e5-base-v2

.gitattributes

@@ -25,7 +25,6 @@
 *.safetensors filter=lfs diff=lfs merge=lfs -text
 saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
 *.tflite filter=lfs diff=lfs merge=lfs -text
 *.tgz filter=lfs diff=lfs merge=lfs -text
 *.wasm filter=lfs diff=lfs merge=lfs -text

1_Pooling/config.json

@@ -0,0 +1,7 @@
+{
+    "word_embedding_dimension": 768,
+    "pooling_mode_cls_token": false,
+    "pooling_mode_mean_tokens": true,
+    "pooling_mode_max_tokens": false,
+    "pooling_mode_mean_sqrt_len_tokens": false
+}

README.md

@@ -1,3 +1,2723 @@
 ---
+tags:
+- mteb
+- Sentence Transformers
+- sentence-similarity
+- sentence-transformers
+model-index:
+- name: e5-base-v2
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 77.77611940298506
+    - type: ap
+      value: 42.052710266606056
+    - type: f1
+      value: 72.12040628266567
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 92.81012500000001
+    - type: ap
+      value: 89.4213700757244
+    - type: f1
+      value: 92.8039091197065
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 46.711999999999996
+    - type: f1
+      value: 46.11544975436018
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.186
+    - type: map_at_10
+      value: 36.632999999999996
+    - type: map_at_100
+      value: 37.842
+    - type: map_at_1000
+      value: 37.865
+    - type: map_at_3
+      value: 32.278
+    - type: map_at_5
+      value: 34.760999999999996
+    - type: mrr_at_1
+      value: 23.400000000000002
+    - type: mrr_at_10
+      value: 36.721
+    - type: mrr_at_100
+      value: 37.937
+    - type: mrr_at_1000
+      value: 37.96
+    - type: mrr_at_3
+      value: 32.302
+    - type: mrr_at_5
+      value: 34.894
+    - type: ndcg_at_1
+      value: 23.186
+    - type: ndcg_at_10
+      value: 44.49
+    - type: ndcg_at_100
+      value: 50.065000000000005
+    - type: ndcg_at_1000
+      value: 50.629999999999995
+    - type: ndcg_at_3
+      value: 35.461
+    - type: ndcg_at_5
+      value: 39.969
+    - type: precision_at_1
+      value: 23.186
+    - type: precision_at_10
+      value: 6.97
+    - type: precision_at_100
+      value: 0.951
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 14.912
+    - type: precision_at_5
+      value: 11.152
+    - type: recall_at_1
+      value: 23.186
+    - type: recall_at_10
+      value: 69.70100000000001
+    - type: recall_at_100
+      value: 95.092
+    - type: recall_at_1000
+      value: 99.431
+    - type: recall_at_3
+      value: 44.737
+    - type: recall_at_5
+      value: 55.761
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 46.10312401440185
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 39.67275326095384
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 58.97793816337376
+    - type: mrr
+      value: 72.76832431957087
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.11646947018187
+    - type: cos_sim_spearman
+      value: 81.40064994975234
+    - type: euclidean_pearson
+      value: 82.37355689019232
+    - type: euclidean_spearman
+      value: 81.6777646977348
+    - type: manhattan_pearson
+      value: 82.61101422716945
+    - type: manhattan_spearman
+      value: 81.80427360442245
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 83.52922077922076
+    - type: f1
+      value: 83.45298679360866
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 37.495115019668496
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 32.724792944166765
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.361000000000004
+    - type: map_at_10
+      value: 43.765
+    - type: map_at_100
+      value: 45.224
+    - type: map_at_1000
+      value: 45.35
+    - type: map_at_3
+      value: 40.353
+    - type: map_at_5
+      value: 42.195
+    - type: mrr_at_1
+      value: 40.629
+    - type: mrr_at_10
+      value: 50.458000000000006
+    - type: mrr_at_100
+      value: 51.06699999999999
+    - type: mrr_at_1000
+      value: 51.12
+    - type: mrr_at_3
+      value: 47.902
+    - type: mrr_at_5
+      value: 49.447
+    - type: ndcg_at_1
+      value: 40.629
+    - type: ndcg_at_10
+      value: 50.376
+    - type: ndcg_at_100
+      value: 55.065
+    - type: ndcg_at_1000
+      value: 57.196000000000005
+    - type: ndcg_at_3
+      value: 45.616
+    - type: ndcg_at_5
+      value: 47.646
+    - type: precision_at_1
+      value: 40.629
+    - type: precision_at_10
+      value: 9.785
+    - type: precision_at_100
+      value: 1.562
+    - type: precision_at_1000
+      value: 0.2
+    - type: precision_at_3
+      value: 22.031
+    - type: precision_at_5
+      value: 15.737000000000002
+    - type: recall_at_1
+      value: 32.361000000000004
+    - type: recall_at_10
+      value: 62.214000000000006
+    - type: recall_at_100
+      value: 81.464
+    - type: recall_at_1000
+      value: 95.905
+    - type: recall_at_3
+      value: 47.5
+    - type: recall_at_5
+      value: 53.69500000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.971
+    - type: map_at_10
+      value: 37.444
+    - type: map_at_100
+      value: 38.607
+    - type: map_at_1000
+      value: 38.737
+    - type: map_at_3
+      value: 34.504000000000005
+    - type: map_at_5
+      value: 36.234
+    - type: mrr_at_1
+      value: 35.35
+    - type: mrr_at_10
+      value: 43.441
+    - type: mrr_at_100
+      value: 44.147999999999996
+    - type: mrr_at_1000
+      value: 44.196000000000005
+    - type: mrr_at_3
+      value: 41.285
+    - type: mrr_at_5
+      value: 42.552
+    - type: ndcg_at_1
+      value: 35.35
+    - type: ndcg_at_10
+      value: 42.903999999999996
+    - type: ndcg_at_100
+      value: 47.406
+    - type: ndcg_at_1000
+      value: 49.588
+    - type: ndcg_at_3
+      value: 38.778
+    - type: ndcg_at_5
+      value: 40.788000000000004
+    - type: precision_at_1
+      value: 35.35
+    - type: precision_at_10
+      value: 8.083
+    - type: precision_at_100
+      value: 1.313
+    - type: precision_at_1000
+      value: 0.18
+    - type: precision_at_3
+      value: 18.769
+    - type: precision_at_5
+      value: 13.439
+    - type: recall_at_1
+      value: 27.971
+    - type: recall_at_10
+      value: 52.492000000000004
+    - type: recall_at_100
+      value: 71.642
+    - type: recall_at_1000
+      value: 85.488
+    - type: recall_at_3
+      value: 40.1
+    - type: recall_at_5
+      value: 45.800000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 39.898
+    - type: map_at_10
+      value: 51.819
+    - type: map_at_100
+      value: 52.886
+    - type: map_at_1000
+      value: 52.941
+    - type: map_at_3
+      value: 48.619
+    - type: map_at_5
+      value: 50.493
+    - type: mrr_at_1
+      value: 45.391999999999996
+    - type: mrr_at_10
+      value: 55.230000000000004
+    - type: mrr_at_100
+      value: 55.887
+    - type: mrr_at_1000
+      value: 55.916
+    - type: mrr_at_3
+      value: 52.717000000000006
+    - type: mrr_at_5
+      value: 54.222
+    - type: ndcg_at_1
+      value: 45.391999999999996
+    - type: ndcg_at_10
+      value: 57.586999999999996
+    - type: ndcg_at_100
+      value: 61.745000000000005
+    - type: ndcg_at_1000
+      value: 62.83800000000001
+    - type: ndcg_at_3
+      value: 52.207
+    - type: ndcg_at_5
+      value: 54.925999999999995
+    - type: precision_at_1
+      value: 45.391999999999996
+    - type: precision_at_10
+      value: 9.21
+    - type: precision_at_100
+      value: 1.226
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 23.177
+    - type: precision_at_5
+      value: 16.038
+    - type: recall_at_1
+      value: 39.898
+    - type: recall_at_10
+      value: 71.18900000000001
+    - type: recall_at_100
+      value: 89.082
+    - type: recall_at_1000
+      value: 96.865
+    - type: recall_at_3
+      value: 56.907
+    - type: recall_at_5
+      value: 63.397999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.706
