upload models

README.md

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+---
+tags:
+- mteb
+model-index:
+- name: e5-large
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 77.68656716417911
+    - type: ap
+      value: 41.336896075573584
+    - type: f1
+      value: 71.788561468075
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 90.04965
+    - type: ap
+      value: 86.24637009569418
+    - type: f1
+      value: 90.03896671762645
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 43.016000000000005
+    - type: f1
+      value: 42.1942431880186
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.107000000000003
+    - type: map_at_10
+      value: 40.464
+    - type: map_at_100
+      value: 41.577999999999996
+    - type: map_at_1000
+      value: 41.588
+    - type: map_at_3
+      value: 35.301
+    - type: map_at_5
+      value: 38.263000000000005
+    - type: mrr_at_1
+      value: 25.605
+    - type: mrr_at_10
+      value: 40.64
+    - type: mrr_at_100
+      value: 41.760000000000005
+    - type: mrr_at_1000
+      value: 41.77
+    - type: mrr_at_3
+      value: 35.443000000000005
+    - type: mrr_at_5
+      value: 38.448
+    - type: ndcg_at_1
+      value: 25.107000000000003
+    - type: ndcg_at_10
+      value: 49.352000000000004
+    - type: ndcg_at_100
+      value: 53.98500000000001
+    - type: ndcg_at_1000
+      value: 54.208
+    - type: ndcg_at_3
+      value: 38.671
+    - type: ndcg_at_5
+      value: 43.991
+    - type: precision_at_1
+      value: 25.107000000000003
+    - type: precision_at_10
+      value: 7.795000000000001
+    - type: precision_at_100
+      value: 0.979
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 16.145
+    - type: precision_at_5
+      value: 12.262
+    - type: recall_at_1
+      value: 25.107000000000003
+    - type: recall_at_10
+      value: 77.952
+    - type: recall_at_100
+      value: 97.866
+    - type: recall_at_1000
+      value: 99.57300000000001
+    - type: recall_at_3
+      value: 48.435
+    - type: recall_at_5
+      value: 61.309000000000005
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 46.19278045044154
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 41.37976387757665
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 60.07433334608074
+    - type: mrr
+      value: 73.44347711383723
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.4298072183543
+    - type: cos_sim_spearman
+      value: 84.73144873582848
+    - type: euclidean_pearson
+      value: 85.15885058870728
+    - type: euclidean_spearman
+      value: 85.42062106559356
+    - type: manhattan_pearson
+      value: 84.89409921792054
+    - type: manhattan_spearman
+      value: 85.31941394024344
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 84.14285714285714
+    - type: f1
+      value: 84.11674412565644
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 37.600076342340785
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 35.08861812135148
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.684000000000005
+    - type: map_at_10
+      value: 41.675000000000004
+    - type: map_at_100
+      value: 42.963
+    - type: map_at_1000
+      value: 43.078
+    - type: map_at_3
+      value: 38.708999999999996
+    - type: map_at_5
+      value: 40.316
+    - type: mrr_at_1
+      value: 39.485
+    - type: mrr_at_10
+      value: 47.152
+    - type: mrr_at_100
+      value: 47.96
+    - type: mrr_at_1000
+      value: 48.010000000000005
+    - type: mrr_at_3
+      value: 44.754
+    - type: mrr_at_5
+      value: 46.285
+    - type: ndcg_at_1
+      value: 39.485
+    - type: ndcg_at_10
+      value: 46.849000000000004
+    - type: ndcg_at_100
+      value: 52.059
+    - type: ndcg_at_1000
+      value: 54.358
+    - type: ndcg_at_3
+      value: 42.705
+    - type: ndcg_at_5
+      value: 44.663000000000004
+    - type: precision_at_1
+      value: 39.485
+    - type: precision_at_10
+      value: 8.455
+    - type: precision_at_100
