, etc.
+
+## Metrics
+
+We compared the performance of the GTE models with other popular text embedding models on the MTEB benchmark. For more detailed comparison results, please refer to the [MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard).
+
+
+
+| Model Name | Model Size (GB) | Dimension | Sequence Length | Average (56) | Clustering (11) | Pair Classification (3) | Reranking (4) | Retrieval (15) | STS (10) | Summarization (1) | Classification (12) |
+|:----:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
+| [**gte-large**](https://huggingface.co/thenlper/gte-large) | 0.67 | 1024 | 512 | **63.13** | 46.84 | 85.00 | 59.13 | 52.22 | 83.35 | 31.66 | 73.33 |
+| [**gte-base**](https://huggingface.co/thenlper/gte-base) 	| 0.22 | 768 | 512 | **62.39** | 46.2 | 84.57 | 58.61 | 51.14 | 82.3 | 31.17 | 73.01 |
+| [e5-large-v2](https://huggingface.co/intfloat/e5-large-v2) | 1.34 | 1024| 512 | 62.25 | 44.49 | 86.03 | 56.61 | 50.56 | 82.05 | 30.19 | 75.24 |
+| [e5-base-v2](https://huggingface.co/intfloat/e5-base-v2) | 0.44 | 768 | 512 | 61.5 | 43.80 | 85.73 | 55.91 | 50.29 | 81.05 | 30.28 | 73.84 |
+| [**gte-small**](https://huggingface.co/thenlper/gte-small) | 0.07 | 384 | 512 | **61.36** | 44.89 | 83.54 | 57.7 | 49.46 | 82.07 | 30.42 | 72.31 |
+| [text-embedding-ada-002](https://platform.openai.com/docs/guides/embeddings) | - | 1536 | 8192 | 60.99 | 45.9 | 84.89 | 56.32 | 49.25 | 80.97 | 30.8 | 70.93 |
+| [e5-small-v2](https://huggingface.co/intfloat/e5-base-v2) | 0.13 | 384 | 512 | 59.93 | 39.92 | 84.67 | 54.32 | 49.04 | 80.39 | 31.16 | 72.94 |
+| [sentence-t5-xxl](https://huggingface.co/sentence-transformers/sentence-t5-xxl) | 9.73 | 768 | 512 | 59.51 | 43.72 | 85.06 | 56.42 | 42.24 | 82.63 | 30.08 | 73.42 |
+| [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) 	| 0.44 | 768 | 514 	| 57.78 | 43.69 | 83.04 | 59.36 | 43.81 | 80.28 | 27.49 | 65.07 |
+| [sgpt-bloom-7b1-msmarco](https://huggingface.co/bigscience/sgpt-bloom-7b1-msmarco) 	| 28.27 | 4096 | 2048 | 57.59 | 38.93 | 81.9 | 55.65 | 48.22 | 77.74 | 33.6 | 66.19 |
+| [all-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2) 	| 0.13 | 384 | 512 	| 56.53 | 41.81 | 82.41 | 58.44 | 42.69 | 79.8 | 27.9 | 63.21 |
+| [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) 	| 0.09 | 384 | 512 	| 56.26 | 42.35 | 82.37 | 58.04 | 41.95 | 78.9 | 30.81 | 63.05 |
+| [contriever-base-msmarco](https://huggingface.co/nthakur/contriever-base-msmarco) 	| 0.44 | 768 | 512 	| 56.00 | 41.1 	| 82.54 | 53.14 | 41.88 | 76.51 | 30.36 | 66.68 |
+| [sentence-t5-base](https://huggingface.co/sentence-transformers/sentence-t5-base) 	| 0.22 | 768 | 512 	| 55.27 | 40.21 | 85.18 | 53.09 | 33.63 | 81.14 | 31.39 | 69.81 |
+
+
+## Usage
+
+Code example
+
+```python
+import torch.nn.functional as F
+from torch import Tensor
+from transformers import AutoTokenizer, AutoModel
+
+def average_pool(last_hidden_states: Tensor,
+                 attention_mask: Tensor) -> Tensor:
+    last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0)
+    return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None]
+
+input_texts = [
+    "what is the capital of China?",
+    "how to implement quick sort in python?",
+    "Beijing",
+    "sorting algorithms"
+]
+
+tokenizer = AutoTokenizer.from_pretrained("thenlper/gte-small")
+model = AutoModel.from_pretrained("thenlper/gte-small")
+
+# Tokenize the input texts
+batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')
+
+outputs = model(**batch_dict)
+embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask'])
+
+# (Optionally) normalize embeddings
+embeddings = F.normalize(embeddings, p=2, dim=1)
+scores = (embeddings[:1] @ embeddings[1:].T) * 100
+print(scores.tolist())
+```
+
+Use with sentence-transformers:
+```python
+from sentence_transformers import SentenceTransformer
+from sentence_transformers.util import cos_sim
+
+sentences = ['That is a happy person', 'That is a very happy person']
+
+model = SentenceTransformer('thenlper/gte-large')
+embeddings = model.encode(sentences)
+print(cos_sim(embeddings[0], embeddings[1]))
+```
+
+### Limitation
+
+This model exclusively caters to English texts, and any lengthy texts will be truncated to a maximum of 512 tokens.
+
+### Citation
+
+If you find our paper or models helpful, please consider citing them as follows:
+
+```
+@misc{li2023general,
+      title={Towards General Text Embeddings with Multi-stage Contrastive Learning}, 
+      author={Zehan Li and Xin Zhang and Yanzhao Zhang and Dingkun Long and Pengjun Xie and Meishan Zhang},
+      year={2023},
+      eprint={2308.03281},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```

config.json

@@ -0,0 +1,24 @@
+{
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float16",
+  "transformers_version": "4.28.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

modules.json

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+[
+    {
+      "idx": 0,
+      "name": "0",
+      "path": "",
+      "type": "sentence_transformers.models.Transformer"
+    },
+    {
+      "idx": 1,
+      "name": "1",
+      "path": "1_Pooling",
+      "type": "sentence_transformers.models.Pooling"
+    },
+    {
+      "idx": 2,
+      "name": "2",
+      "path": "2_Normalize",
+      "type": "sentence_transformers.models.Normalize"
+    }
+]

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:344099675ecefb2dc886e6dcc1fba7ccc0c66dbf455e8aa289035ee8d688f125
+size 66751231

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+    "max_seq_length": 512,
+    "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,7 @@
+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

@@ -0,0 +1,15 @@
+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}