+    - type: map_at_10
+      value: 30.818
+    - type: map_at_100
+      value: 32.038
+    - type: map_at_1000
+      value: 32.123000000000005
+    - type: map_at_3
+      value: 28.077
+    - type: map_at_5
+      value: 29.709999999999997
+    - type: mrr_at_1
+      value: 24.407
+    - type: mrr_at_10
+      value: 32.555
+    - type: mrr_at_100
+      value: 33.692
+    - type: mrr_at_1000
+      value: 33.751
+    - type: mrr_at_3
+      value: 29.848999999999997
+    - type: mrr_at_5
+      value: 31.509999999999998
+    - type: ndcg_at_1
+      value: 24.407
+    - type: ndcg_at_10
+      value: 35.624
+    - type: ndcg_at_100
+      value: 41.454
+    - type: ndcg_at_1000
+      value: 43.556
+    - type: ndcg_at_3
+      value: 30.217
+    - type: ndcg_at_5
+      value: 33.111000000000004
+    - type: precision_at_1
+      value: 24.407
+    - type: precision_at_10
+      value: 5.548
+    - type: precision_at_100
+      value: 0.8869999999999999
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 12.731
+    - type: precision_at_5
+      value: 9.22
+    - type: recall_at_1
+      value: 22.706
+    - type: recall_at_10
+      value: 48.772
+    - type: recall_at_100
+      value: 75.053
+    - type: recall_at_1000
+      value: 90.731
+    - type: recall_at_3
+      value: 34.421
+    - type: recall_at_5
+      value: 41.427
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 13.424
+    - type: map_at_10
+      value: 21.09
+    - type: map_at_100
+      value: 22.264999999999997
+    - type: map_at_1000
+      value: 22.402
+    - type: map_at_3
+      value: 18.312
+    - type: map_at_5
+      value: 19.874
+    - type: mrr_at_1
+      value: 16.915
+    - type: mrr_at_10
+      value: 25.258000000000003
+    - type: mrr_at_100
+      value: 26.228
+    - type: mrr_at_1000
+      value: 26.31
+    - type: mrr_at_3
+      value: 22.492
+    - type: mrr_at_5
+      value: 24.04
+    - type: ndcg_at_1
+      value: 16.915
+    - type: ndcg_at_10
+      value: 26.266000000000002
+    - type: ndcg_at_100
+      value: 32.08
+    - type: ndcg_at_1000
+      value: 35.086
+    - type: ndcg_at_3
+      value: 21.049
+    - type: ndcg_at_5
+      value: 23.508000000000003
+    - type: precision_at_1
+      value: 16.915
+    - type: precision_at_10
+      value: 5.1
+    - type: precision_at_100
+      value: 0.9329999999999999
+    - type: precision_at_1000
+      value: 0.131
+    - type: precision_at_3
+      value: 10.282
+    - type: precision_at_5
+      value: 7.836
+    - type: recall_at_1
+      value: 13.424
+    - type: recall_at_10
+      value: 38.179
+    - type: recall_at_100
+      value: 63.906
+    - type: recall_at_1000
+      value: 84.933
+    - type: recall_at_3
+      value: 23.878
+    - type: recall_at_5
+      value: 30.037999999999997
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.154
+    - type: map_at_10
+      value: 35.912
+    - type: map_at_100
+      value: 37.211
+    - type: map_at_1000
+      value: 37.327
+    - type: map_at_3
+      value: 32.684999999999995
+    - type: map_at_5
+      value: 34.562
+    - type: mrr_at_1
+      value: 32.435
+    - type: mrr_at_10
+      value: 41.411
+    - type: mrr_at_100
+      value: 42.297000000000004
+    - type: mrr_at_1000
+      value: 42.345
+    - type: mrr_at_3
+      value: 38.771
+    - type: mrr_at_5
+      value: 40.33
+    - type: ndcg_at_1
+      value: 32.435
+    - type: ndcg_at_10
+      value: 41.785
+    - type: ndcg_at_100
+      value: 47.469
+    - type: ndcg_at_1000
+      value: 49.685
+    - type: ndcg_at_3
+      value: 36.618
+    - type: ndcg_at_5
+      value: 39.101
+    - type: precision_at_1
+      value: 32.435
+    - type: precision_at_10
+      value: 7.642
+    - type: precision_at_100
+      value: 1.244
+    - type: precision_at_1000
+      value: 0.163
+    - type: precision_at_3
+      value: 17.485
+    - type: precision_at_5
+      value: 12.57
+    - type: recall_at_1
+      value: 26.154
+    - type: recall_at_10
+      value: 54.111
+    - type: recall_at_100
+      value: 78.348
+    - type: recall_at_1000
+      value: 92.996
+    - type: recall_at_3
+      value: 39.189
+    - type: recall_at_5
+      value: 45.852
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.308999999999997
+    - type: map_at_10
+      value: 35.524
+    - type: map_at_100
+      value: 36.774
+    - type: map_at_1000
+      value: 36.891
+    - type: map_at_3
+      value: 32.561
+    - type: map_at_5
+      value: 34.034
+    - type: mrr_at_1
+      value: 31.735000000000003
+    - type: mrr_at_10
+      value: 40.391
+    - type: mrr_at_100
+      value: 41.227000000000004
+    - type: mrr_at_1000
+      value: 41.288000000000004
+    - type: mrr_at_3
+      value: 37.938
+    - type: mrr_at_5
+      value: 39.193
+    - type: ndcg_at_1
+      value: 31.735000000000003
+    - type: ndcg_at_10
+      value: 41.166000000000004
+    - type: ndcg_at_100
+      value: 46.702
+    - type: ndcg_at_1000
+      value: 49.157000000000004
+    - type: ndcg_at_3
+      value: 36.274
+    - type: ndcg_at_5
+      value: 38.177
+    - type: precision_at_1
+      value: 31.735000000000003
+    - type: precision_at_10
+      value: 7.5569999999999995
+    - type: precision_at_100
+      value: 1.2109999999999999
+    - type: precision_at_1000
+      value: 0.16
+    - type: precision_at_3
+      value: 17.199
+    - type: precision_at_5
+      value: 12.123000000000001
+    - type: recall_at_1
+      value: 26.308999999999997
+    - type: recall_at_10
+      value: 53.083000000000006
+    - type: recall_at_100
+      value: 76.922
+    - type: recall_at_1000
+      value: 93.767
+    - type: recall_at_3
+      value: 39.262
+    - type: recall_at_5
+      value: 44.413000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.391250000000003
+    - type: map_at_10
+      value: 33.280166666666666
+    - type: map_at_100
+      value: 34.49566666666667
+    - type: map_at_1000
+      value: 34.61533333333333
+    - type: map_at_3
+      value: 30.52183333333333
+    - type: map_at_5
+      value: 32.06608333333333
+    - type: mrr_at_1
+      value: 29.105083333333337
+    - type: mrr_at_10
+      value: 37.44766666666666
+    - type: mrr_at_100
+      value: 38.32491666666667
+    - type: mrr_at_1000
+      value: 38.385666666666665
+    - type: mrr_at_3
+      value: 35.06883333333333
+    - type: mrr_at_5
+      value: 36.42066666666667
+    - type: ndcg_at_1
+      value: 29.105083333333337
+    - type: ndcg_at_10
+      value: 38.54358333333333
+    - type: ndcg_at_100
+      value: 43.833583333333344
+    - type: ndcg_at_1000
+      value: 46.215333333333334
+    - type: ndcg_at_3
+      value: 33.876
+    - type: ndcg_at_5
+      value: 36.05208333333333
+    - type: precision_at_1
+      value: 29.105083333333337
+    - type: precision_at_10
+      value: 6.823416666666665
+    - type: precision_at_100
+      value: 1.1270833333333334
+    - type: precision_at_1000
+      value: 0.15208333333333332
+    - type: precision_at_3
+      value: 15.696750000000002
+    - type: precision_at_5
+      value: 11.193499999999998
+    - type: recall_at_1
+      value: 24.391250000000003
+    - type: recall_at_10
+      value: 49.98808333333333
+    - type: recall_at_100
+      value: 73.31616666666666
+    - type: recall_at_1000
+      value: 89.96291666666667
+    - type: recall_at_3
+      value: 36.86666666666667
+    - type: recall_at_5
+      value: 42.54350000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.995
+    - type: map_at_10
+      value: 28.807
+    - type: map_at_100
+      value: 29.813000000000002
+    - type: map_at_1000
+      value: 29.903000000000002
+    - type: map_at_3
+      value: 26.636
+    - type: map_at_5
+      value: 27.912
+    - type: mrr_at_1
+      value: 24.847
+    - type: mrr_at_10
+      value: 31.494