+      value: 1.3379999999999999
+    - type: precision_at_1000
+      value: 0.178
+    - type: precision_at_3
+      value: 19.695
+    - type: precision_at_5
+      value: 13.905999999999999
+    - type: recall_at_1
+      value: 32.684000000000005
+    - type: recall_at_10
+      value: 56.227000000000004
+    - type: recall_at_100
+      value: 78.499
+    - type: recall_at_1000
+      value: 94.021
+    - type: recall_at_3
+      value: 44.157999999999994
+    - type: recall_at_5
+      value: 49.694
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 31.875999999999998
+    - type: map_at_10
+      value: 41.603
+    - type: map_at_100
+      value: 42.825
+    - type: map_at_1000
+      value: 42.961
+    - type: map_at_3
+      value: 38.655
+    - type: map_at_5
+      value: 40.294999999999995
+    - type: mrr_at_1
+      value: 40.127
+    - type: mrr_at_10
+      value: 47.959
+    - type: mrr_at_100
+      value: 48.59
+    - type: mrr_at_1000
+      value: 48.634
+    - type: mrr_at_3
+      value: 45.786
+    - type: mrr_at_5
+      value: 46.964
+    - type: ndcg_at_1
+      value: 40.127
+    - type: ndcg_at_10
+      value: 47.176
+    - type: ndcg_at_100
+      value: 51.346000000000004
+    - type: ndcg_at_1000
+      value: 53.502
+    - type: ndcg_at_3
+      value: 43.139
+    - type: ndcg_at_5
+      value: 44.883
+    - type: precision_at_1
+      value: 40.127
+    - type: precision_at_10
+      value: 8.72
+    - type: precision_at_100
+      value: 1.387
+    - type: precision_at_1000
+      value: 0.188
+    - type: precision_at_3
+      value: 20.637
+    - type: precision_at_5
+      value: 14.446
+    - type: recall_at_1
+      value: 31.875999999999998
+    - type: recall_at_10
+      value: 56.54900000000001
+    - type: recall_at_100
+      value: 73.939
+    - type: recall_at_1000
+      value: 87.732
+    - type: recall_at_3
+      value: 44.326
+    - type: recall_at_5
+      value: 49.445
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 41.677
+    - type: map_at_10
+      value: 52.222
+    - type: map_at_100
+      value: 53.229000000000006
+    - type: map_at_1000
+      value: 53.288000000000004
+    - type: map_at_3
+      value: 49.201
+    - type: map_at_5
+      value: 51.00599999999999
+    - type: mrr_at_1
+      value: 47.524
+    - type: mrr_at_10
+      value: 55.745999999999995
+    - type: mrr_at_100
+      value: 56.433
+    - type: mrr_at_1000
+      value: 56.464999999999996
+    - type: mrr_at_3
+      value: 53.37499999999999
+    - type: mrr_at_5
+      value: 54.858
+    - type: ndcg_at_1
+      value: 47.524
+    - type: ndcg_at_10
+      value: 57.406
+    - type: ndcg_at_100
+      value: 61.403
+    - type: ndcg_at_1000
+      value: 62.7
+    - type: ndcg_at_3
+      value: 52.298
+    - type: ndcg_at_5
+      value: 55.02
+    - type: precision_at_1
+      value: 47.524
+    - type: precision_at_10
+      value: 8.865
+    - type: precision_at_100
+      value: 1.179
+    - type: precision_at_1000
+      value: 0.134
+    - type: precision_at_3
+      value: 22.612
+    - type: precision_at_5
+      value: 15.461
+    - type: recall_at_1
+      value: 41.677
+    - type: recall_at_10
+      value: 69.346
+    - type: recall_at_100
+      value: 86.344
+    - type: recall_at_1000
+      value: 95.703
+    - type: recall_at_3
+      value: 55.789
+    - type: recall_at_5
+      value: 62.488
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.991999999999997
+    - type: map_at_10
+      value: 32.804
+    - type: map_at_100
+      value: 33.812999999999995
+    - type: map_at_1000
+      value: 33.897
+    - type: map_at_3
+      value: 30.567
+    - type: map_at_5
+      value: 31.599
+    - type: mrr_at_1
+      value: 27.797
+    - type: mrr_at_10
+      value: 34.768
+    - type: mrr_at_100
+      value: 35.702
+    - type: mrr_at_1000
+      value: 35.766
+    - type: mrr_at_3
+      value: 32.637
+    - type: mrr_at_5
+      value: 33.614
+    - type: ndcg_at_1
+      value: 27.797