+    - type: mrr_at_100
+      value: 32.381
+    - type: mrr_at_1000
+      value: 32.446999999999996
+    - type: mrr_at_3
+      value: 29.473
+    - type: mrr_at_5
+      value: 30.7
+    - type: ndcg_at_1
+      value: 24.847
+    - type: ndcg_at_10
+      value: 32.818999999999996
+    - type: ndcg_at_100
+      value: 37.835
+    - type: ndcg_at_1000
+      value: 40.226
+    - type: ndcg_at_3
+      value: 28.811999999999998
+    - type: ndcg_at_5
+      value: 30.875999999999998
+    - type: precision_at_1
+      value: 24.847
+    - type: precision_at_10
+      value: 5.244999999999999
+    - type: precision_at_100
+      value: 0.856
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 12.577
+    - type: precision_at_5
+      value: 8.895999999999999
+    - type: recall_at_1
+      value: 21.995
+    - type: recall_at_10
+      value: 42.479
+    - type: recall_at_100
+      value: 65.337
+    - type: recall_at_1000
+      value: 83.23700000000001
+    - type: recall_at_3
+      value: 31.573
+    - type: recall_at_5
+      value: 36.684
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 15.751000000000001
+    - type: map_at_10
+      value: 21.909
+    - type: map_at_100
+      value: 23.064
+    - type: map_at_1000
+      value: 23.205000000000002
+    - type: map_at_3
+      value: 20.138
+    - type: map_at_5
+      value: 20.973
+    - type: mrr_at_1
+      value: 19.305
+    - type: mrr_at_10
+      value: 25.647
+    - type: mrr_at_100
+      value: 26.659
+    - type: mrr_at_1000
+      value: 26.748
+    - type: mrr_at_3
+      value: 23.933
+    - type: mrr_at_5
+      value: 24.754
+    - type: ndcg_at_1
+      value: 19.305
+    - type: ndcg_at_10
+      value: 25.886
+    - type: ndcg_at_100
+      value: 31.56
+    - type: ndcg_at_1000
+      value: 34.799
+    - type: ndcg_at_3
+      value: 22.708000000000002
+    - type: ndcg_at_5
+      value: 23.838
+    - type: precision_at_1
+      value: 19.305
+    - type: precision_at_10
+      value: 4.677
+    - type: precision_at_100
+      value: 0.895
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 10.771
+    - type: precision_at_5
+      value: 7.46
+    - type: recall_at_1
+      value: 15.751000000000001
+    - type: recall_at_10
+      value: 34.156
+    - type: recall_at_100
+      value: 59.899
+    - type: recall_at_1000
+      value: 83.08
+    - type: recall_at_3
+      value: 24.772
+    - type: recall_at_5
+      value: 28.009
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.34
+    - type: map_at_10
+      value: 32.383
+    - type: map_at_100
+      value: 33.629999999999995
+    - type: map_at_1000
+      value: 33.735
+    - type: map_at_3
+      value: 29.68
+    - type: map_at_5
+      value: 31.270999999999997
+    - type: mrr_at_1
+      value: 27.612
+    - type: mrr_at_10
+      value: 36.381
+    - type: mrr_at_100
+      value: 37.351
+    - type: mrr_at_1000
+      value: 37.411
+    - type: mrr_at_3
+      value: 33.893
+    - type: mrr_at_5
+      value: 35.353
+    - type: ndcg_at_1
+      value: 27.612
+    - type: ndcg_at_10
+      value: 37.714999999999996
+    - type: ndcg_at_100
+      value: 43.525000000000006
+    - type: ndcg_at_1000
+      value: 45.812999999999995
+    - type: ndcg_at_3
+      value: 32.796
+    - type: ndcg_at_5
+      value: 35.243
+    - type: precision_at_1
+      value: 27.612
+    - type: precision_at_10
+      value: 6.465
+    - type: precision_at_100
+      value: 1.0619999999999998
+    - type: precision_at_1000
+      value: 0.13699999999999998
+    - type: precision_at_3
+      value: 15.049999999999999
+    - type: precision_at_5
+      value: 10.764999999999999
+    - type: recall_at_1
+      value: 23.34
+    - type: recall_at_10
+      value: 49.856
+    - type: recall_at_100
+      value: 75.334
+    - type: recall_at_1000
+      value: 91.156
+    - type: recall_at_3
+      value: 36.497
+    - type: recall_at_5
+      value: 42.769
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.097
+    - type: map_at_10
+      value: 34.599999999999994
+    - type: map_at_100
+      value: 36.174
+    - type: map_at_1000
+      value: 36.398
+    - type: map_at_3
+      value: 31.781
+    - type: map_at_5
+      value: 33.22
+    - type: mrr_at_1
+      value: 31.225
+    - type: mrr_at_10
+      value: 39.873
+    - type: mrr_at_100
+      value: 40.853
+    - type: mrr_at_1000
+      value: 40.904
+    - type: mrr_at_3
+      value: 37.681
+    - type: mrr_at_5
+      value: 38.669
+    - type: ndcg_at_1
+      value: 31.225
+    - type: ndcg_at_10
+      value: 40.586
+    - type: ndcg_at_100
+      value: 46.226
+    - type: ndcg_at_1000
+      value: 48.788
+    - type: ndcg_at_3
+      value: 36.258
+    - type: ndcg_at_5
+      value: 37.848
+    - type: precision_at_1
+      value: 31.225
+    - type: precision_at_10
+      value: 7.707999999999999
+    - type: precision_at_100
+      value: 1.536
+    - type: precision_at_1000
+      value: 0.242
+    - type: precision_at_3
+      value: 17.26
+    - type: precision_at_5
+      value: 12.253
+    - type: recall_at_1
+      value: 25.097
+    - type: recall_at_10
+      value: 51.602000000000004
+    - type: recall_at_100
+      value: 76.854
+    - type: recall_at_1000
+      value: 93.303
+    - type: recall_at_3
+      value: 38.68
+    - type: recall_at_5
+      value: 43.258
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.689
+    - type: map_at_10
+      value: 25.291000000000004
+    - type: map_at_100
+      value: 26.262
+    - type: map_at_1000
+      value: 26.372
+    - type: map_at_3
+      value: 22.916
+    - type: map_at_5
+      value: 24.315
+    - type: mrr_at_1
+      value: 19.409000000000002
+    - type: mrr_at_10
+      value: 27.233
+    - type: mrr_at_100
+      value: 28.109
+    - type: mrr_at_1000
+      value: 28.192
+    - type: mrr_at_3
+      value: 24.892
+    - type: mrr_at_5
+      value: 26.278000000000002
+    - type: ndcg_at_1
+      value: 19.409000000000002
+    - type: ndcg_at_10
+      value: 29.809
+    - type: ndcg_at_100
+      value: 34.936
+    - type: ndcg_at_1000
+      value: 37.852000000000004
+    - type: ndcg_at_3
+      value: 25.179000000000002
+    - type: ndcg_at_5
+      value: 27.563
+    - type: precision_at_1
+      value: 19.409000000000002
+    - type: precision_at_10
+      value: 4.861
+    - type: precision_at_100
+      value: 0.8
+    - type: precision_at_1000
+      value: 0.116
+    - type: precision_at_3
+      value: 11.029
+    - type: precision_at_5
+      value: 7.985
+    - type: recall_at_1
+      value: 17.689
+    - type: recall_at_10
+      value: 41.724
+    - type: recall_at_100
+      value: 65.95299999999999
+    - type: recall_at_1000
+      value: 88.094
+    - type: recall_at_3
+      value: 29.621
+    - type: recall_at_5
+      value: 35.179
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 10.581
+    - type: map_at_10
+      value: 18.944
+    - type: map_at_100
+      value: 20.812
+    - type: map_at_1000
+      value: 21.002000000000002
+    - type: map_at_3
+      value: 15.661
+    - type: map_at_5
+      value: 17.502000000000002
+    - type: mrr_at_1
+      value: 23.388
+    - type: mrr_at_10
+      value: 34.263
+    - type: mrr_at_100
+      value: 35.364000000000004
+    - type: mrr_at_1000
+      value: 35.409
+    - type: mrr_at_3
+      value: 30.586000000000002
+    - type: mrr_at_5
+      value: 32.928000000000004
+    - type: ndcg_at_1
+      value: 23.388
+    - type: ndcg_at_10
+      value: 26.56
+    - type: ndcg_at_100
+      value: 34.248
+    - type: ndcg_at_1000
+      value: 37.779
+    - type: ndcg_at_3
+      value: 21.179000000000002
+    - type: ndcg_at_5
+      value: 23.504
+    - type: precision_at_1
+      value: 23.388
+    - type: precision_at_10
+      value: 8.476
+    - type: precision_at_100
+      value: 1.672
+    - type: precision_at_1000
+      value: 0.233
+    - type: precision_at_3
+      value: 15.852
+    - type: precision_at_5
+      value: 12.73
+    - type: recall_at_1
+      value: 10.581
+    - type: recall_at_10
+      value: 32.512
+    - type: recall_at_100
+      value: 59.313
+    - type: recall_at_1000
+      value: 79.25
+    - type: recall_at_3
+      value: 19.912
+    - type: recall_at_5
+      value: 25.832
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 9.35
+    - type: map_at_10
+      value: 20.134
+    - type: map_at_100
+      value: 28.975
+    - type: map_at_1000
+      value: 30.709999999999997
+    - type: map_at_3
+      value: 14.513000000000002
+    - type: map_at_5
+      value: 16.671
+    - type: mrr_at_1
+      value: 69.75
+    - type: mrr_at_10
+      value: 77.67699999999999
+    - type: mrr_at_100
+      value: 77.97500000000001
+    - type: mrr_at_1000
+      value: 77.985
+    - type: mrr_at_3
+      value: 76.292
+    - type: mrr_at_5
+      value: 77.179
+    - type: ndcg_at_1
+      value: 56.49999999999999
+    - type: ndcg_at_10
+      value: 42.226
+    - type: ndcg_at_100
+      value: 47.562
+    - type: ndcg_at_1000
+      value: 54.923
+    - type: ndcg_at_3
+      value: 46.564
+    - type: ndcg_at_5
+      value: 43.830000000000005
+    - type: precision_at_1
+      value: 69.75
+    - type: precision_at_10
+      value: 33.525
+    - type: precision_at_100
+      value: 11.035
+    - type: precision_at_1000
+      value: 2.206
+    - type: precision_at_3
+      value: 49.75
+    - type: precision_at_5
+      value: 42
+    - type: recall_at_1
+      value: 9.35
+    - type: recall_at_10
+      value: 25.793
+    - type: recall_at_100
+      value: 54.186
+    - type: recall_at_1000
+      value: 77.81
+    - type: recall_at_3
+      value: 15.770000000000001
+    - type: recall_at_5
+      value: 19.09
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 46.945
+    - type: f1
+      value: 42.07407842992542
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 71.04599999999999
+    - type: map_at_10
+      value: 80.718
+    - type: map_at_100
+      value: 80.961
+    - type: map_at_1000
+      value: 80.974
+    - type: map_at_3
+      value: 79.49199999999999
+    - type: map_at_5
+      value: 80.32000000000001
+    - type: mrr_at_1
+      value: 76.388
+    - type: mrr_at_10
+      value: 85.214
+    - type: mrr_at_100
+      value: 85.302
+    - type: mrr_at_1000
+      value: 85.302
+    - type: mrr_at_3
+      value: 84.373
+    - type: mrr_at_5
+      value: 84.979
+    - type: ndcg_at_1
+      value: 76.388
+    - type: ndcg_at_10
+      value: 84.987
+    - type: ndcg_at_100
+      value: 85.835
+    - type: ndcg_at_1000
+      value: 86.04899999999999
+    - type: ndcg_at_3
+      value: 83.04
+    - type: ndcg_at_5
+      value: 84.22500000000001
+    - type: precision_at_1
+      value: 76.388
+    - type: precision_at_10
+      value: 10.35
+    - type: precision_at_100
+      value: 1.099
+    - type: precision_at_1000
+      value: 0.11399999999999999
+    - type: precision_at_3
+      value: 32.108
+    - type: precision_at_5
+      value: 20.033
+    - type: recall_at_1
+      value: 71.04599999999999
+    - type: recall_at_10
+      value: 93.547
+    - type: recall_at_100
+      value: 96.887
+    - type: recall_at_1000
+      value: 98.158
+    - type: recall_at_3
+      value: 88.346
+    - type: recall_at_5
+      value: 91.321
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 19.8
+    - type: map_at_10
+      value: 31.979999999999997
+    - type: map_at_100
+      value: 33.876
+    - type: map_at_1000
+      value: 34.056999999999995
+    - type: map_at_3
+      value: 28.067999999999998
+    - type: map_at_5
+      value: 30.066
+    - type: mrr_at_1
+      value: 38.735
+    - type: mrr_at_10
+      value: 47.749
+    - type: mrr_at_100
+      value: 48.605
+    - type: mrr_at_1000
+      value: 48.644999999999996
+    - type: mrr_at_3
+      value: 45.165
+    - type: mrr_at_5
+      value: 46.646
+    - type: ndcg_at_1
+      value: 38.735
+    - type: ndcg_at_10
+      value: 39.883
+    - type: ndcg_at_100
+      value: 46.983000000000004
+    - type: ndcg_at_1000
+      value: 50.043000000000006
+    - type: ndcg_at_3
+      value: 35.943000000000005
+    - type: ndcg_at_5
+      value: 37.119
+    - type: precision_at_1
+      value: 38.735
+    - type: precision_at_10
+      value: 10.940999999999999
+    - type: precision_at_100
+      value: 1.836
+    - type: precision_at_1000
+      value: 0.23900000000000002
+    - type: precision_at_3
+      value: 23.817
+    - type: precision_at_5
+      value: 17.346
+    - type: recall_at_1
+      value: 19.8
+    - type: recall_at_10
+      value: 47.082
+    - type: recall_at_100
+      value: 73.247
+    - type: recall_at_1000
+      value: 91.633
+    - type: recall_at_3
+      value: 33.201
+    - type: recall_at_5
+      value: 38.81
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 38.102999999999994
+    - type: map_at_10
+      value: 60.547
+    - type: map_at_100
+      value: 61.466
+    - type: map_at_1000
+      value: 61.526
+    - type: map_at_3
+      value: 56.973
+    - type: map_at_5
+      value: 59.244
+    - type: mrr_at_1
+      value: 76.205
+    - type: mrr_at_10
+      value: 82.816
+    - type: mrr_at_100
+      value: 83.002
+    - type: mrr_at_1000
+      value: 83.009
+    - type: mrr_at_3
+      value: 81.747
+    - type: mrr_at_5
+      value: 82.467
+    - type: ndcg_at_1
+      value: 76.205
+    - type: ndcg_at_10
+      value: 69.15
+    - type: ndcg_at_100
+      value: 72.297
+    - type: ndcg_at_1000
+      value: 73.443
+    - type: ndcg_at_3
+      value: 64.07000000000001
+    - type: ndcg_at_5
+      value: 66.96600000000001
+    - type: precision_at_1
+      value: 76.205
+    - type: precision_at_10
+      value: 14.601
+    - type: precision_at_100
+      value: 1.7049999999999998
+    - type: precision_at_1000
+      value: 0.186
+    - type: precision_at_3
+      value: 41.202
+    - type: precision_at_5
+      value: 27.006000000000004
+    - type: recall_at_1
+      value: 38.102999999999994
+    - type: recall_at_10
+      value: 73.005
+    - type: recall_at_100
+      value: 85.253
+    - type: recall_at_1000
+      value: 92.795
+    - type: recall_at_3
+      value: 61.803
+    - type: recall_at_5
+      value: 67.515
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 86.15
+    - type: ap
+      value: 80.36282825265391
+    - type: f1
+      value: 86.07368510726472
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.6
+    - type: map_at_10
+      value: 34.887
+    - type: map_at_100
+      value: 36.069
+    - type: map_at_1000
+      value: 36.115
+    - type: map_at_3
+      value: 31.067
+    - type: map_at_5
+      value: 33.300000000000004
+    - type: mrr_at_1
+      value: 23.238
+    - type: mrr_at_10
+      value: 35.47
+    - type: mrr_at_100
+      value: 36.599
+    - type: mrr_at_1000
+      value: 36.64
+    - type: mrr_at_3
+      value: 31.735999999999997
+    - type: mrr_at_5
+      value: 33.939
+    - type: ndcg_at_1
+      value: 23.252
+    - type: ndcg_at_10
+      value: 41.765
+    - type: ndcg_at_100
+      value: 47.402
+    - type: ndcg_at_1000
+      value: 48.562
+    - type: ndcg_at_3
+      value: 34.016999999999996
+    - type: ndcg_at_5
+      value: 38.016
+    - type: precision_at_1
+      value: 23.252
+    - type: precision_at_10
+      value: 6.569
+    - type: precision_at_100
+      value: 0.938
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 14.479000000000001
+    - type: precision_at_5
+      value: 10.722
+    - type: recall_at_1
+      value: 22.6
+    - type: recall_at_10
+      value: 62.919000000000004
+    - type: recall_at_100
+      value: 88.82
+    - type: recall_at_1000
+      value: 97.71600000000001