+    - type: ndcg_at_10
+      value: 36.966
+    - type: ndcg_at_100
+      value: 41.972
+    - type: ndcg_at_1000
+      value: 44.139
+    - type: ndcg_at_3
+      value: 32.547
+    - type: ndcg_at_5
+      value: 34.258
+    - type: precision_at_1
+      value: 27.797
+    - type: precision_at_10
+      value: 5.514
+    - type: precision_at_100
+      value: 0.8340000000000001
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 13.333
+    - type: precision_at_5
+      value: 9.04
+    - type: recall_at_1
+      value: 25.991999999999997
+    - type: recall_at_10
+      value: 47.941
+    - type: recall_at_100
+      value: 71.039
+    - type: recall_at_1000
+      value: 87.32799999999999
+    - type: recall_at_3
+      value: 36.01
+    - type: recall_at_5
+      value: 40.056000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.533
+    - type: map_at_10
+      value: 24.336
+    - type: map_at_100
+      value: 25.445
+    - type: map_at_1000
+      value: 25.561
+    - type: map_at_3
+      value: 22.116
+    - type: map_at_5
+      value: 23.347
+    - type: mrr_at_1
+      value: 21.642
+    - type: mrr_at_10
+      value: 28.910999999999998
+    - type: mrr_at_100
+      value: 29.836000000000002
+    - type: mrr_at_1000
+      value: 29.907
+    - type: mrr_at_3
+      value: 26.638
+    - type: mrr_at_5
+      value: 27.857
+    - type: ndcg_at_1
+      value: 21.642
+    - type: ndcg_at_10
+      value: 28.949
+    - type: ndcg_at_100
+      value: 34.211000000000006
+    - type: ndcg_at_1000
+      value: 37.031
+    - type: ndcg_at_3
+      value: 24.788
+    - type: ndcg_at_5
+      value: 26.685
+    - type: precision_at_1
+      value: 21.642
+    - type: precision_at_10
+      value: 5.137
+    - type: precision_at_100
+      value: 0.893
+    - type: precision_at_1000
+      value: 0.127
+    - type: precision_at_3
+      value: 11.733
+    - type: precision_at_5
+      value: 8.383000000000001
+    - type: recall_at_1
+      value: 17.533
+    - type: recall_at_10
+      value: 38.839
+    - type: recall_at_100
+      value: 61.458999999999996
+    - type: recall_at_1000
+      value: 81.58
+    - type: recall_at_3
+      value: 27.328999999999997
+    - type: recall_at_5
+      value: 32.168
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.126
+    - type: map_at_10
+      value: 37.872
+    - type: map_at_100
+      value: 39.229
+    - type: map_at_1000
+      value: 39.353
+    - type: map_at_3
+      value: 34.93
+    - type: map_at_5
+      value: 36.59
+    - type: mrr_at_1
+      value: 34.071
+    - type: mrr_at_10
+      value: 43.056
+    - type: mrr_at_100
+      value: 43.944
+    - type: mrr_at_1000
+      value: 43.999
+    - type: mrr_at_3
+      value: 40.536
+    - type: mrr_at_5
+      value: 42.065999999999995
+    - type: ndcg_at_1
+      value: 34.071
+    - type: ndcg_at_10
+      value: 43.503
+    - type: ndcg_at_100
+      value: 49.120000000000005
+    - type: ndcg_at_1000
+      value: 51.410999999999994
+    - type: ndcg_at_3
+      value: 38.767
+    - type: ndcg_at_5
+      value: 41.075
+    - type: precision_at_1
+      value: 34.071
+    - type: precision_at_10
+      value: 7.843999999999999
+    - type: precision_at_100
+      value: 1.2489999999999999
+    - type: precision_at_1000
+      value: 0.163
+    - type: precision_at_3
+      value: 18.223
+    - type: precision_at_5
+      value: 13.050999999999998
+    - type: recall_at_1
+      value: 28.126
+    - type: recall_at_10
+      value: 54.952
+    - type: recall_at_100
+      value: 78.375
+    - type: recall_at_1000
+      value: 93.29899999999999
+    - type: recall_at_3
+      value: 41.714
+    - type: recall_at_5
+      value: 47.635
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.957
+    - type: map_at_10
+      value: 34.749
+    - type: map_at_100
+      value: 35.929
+    - type: map_at_1000
+      value: 36.043
+    - type: map_at_3
+      value: 31.947
+    - type: map_at_5
+      value: 33.575