+    - type: recall_at_3
+      value: 41.896
+    - type: recall_at_5
+      value: 51.537
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 93.69357045143639
+    - type: f1
+      value: 93.55489858177597
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 75.31235750114
+    - type: f1
+      value: 57.891491963121155
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 73.04303967720243
+    - type: f1
+      value: 70.51516022297616
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 77.65299260255549
+    - type: f1
+      value: 77.49059766538576
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 31.458906115906597
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 28.9851513122443
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 31.2916268497217
+    - type: mrr
+      value: 32.328276715593816
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 6.3740000000000006
+    - type: map_at_10
+      value: 13.089999999999998
+    - type: map_at_100
+      value: 16.512
+    - type: map_at_1000
+      value: 18.014
+    - type: map_at_3
+      value: 9.671000000000001
+    - type: map_at_5
+      value: 11.199
+    - type: mrr_at_1
+      value: 46.749
+    - type: mrr_at_10
+      value: 55.367
+    - type: mrr_at_100
+      value: 56.021
+    - type: mrr_at_1000
+      value: 56.058
+    - type: mrr_at_3
+      value: 53.30200000000001
+    - type: mrr_at_5
+      value: 54.773
+    - type: ndcg_at_1
+      value: 45.046
+    - type: ndcg_at_10
+      value: 35.388999999999996
+    - type: ndcg_at_100
+      value: 32.175
+    - type: ndcg_at_1000
+      value: 41.018
+    - type: ndcg_at_3
+      value: 40.244
+    - type: ndcg_at_5
+      value: 38.267
+    - type: precision_at_1
+      value: 46.749
+    - type: precision_at_10
+      value: 26.563
+    - type: precision_at_100
+      value: 8.074
+    - type: precision_at_1000
+      value: 2.099
+    - type: precision_at_3
+      value: 37.358000000000004
+    - type: precision_at_5
+      value: 33.003
+    - type: recall_at_1
+      value: 6.3740000000000006
+    - type: recall_at_10
+      value: 16.805999999999997
+    - type: recall_at_100
+      value: 31.871
+    - type: recall_at_1000
+      value: 64.098
+    - type: recall_at_3
+      value: 10.383000000000001
+    - type: recall_at_5
+      value: 13.166
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 34.847
+    - type: map_at_10
+      value: 50.532
+    - type: map_at_100
+      value: 51.504000000000005
+    - type: map_at_1000
+      value: 51.528
+    - type: map_at_3
+      value: 46.219
+    - type: map_at_5
+      value: 48.868
+    - type: mrr_at_1
+      value: 39.137
+    - type: mrr_at_10
+      value: 53.157
+    - type: mrr_at_100
+      value: 53.839999999999996
+    - type: mrr_at_1000
+      value: 53.857
+    - type: mrr_at_3
+      value: 49.667
+    - type: mrr_at_5
+      value: 51.847
+    - type: ndcg_at_1
+      value: 39.108
+    - type: ndcg_at_10
+      value: 58.221000000000004
+    - type: ndcg_at_100
+      value: 62.021
+    - type: ndcg_at_1000
+      value: 62.57
+    - type: ndcg_at_3
+      value: 50.27199999999999
+    - type: ndcg_at_5
+      value: 54.623999999999995
+    - type: precision_at_1
+      value: 39.108
+    - type: precision_at_10
+      value: 9.397
+    - type: precision_at_100
+      value: 1.1520000000000001
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_3
+      value: 22.644000000000002
+    - type: precision_at_5
+      value: 16.141
+    - type: recall_at_1
+      value: 34.847
+    - type: recall_at_10
+      value: 78.945
+    - type: recall_at_100
+      value: 94.793
+    - type: recall_at_1000
+      value: 98.904
+    - type: recall_at_3
+      value: 58.56
+    - type: recall_at_5
+      value: 68.535
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 68.728
+    - type: map_at_10
+      value: 82.537
+    - type: map_at_100
+      value: 83.218
+    - type: map_at_1000
+      value: 83.238
+    - type: map_at_3
+      value: 79.586
+    - type: map_at_5
+      value: 81.416
+    - type: mrr_at_1
+      value: 79.17999999999999
+    - type: mrr_at_10
+      value: 85.79299999999999
+    - type: mrr_at_100
+      value: 85.937
+    - type: mrr_at_1000
+      value: 85.938
+    - type: mrr_at_3
+      value: 84.748
+    - type: mrr_at_5
+      value: 85.431
+    - type: ndcg_at_1
+      value: 79.17
+    - type: ndcg_at_10
+      value: 86.555
+    - type: ndcg_at_100
+      value: 88.005
+    - type: ndcg_at_1000
+      value: 88.146
+    - type: ndcg_at_3
+      value: 83.557
+    - type: ndcg_at_5
+      value: 85.152
+    - type: precision_at_1
+      value: 79.17
+    - type: precision_at_10
+      value: 13.163
+    - type: precision_at_100
+      value: 1.52
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 36.53
+    - type: precision_at_5
+      value: 24.046
+    - type: recall_at_1
+      value: 68.728
+    - type: recall_at_10
+      value: 94.217
+    - type: recall_at_100
+      value: 99.295
+    - type: recall_at_1000
+      value: 99.964
+    - type: recall_at_3
+      value: 85.646
+    - type: recall_at_5
+      value: 90.113
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 56.15680266226348
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 63.4318549229047
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.353
+    - type: map_at_10
+      value: 10.956000000000001
+    - type: map_at_100
+      value: 12.873999999999999
+    - type: map_at_1000
+      value: 13.177
+    - type: map_at_3
+      value: 7.854
+    - type: map_at_5
+      value: 9.327
+    - type: mrr_at_1
+      value: 21.4
+    - type: mrr_at_10
+      value: 31.948999999999998
+    - type: mrr_at_100
+      value: 33.039
+    - type: mrr_at_1000
+      value: 33.106
+    - type: mrr_at_3
+      value: 28.449999999999996
+    - type: mrr_at_5
+      value: 30.535
+    - type: ndcg_at_1
+      value: 21.4
+    - type: ndcg_at_10
+      value: 18.694
+    - type: ndcg_at_100
+      value: 26.275
+    - type: ndcg_at_1000
+      value: 31.836
+    - type: ndcg_at_3
+      value: 17.559
+    - type: ndcg_at_5
+      value: 15.372
+    - type: precision_at_1
+      value: 21.4
+    - type: precision_at_10
+      value: 9.790000000000001
+    - type: precision_at_100
+      value: 2.0709999999999997
+    - type: precision_at_1000
+      value: 0.34099999999999997
+    - type: precision_at_3
+      value: 16.467000000000002
+    - type: precision_at_5
+      value: 13.54
+    - type: recall_at_1
+      value: 4.353
+    - type: recall_at_10
+      value: 19.892000000000003
+    - type: recall_at_100
+      value: 42.067
+    - type: recall_at_1000
+      value: 69.268
+    - type: recall_at_3
+      value: 10.042
+    - type: recall_at_5
+      value: 13.741999999999999
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.75433886279843
+    - type: cos_sim_spearman
+      value: 78.29727771767095
+    - type: euclidean_pearson
+      value: 80.83057828506621
+    - type: euclidean_spearman
+      value: 78.35203149750356
+    - type: manhattan_pearson
+      value: 80.7403553891142
+    - type: manhattan_spearman
+      value: 78.33670488531051
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.59999465280839
+    - type: cos_sim_spearman
+      value: 75.79279003980383
+    - type: euclidean_pearson
+      value: 82.29895375956758
+    - type: euclidean_spearman
+      value: 77.33856514102094
+    - type: manhattan_pearson
+      value: 82.22694214534756
+    - type: manhattan_spearman
+      value: 77.3028993008695
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.09296929691297
+    - type: cos_sim_spearman
+      value: 83.58056936846941
+    - type: euclidean_pearson
+      value: 83.84067483060005
+    - type: euclidean_spearman
+      value: 84.45155680480985
+    - type: manhattan_pearson
+      value: 83.82353052971942
+    - type: manhattan_spearman