+    - type: mrr_at_1
+      value: 32.078
+    - type: mrr_at_10
+      value: 39.844
+    - type: mrr_at_100
+      value: 40.71
+    - type: mrr_at_1000
+      value: 40.77
+    - type: mrr_at_3
+      value: 37.386
+    - type: mrr_at_5
+      value: 38.83
+    - type: ndcg_at_1
+      value: 32.078
+    - type: ndcg_at_10
+      value: 39.97
+    - type: ndcg_at_100
+      value: 45.254
+    - type: ndcg_at_1000
+      value: 47.818
+    - type: ndcg_at_3
+      value: 35.453
+    - type: ndcg_at_5
+      value: 37.631
+    - type: precision_at_1
+      value: 32.078
+    - type: precision_at_10
+      value: 7.158
+    - type: precision_at_100
+      value: 1.126
+    - type: precision_at_1000
+      value: 0.153
+    - type: precision_at_3
+      value: 16.743
+    - type: precision_at_5
+      value: 11.872
+    - type: recall_at_1
+      value: 25.957
+    - type: recall_at_10
+      value: 50.583
+    - type: recall_at_100
+      value: 73.593
+    - type: recall_at_1000
+      value: 91.23599999999999
+    - type: recall_at_3
+      value: 37.651
+    - type: recall_at_5
+      value: 43.626
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.1505
+    - type: map_at_10
+      value: 34.844833333333334
+    - type: map_at_100
+      value: 35.95216666666667
+    - type: map_at_1000
+      value: 36.06675
+    - type: map_at_3
+      value: 32.41975
+    - type: map_at_5
+      value: 33.74233333333333
+    - type: mrr_at_1
+      value: 31.923666666666662
+    - type: mrr_at_10
+      value: 38.87983333333334
+    - type: mrr_at_100
+      value: 39.706250000000004
+    - type: mrr_at_1000
+      value: 39.76708333333333
+    - type: mrr_at_3
+      value: 36.72008333333333
+    - type: mrr_at_5
+      value: 37.96933333333334
+    - type: ndcg_at_1
+      value: 31.923666666666662
+    - type: ndcg_at_10
+      value: 39.44258333333334
+    - type: ndcg_at_100
+      value: 44.31475
+    - type: ndcg_at_1000
+      value: 46.75
+    - type: ndcg_at_3
+      value: 35.36299999999999
+    - type: ndcg_at_5
+      value: 37.242333333333335
+    - type: precision_at_1
+      value: 31.923666666666662
+    - type: precision_at_10
+      value: 6.643333333333333
+    - type: precision_at_100
+      value: 1.0612499999999998
+    - type: precision_at_1000
+      value: 0.14575
+    - type: precision_at_3
+      value: 15.875250000000001
+    - type: precision_at_5
+      value: 11.088916666666664
+    - type: recall_at_1
+      value: 27.1505
+    - type: recall_at_10
+      value: 49.06349999999999
+    - type: recall_at_100
+      value: 70.60841666666666
+    - type: recall_at_1000
+      value: 87.72049999999999
+    - type: recall_at_3
+      value: 37.60575000000001
+    - type: recall_at_5
+      value: 42.511166666666675
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.101000000000003
+    - type: map_at_10
+      value: 30.147000000000002
+    - type: map_at_100
+      value: 30.98
+    - type: map_at_1000
+      value: 31.080000000000002
+    - type: map_at_3
+      value: 28.571
+    - type: map_at_5
+      value: 29.319
+    - type: mrr_at_1
+      value: 27.761000000000003
+    - type: mrr_at_10
+      value: 32.716
+    - type: mrr_at_100
+      value: 33.504
+    - type: mrr_at_1000
+      value: 33.574
+    - type: mrr_at_3
+      value: 31.135
+    - type: mrr_at_5
+      value: 32.032
+    - type: ndcg_at_1
+      value: 27.761000000000003
+    - type: ndcg_at_10
+      value: 33.358
+    - type: ndcg_at_100
+      value: 37.569
+    - type: ndcg_at_1000
+      value: 40.189
+    - type: ndcg_at_3
+      value: 30.291
+    - type: ndcg_at_5
+      value: 31.558000000000003
+    - type: precision_at_1
+      value: 27.761000000000003
+    - type: precision_at_10
+      value: 4.939
+    - type: precision_at_100
+      value: 0.759
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 12.577
+    - type: precision_at_5
+      value: 8.497
+    - type: recall_at_1
+      value: 25.101000000000003
+    - type: recall_at_10
+      value: 40.739
+    - type: recall_at_100
+      value: 60.089999999999996
+    - type: recall_at_1000
+      value: 79.768
+    - type: recall_at_3
+      value: 32.16
+    - type: recall_at_5
+      value: 35.131
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 20.112
+    - type: map_at_10
+      value: 26.119999999999997
+    - type: map_at_100
+      value: 27.031
+    - type: map_at_1000
+      value: 27.150000000000002
+    - type: map_at_3
+      value: 24.230999999999998
+    - type: map_at_5
+      value: 25.15
+    - type: mrr_at_1
+      value: 24.535
+    - type: mrr_at_10
+      value: 30.198000000000004
+    - type: mrr_at_100
+      value: 30.975
+    - type: mrr_at_1000
+      value: 31.051000000000002
+    - type: mrr_at_3
+      value: 28.338
+    - type: mrr_at_5
+      value: 29.269000000000002
+    - type: ndcg_at_1
+      value: 24.535
+    - type: ndcg_at_10
+      value: 30.147000000000002
+    - type: ndcg_at_100
+      value: 34.544000000000004
+    - type: ndcg_at_1000
+      value: 37.512
+    - type: ndcg_at_3
+      value: 26.726
+    - type: ndcg_at_5
+      value: 28.046
+    - type: precision_at_1
+      value: 24.535
+    - type: precision_at_10
+      value: 5.179
+    - type: precision_at_100
+      value: 0.859
+    - type: precision_at_1000
+      value: 0.128
+    - type: precision_at_3
+      value: 12.159
+    - type: precision_at_5
+      value: 8.424
+    - type: recall_at_1
+      value: 20.112
+    - type: recall_at_10
+      value: 38.312000000000005
+    - type: recall_at_100
+      value: 58.406000000000006
+    - type: recall_at_1000
+      value: 79.863
+    - type: recall_at_3
+      value: 28.358
+    - type: recall_at_5
+      value: 31.973000000000003
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.111
+    - type: map_at_10
+      value: 34.096
+    - type: map_at_100
+      value: 35.181000000000004
+    - type: map_at_1000
+      value: 35.276
+    - type: map_at_3
+      value: 31.745
+    - type: map_at_5
+      value: 33.045
+    - type: mrr_at_1
+      value: 31.343
+    - type: mrr_at_10
+      value: 37.994
+    - type: mrr_at_100
+      value: 38.873000000000005
+    - type: mrr_at_1000
+      value: 38.934999999999995
+    - type: mrr_at_3
+      value: 35.743
+    - type: mrr_at_5
+      value: 37.077
+    - type: ndcg_at_1
+      value: 31.343
+    - type: ndcg_at_10
+      value: 38.572
+    - type: ndcg_at_100
+      value: 43.854
+    - type: ndcg_at_1000
+      value: 46.190999999999995
+    - type: ndcg_at_3
+      value: 34.247
+    - type: ndcg_at_5
+      value: 36.28
+    - type: precision_at_1
+      value: 31.343
+    - type: precision_at_10
+      value: 6.166
+    - type: precision_at_100
+      value: 1.0
+    - type: precision_at_1000
+      value: 0.13
+    - type: precision_at_3
+      value: 15.081
+    - type: precision_at_5
+      value: 10.428999999999998
+    - type: recall_at_1
+      value: 27.111
+    - type: recall_at_10
+      value: 48.422
+    - type: recall_at_100
+      value: 71.846
+    - type: recall_at_1000
+      value: 88.57000000000001
+    - type: recall_at_3
+      value: 36.435
+    - type: recall_at_5
+      value: 41.765
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.264
+    - type: map_at_10
+      value: 33.522
+    - type: map_at_100
+      value: 34.963
+    - type: map_at_1000
+      value: 35.175
+    - type: map_at_3
+      value: 31.366
+    - type: map_at_5
+      value: 32.621
+    - type: mrr_at_1
+      value: 31.028
+    - type: mrr_at_10
+      value: 37.230000000000004
+    - type: mrr_at_100
+      value: 38.149
+    - type: mrr_at_1000
+      value: 38.218
+    - type: mrr_at_3
+      value: 35.046
+    - type: mrr_at_5
+      value: 36.617
+    - type: ndcg_at_1
+      value: 31.028
+    - type: ndcg_at_10
+      value: 37.964999999999996
+    - type: ndcg_at_100
+      value: 43.342000000000006
+    - type: ndcg_at_1000
+      value: 46.471000000000004
+    - type: ndcg_at_3