+      value: 84.43030567861112
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.74616852320915
+    - type: cos_sim_spearman
+      value: 79.948683747966
+    - type: euclidean_pearson
+      value: 81.55702283757084
+    - type: euclidean_spearman
+      value: 80.1721505114231
+    - type: manhattan_pearson
+      value: 81.52251518619441
+    - type: manhattan_spearman
+      value: 80.1469800135577
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.97170104226318
+    - type: cos_sim_spearman
+      value: 88.82021731518206
+    - type: euclidean_pearson
+      value: 87.92950547187615
+    - type: euclidean_spearman
+      value: 88.67043634645866
+    - type: manhattan_pearson
+      value: 87.90668112827639
+    - type: manhattan_spearman
+      value: 88.64471082785317
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.02790375770599
+    - type: cos_sim_spearman
+      value: 84.46308496590792
+    - type: euclidean_pearson
+      value: 84.29430000414911
+    - type: euclidean_spearman
+      value: 84.77298303589936
+    - type: manhattan_pearson
+      value: 84.23919291368665
+    - type: manhattan_spearman
+      value: 84.75272234871308
+  - 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: 87.62885108477064
+    - type: cos_sim_spearman
+      value: 87.58456196391622
+    - type: euclidean_pearson
+      value: 88.2602775281007
+    - type: euclidean_spearman
+      value: 87.51556278299846
+    - type: manhattan_pearson
+      value: 88.11224053672842
+    - type: manhattan_spearman
+      value: 87.4336094383095
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 63.98187965128411
+    - type: cos_sim_spearman
+      value: 64.0653163219731
+    - type: euclidean_pearson
+      value: 62.30616725924099
+    - type: euclidean_spearman
+      value: 61.556971332295916
+    - type: manhattan_pearson
+      value: 62.07642330128549
+    - type: manhattan_spearman
+      value: 61.155494129828
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.6089703921826
+    - type: cos_sim_spearman
+      value: 86.52303197250791
+    - type: euclidean_pearson
+      value: 85.95801955963246
+    - type: euclidean_spearman
+      value: 86.25242424112962
+    - type: manhattan_pearson
+      value: 85.88829100470312
+    - type: manhattan_spearman
+      value: 86.18742955805165
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 83.02282098487036
+    - type: mrr
+      value: 95.05126409538174
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 55.928
+    - type: map_at_10
+      value: 67.308
+    - type: map_at_100
+      value: 67.89500000000001
+    - type: map_at_1000
+      value: 67.91199999999999
+    - type: map_at_3
+      value: 65.091
+    - type: map_at_5
+      value: 66.412
+    - type: mrr_at_1
+      value: 58.667
+    - type: mrr_at_10
+      value: 68.401
+    - type: mrr_at_100
+      value: 68.804
+    - type: mrr_at_1000
+      value: 68.819
+    - type: mrr_at_3
+      value: 66.72200000000001
+    - type: mrr_at_5
+      value: 67.72200000000001
+    - type: ndcg_at_1
+      value: 58.667
+    - type: ndcg_at_10
+      value: 71.944
+    - type: ndcg_at_100
+      value: 74.464
+    - type: ndcg_at_1000
+      value: 74.82799999999999
+    - type: ndcg_at_3
+      value: 68.257
+    - type: ndcg_at_5
+      value: 70.10300000000001
+    - type: precision_at_1
+      value: 58.667
+    - type: precision_at_10
+      value: 9.533
+    - type: precision_at_100
+      value: 1.09
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 27.222
+    - type: precision_at_5
+      value: 17.533
+    - type: recall_at_1
+      value: 55.928
+    - type: recall_at_10
+      value: 84.65
+    - type: recall_at_100
+      value: 96.267
+    - type: recall_at_1000
+      value: 99
+    - type: recall_at_3
+      value: 74.656
+    - type: recall_at_5
+      value: 79.489
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.79009900990098
+    - type: cos_sim_ap
+      value: 94.5795129511524
+    - type: cos_sim_f1
+      value: 89.34673366834171
+    - type: cos_sim_precision
+      value: 89.79797979797979
+    - type: cos_sim_recall
+      value: 88.9
+    - type: dot_accuracy
+      value: 99.53465346534654
+    - type: dot_ap
+      value: 81.56492504352725
+    - type: dot_f1
+      value: 76.33816908454227
+    - type: dot_precision
+      value: 76.37637637637637
+    - type: dot_recall
+      value: 76.3
+    - type: euclidean_accuracy
+      value: 99.78514851485149
+    - type: euclidean_ap
+      value: 94.59134620408962
+    - type: euclidean_f1
+      value: 88.96484375
+    - type: euclidean_precision
+      value: 86.92748091603053
+    - type: euclidean_recall
+      value: 91.10000000000001
+    - type: manhattan_accuracy
+      value: 99.78415841584159
+    - type: manhattan_ap
+      value: 94.5190197328845
+    - type: manhattan_f1
+      value: 88.84462151394423
+    - type: manhattan_precision
+      value: 88.4920634920635
+    - type: manhattan_recall
+      value: 89.2
+    - type: max_accuracy
+      value: 99.79009900990098
+    - type: max_ap
+      value: 94.59134620408962
+    - type: max_f1
+      value: 89.34673366834171
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 65.1487505617497
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 32.502518166001856
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 50.33775480236701
+    - type: mrr
+      value: 51.17302223919871
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.561111309808208
+    - type: cos_sim_spearman
+      value: 30.2839254379273
+    - type: dot_pearson
+      value: 29.560242291401973
+    - type: dot_spearman
+      value: 30.51527274679116
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.215
+    - type: map_at_10
+      value: 1.752
+    - type: map_at_100
+      value: 9.258
+    - type: map_at_1000
+      value: 23.438
+    - type: map_at_3
+      value: 0.6
+    - type: map_at_5
+      value: 0.968
+    - type: mrr_at_1
+      value: 84
+    - type: mrr_at_10
+      value: 91.333
+    - type: mrr_at_100
+      value: 91.333
+    - type: mrr_at_1000
+      value: 91.333
+    - type: mrr_at_3
+      value: 91.333
+    - type: mrr_at_5
+      value: 91.333
+    - type: ndcg_at_1
+      value: 75
+    - type: ndcg_at_10
+      value: 69.596
+    - type: ndcg_at_100
+      value: 51.970000000000006
+    - type: ndcg_at_1000
+      value: 48.864999999999995
+    - type: ndcg_at_3
+      value: 73.92699999999999
+    - type: ndcg_at_5
+      value: 73.175
+    - type: precision_at_1
+      value: 84
+    - type: precision_at_10
+      value: 74
+    - type: precision_at_100
+      value: 53.2
+    - type: precision_at_1000
+      value: 21.836
+    - type: precision_at_3
+      value: 79.333
+    - type: precision_at_5
+      value: 78.4
+    - type: recall_at_1
+      value: 0.215
+    - type: recall_at_10
+      value: 1.9609999999999999
+    - type: recall_at_100
+      value: 12.809999999999999
+    - type: recall_at_1000
+      value: 46.418
+    - type: recall_at_3
+      value: 0.6479999999999999
+    - type: recall_at_5
+      value: 1.057
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 3.066
+    - type: map_at_10
+      value: 10.508000000000001
+    - type: map_at_100
+      value: 16.258
+    - type: map_at_1000
+      value: 17.705000000000002
+    - type: map_at_3
+      value: 6.157
+    - type: map_at_5
+      value: 7.510999999999999
+    - type: mrr_at_1
+      value: 34.694
+    - type: mrr_at_10
+      value: 48.786
+    - type: mrr_at_100
+      value: 49.619
+    - type: mrr_at_1000
+      value: 49.619
+    - type: mrr_at_3
+      value: 45.918
+    - type: mrr_at_5
+      value: 46.837
+    - type: ndcg_at_1
+      value: 31.633
+    - type: ndcg_at_10
+      value: 26.401999999999997
+    - type: ndcg_at_100
+      value: 37.139
+    - type: ndcg_at_1000
+      value: 48.012