+      value: 34.67
+    - type: ndcg_at_5
+      value: 36.458
+    - type: precision_at_1
+      value: 31.028
+    - type: precision_at_10
+      value: 6.937
+    - type: precision_at_100
+      value: 1.346
+    - type: precision_at_1000
+      value: 0.22799999999999998
+    - type: precision_at_3
+      value: 15.942
+    - type: precision_at_5
+      value: 11.462
+    - type: recall_at_1
+      value: 26.264
+    - type: recall_at_10
+      value: 45.571
+    - type: recall_at_100
+      value: 70.246
+    - type: recall_at_1000
+      value: 90.971
+    - type: recall_at_3
+      value: 36.276
+    - type: recall_at_5
+      value: 41.162
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.372999999999998
+    - type: map_at_10
+      value: 28.992
+    - type: map_at_100
+      value: 29.837999999999997
+    - type: map_at_1000
+      value: 29.939
+    - type: map_at_3
+      value: 26.999000000000002
+    - type: map_at_5
+      value: 28.044999999999998
+    - type: mrr_at_1
+      value: 25.692999999999998
+    - type: mrr_at_10
+      value: 30.984
+    - type: mrr_at_100
+      value: 31.799
+    - type: mrr_at_1000
+      value: 31.875999999999998
+    - type: mrr_at_3
+      value: 29.267
+    - type: mrr_at_5
+      value: 30.163
+    - type: ndcg_at_1
+      value: 25.692999999999998
+    - type: ndcg_at_10
+      value: 32.45
+    - type: ndcg_at_100
+      value: 37.103
+    - type: ndcg_at_1000
+      value: 39.678000000000004
+    - type: ndcg_at_3
+      value: 28.725
+    - type: ndcg_at_5
+      value: 30.351
+    - type: precision_at_1
+      value: 25.692999999999998
+    - type: precision_at_10
+      value: 4.806
+    - type: precision_at_100
+      value: 0.765
+    - type: precision_at_1000
+      value: 0.108
+    - type: precision_at_3
+      value: 11.768
+    - type: precision_at_5
+      value: 8.096
+    - type: recall_at_1
+      value: 23.372999999999998
+    - type: recall_at_10
+      value: 41.281
+    - type: recall_at_100
+      value: 63.465
+    - type: recall_at_1000
+      value: 82.575
+    - type: recall_at_3
+      value: 31.063000000000002
+    - type: recall_at_5
+      value: 34.991
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 8.821
+    - type: map_at_10
+      value: 15.383
+    - type: map_at_100
+      value: 17.244999999999997
+    - type: map_at_1000
+      value: 17.445
+    - type: map_at_3
+      value: 12.64
+    - type: map_at_5
+      value: 13.941999999999998
+    - type: mrr_at_1
+      value: 19.544
+    - type: mrr_at_10
+      value: 29.738999999999997
+    - type: mrr_at_100
+      value: 30.923000000000002
+    - type: mrr_at_1000
+      value: 30.969
+    - type: mrr_at_3
+      value: 26.384
+    - type: mrr_at_5
+      value: 28.199
+    - type: ndcg_at_1
+      value: 19.544
+    - type: ndcg_at_10
+      value: 22.398
+    - type: ndcg_at_100
+      value: 30.253999999999998
+    - type: ndcg_at_1000
+      value: 33.876
+    - type: ndcg_at_3
+      value: 17.473
+    - type: ndcg_at_5
+      value: 19.154
+    - type: precision_at_1
+      value: 19.544
+    - type: precision_at_10
+      value: 7.217999999999999
+    - type: precision_at_100
+      value: 1.564
+    - type: precision_at_1000
+      value: 0.22300000000000003
+    - type: precision_at_3
+      value: 13.225000000000001
+    - type: precision_at_5
+      value: 10.319
+    - type: recall_at_1
+      value: 8.821
+    - type: recall_at_10
+      value: 28.110000000000003
+    - type: recall_at_100
+      value: 55.64
+    - type: recall_at_1000
+      value: 75.964
+    - type: recall_at_3
+      value: 16.195
+    - type: recall_at_5
+      value: 20.678
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 9.344
+    - type: map_at_10
+      value: 20.301
+    - type: map_at_100
+      value: 28.709
+    - type: map_at_1000
+      value: 30.470999999999997
+    - type: map_at_3
+      value: 14.584
+    - type: map_at_5
+      value: 16.930999999999997
+    - type: mrr_at_1
+      value: 67.25