+    - type: ndcg_at_3
+      value: 31.875999999999998
+    - type: ndcg_at_5
+      value: 27.383000000000003
+    - type: precision_at_1
+      value: 34.694
+    - type: precision_at_10
+      value: 22.857
+    - type: precision_at_100
+      value: 7.611999999999999
+    - type: precision_at_1000
+      value: 1.492
+    - type: precision_at_3
+      value: 33.333
+    - type: precision_at_5
+      value: 26.122
+    - type: recall_at_1
+      value: 3.066
+    - type: recall_at_10
+      value: 16.239
+    - type: recall_at_100
+      value: 47.29
+    - type: recall_at_1000
+      value: 81.137
+    - type: recall_at_3
+      value: 7.069
+    - type: recall_at_5
+      value: 9.483
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 72.1126
+    - type: ap
+      value: 14.710862719285753
+    - type: f1
+      value: 55.437808972378846
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 60.39049235993209
+    - type: f1
+      value: 60.69810537250234
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 48.15576640316866
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 86.52917684925792
+    - type: cos_sim_ap
+      value: 75.97497873817315
+    - type: cos_sim_f1
+      value: 70.01151926276718
+    - type: cos_sim_precision
+      value: 67.98409147402435
+    - type: cos_sim_recall
+      value: 72.16358839050132
+    - type: dot_accuracy
+      value: 82.47004828038385
+    - type: dot_ap
+      value: 62.48739894974198
+    - type: dot_f1
+      value: 59.13107511045656
+    - type: dot_precision
+      value: 55.27765029830197
+    - type: dot_recall
+      value: 63.562005277044854
+    - type: euclidean_accuracy
+      value: 86.46361089586935
+    - type: euclidean_ap
+      value: 75.59282886839452
+    - type: euclidean_f1
+      value: 69.6465443945099
+    - type: euclidean_precision
+      value: 64.52847175331982
+    - type: euclidean_recall
+      value: 75.64643799472296
+    - type: manhattan_accuracy
+      value: 86.43380818978363
+    - type: manhattan_ap
+      value: 75.5742420974403
+    - type: manhattan_f1
+      value: 69.8636926889715
+    - type: manhattan_precision
+      value: 65.8644859813084
+    - type: manhattan_recall
+      value: 74.37994722955145
+    - type: max_accuracy
+      value: 86.52917684925792
+    - type: max_ap
+      value: 75.97497873817315
+    - type: max_f1
+      value: 70.01151926276718
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.29056545193464
+    - type: cos_sim_ap
+      value: 86.63028865482376
+    - type: cos_sim_f1
+      value: 79.18166458532285
+    - type: cos_sim_precision
+      value: 75.70585756426465
+    - type: cos_sim_recall
+      value: 82.99199260856174
+    - type: dot_accuracy
+      value: 85.23305002522606
+    - type: dot_ap
+      value: 76.0482687263196
+    - type: dot_f1
+      value: 70.80484330484332
+    - type: dot_precision
+      value: 65.86933474688577
+    - type: dot_recall
+      value: 76.53988296889437
+    - type: euclidean_accuracy
+      value: 89.26145845461248
+    - type: euclidean_ap
+      value: 86.54073288416006
+    - type: euclidean_f1
+      value: 78.9721371479794
+    - type: euclidean_precision
+      value: 76.68649354417525
+    - type: euclidean_recall
+      value: 81.39821373575609
+    - type: manhattan_accuracy
+      value: 89.22847052431405
+    - type: manhattan_ap
+      value: 86.51250729037905
+    - type: manhattan_f1
+      value: 78.94601825044894
+    - type: manhattan_precision
+      value: 75.32694594027555
+    - type: manhattan_recall
+      value: 82.93039728980598
+    - type: max_accuracy
+      value: 89.29056545193464
+    - type: max_ap
+      value: 86.63028865482376
+    - type: max_f1
+      value: 79.18166458532285
+language:
+- en
 license: mit
 ---
+
+# E5-base-v2
+
+[Text Embeddings by Weakly-Supervised Contrastive Pre-training](https://arxiv.org/pdf/2212.03533.pdf).
+Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022
+
+This model has 12 layers and the embedding size is 768.
+
+## Usage
+
+Below is an example to encode queries and passages from the MS-MARCO passage ranking dataset.
+
+```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]
+
+
+# Each input text should start with "query: " or "passage: ".
+# For tasks other than retrieval, you can simply use the "query: " prefix.
+input_texts = ['query: how much protein should a female eat',
+               'query: summit define',
+               "passage: As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.",
+               "passage: Definition of summit for English Language Learners. : 1  the highest point of a mountain : the top of a mountain. : 2  the highest level. : 3  a meeting or series of meetings between the leaders of two or more governments."]
+
+tokenizer = AutoTokenizer.from_pretrained('intfloat/e5-base-v2')
+model = AutoModel.from_pretrained('intfloat/e5-base-v2')
+
+# 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'])
+
+# normalize embeddings
+embeddings = F.normalize(embeddings, p=2, dim=1)
+scores = (embeddings[:2] @ embeddings[2:].T) * 100
+print(scores.tolist())
+```
+
+## Training Details
+
+Please refer to our paper at [https://arxiv.org/pdf/2212.03533.pdf](https://arxiv.org/pdf/2212.03533.pdf).
+
+## Benchmark Evaluation
+
+Check out [unilm/e5](https://github.com/microsoft/unilm/tree/master/e5) to reproduce evaluation results 
+on the [BEIR](https://arxiv.org/abs/2104.08663) and [MTEB benchmark](https://arxiv.org/abs/2210.07316).
+
+## Support for Sentence Transformers
+
+Below is an example for usage with sentence_transformers.
+```python
+from sentence_transformers import SentenceTransformer
+model = SentenceTransformer('intfloat/e5-base-v2')
+input_texts = [
+    'query: how much protein should a female eat',
+    'query: summit define',
+    "passage: As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.",
+    "passage: Definition of summit for English Language Learners. : 1  the highest point of a mountain : the top of a mountain. : 2  the highest level. : 3  a meeting or series of meetings between the leaders of two or more governments."
+]
+embeddings = model.encode(input_texts, normalize_embeddings=True)
+```
+
+Package requirements
+
+`pip install sentence_transformers~=2.2.2`
+
+Contributors: [michaelfeil](https://huggingface.co/michaelfeil)
+
+## FAQ
+
+**1. Do I need to add the prefix "query: " and "passage: " to input texts?**
+
+Yes, this is how the model is trained, otherwise you will see a performance degradation.
+
+Here are some rules of thumb:
+- Use "query: " and "passage: " correspondingly for asymmetric tasks such as passage retrieval in open QA, ad-hoc information retrieval.
+
+- Use "query: " prefix for symmetric tasks such as semantic similarity, paraphrase retrieval.
+
+- Use "query: " prefix if you want to use embeddings as features, such as linear probing classification, clustering.
+
+**2. Why are my reproduced results slightly different from reported in the model card?**
+
+Different versions of `transformers` and `pytorch` could cause negligible but non-zero performance differences.
+
+**3. Why does the cosine similarity scores distribute around 0.7 to 1.0?**
+
+This is a known and expected behavior as we use a low temperature 0.01 for InfoNCE contrastive loss. 
+
+For text embedding tasks like text retrieval or semantic similarity, 
+what matters is the relative order of the scores instead of the absolute values, 
+so this should not be an issue.
+
+## Citation
+
+If you find our paper or models helpful, please consider cite as follows:
+
+```
+@article{wang2022text,
+  title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
+  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
+  journal={arXiv preprint arXiv:2212.03533},
+  year={2022}
+}
+```
+
+## Limitations
+
+This model only works for English texts. Long texts will be truncated to at most 512 tokens.

config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "tmp/",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "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": "float32",
+  "transformers_version": "4.29.0.dev0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d0d559c47d5f71b1d280b13b62a2657f3e3bc70c0786f9ab91a36545e6a8f693
+size 437955512

modules.json

@@ -0,0 +1,20 @@
+[
+    {
+      "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"
+    }
+  ]

onnx/model.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7c65bec2e3ae59c9f3ab86d4a9762c1a73677b5d7edbb41263cddb10b75a5dd5
+size 435811539

onnx/model_quantized.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:251e9ea18f3228c049e6b89d418ffcdcd676f26ab9e17ee497e6cf9cbb7befbd
+size 110083338

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5b119cd34c663c26fcd8bbe82e9873e9a16c6588b9817a4243947a6de478c273
+size 437997357

quantize_config.json

@@ -0,0 +1,30 @@
+{
+    "per_channel": true,
+    "reduce_range": true,
+    "per_model_config": {
+        "model": {
+            "op_types": [
+                "MatMul",
+                "Concat",
+                "Sqrt",
+                "Reshape",
+                "Constant",
+                "Transpose",
+                "Gather",
+                "Unsqueeze",
+                "Mul",
+                "Div",
+                "Sub",
+                "Shape",
+                "Add",
+                "ReduceMean",
+                "Erf",
+                "Slice",
+                "Softmax",
+                "Cast",
+                "Pow"
+            ],
+            "weight_type": "QInt8"
+        }
+    }
+}

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 +1,13 @@
+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}