+    - type: mrr_at_10
+      value: 75.393
+    - type: mrr_at_100
+      value: 75.742
+    - type: mrr_at_1000
+      value: 75.75
+    - type: mrr_at_3
+      value: 73.958
+    - type: mrr_at_5
+      value: 74.883
+    - type: ndcg_at_1
+      value: 56.00000000000001
+    - type: ndcg_at_10
+      value: 42.394
+    - type: ndcg_at_100
+      value: 47.091
+    - type: ndcg_at_1000
+      value: 54.215
+    - type: ndcg_at_3
+      value: 46.995
+    - type: ndcg_at_5
+      value: 44.214999999999996
+    - type: precision_at_1
+      value: 67.25
+    - type: precision_at_10
+      value: 33.525
+    - type: precision_at_100
+      value: 10.67
+    - type: precision_at_1000
+      value: 2.221
+    - type: precision_at_3
+      value: 49.417
+    - type: precision_at_5
+      value: 42.15
+    - type: recall_at_1
+      value: 9.344
+    - type: recall_at_10
+      value: 25.209
+    - type: recall_at_100
+      value: 52.329
+    - type: recall_at_1000
+      value: 74.2
+    - type: recall_at_3
+      value: 15.699
+    - type: recall_at_5
+      value: 19.24
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 48.05
+    - type: f1
+      value: 43.06718139212933
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 46.452
+    - type: map_at_10
+      value: 58.825
+    - type: map_at_100
+      value: 59.372
+    - type: map_at_1000
+      value: 59.399
+    - type: map_at_3
+      value: 56.264
+    - type: map_at_5
+      value: 57.879999999999995
+    - type: mrr_at_1
+      value: 49.82
+    - type: mrr_at_10
+      value: 62.178999999999995
+    - type: mrr_at_100
+      value: 62.641999999999996
+    - type: mrr_at_1000
+      value: 62.658
+    - type: mrr_at_3
+      value: 59.706
+    - type: mrr_at_5
+      value: 61.283
+    - type: ndcg_at_1
+      value: 49.82
+    - type: ndcg_at_10
+      value: 65.031
+    - type: ndcg_at_100
+      value: 67.413
+    - type: ndcg_at_1000
+      value: 68.014
+    - type: ndcg_at_3
+      value: 60.084
+    - type: ndcg_at_5
+      value: 62.858000000000004
+    - type: precision_at_1
+      value: 49.82
+    - type: precision_at_10
+      value: 8.876000000000001
+    - type: precision_at_100
+      value: 1.018
+    - type: precision_at_1000
+      value: 0.109
+    - type: precision_at_3
+      value: 24.477
+    - type: precision_at_5
+      value: 16.208
+    - type: recall_at_1
+      value: 46.452
+    - type: recall_at_10
+      value: 80.808
+    - type: recall_at_100
+      value: 91.215
+    - type: recall_at_1000
+      value: 95.52000000000001
+    - type: recall_at_3
+      value: 67.62899999999999
+    - type: recall_at_5
+      value: 74.32900000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 18.351
+    - type: map_at_10
+      value: 30.796
+    - type: map_at_100
+      value: 32.621
+    - type: map_at_1000
+      value: 32.799
+    - type: map_at_3
+      value: 26.491
+    - type: map_at_5
+      value: 28.933999999999997
+    - type: mrr_at_1
+      value: 36.265
+    - type: mrr_at_10
+      value: 45.556999999999995
+    - type: mrr_at_100
+      value: 46.323
+    - type: mrr_at_1000
+      value: 46.359
+    - type: mrr_at_3
+      value: 42.695
+    - type: mrr_at_5
+      value: 44.324000000000005
+    - type: ndcg_at_1
+      value: 36.265
+    - type: ndcg_at_10
+      value: 38.558
+    - type: ndcg_at_100
+      value: 45.18
+    - type: ndcg_at_1000
+      value: 48.292
+    - type: ndcg_at_3
+      value: 34.204
+    - type: ndcg_at_5
+      value: 35.735
+    - type: precision_at_1
+      value: 36.265
+    - type: precision_at_10
+      value: 10.879999999999999
+    - type: precision_at_100
+      value: 1.77
+    - type: precision_at_1000
+      value: 0.234
+    - type: precision_at_3
+      value: 23.044999999999998
+    - type: precision_at_5
+      value: 17.253
+    - type: recall_at_1
+      value: 18.351
+    - type: recall_at_10
+      value: 46.116
+    - type: recall_at_100
+      value: 70.786
+    - type: recall_at_1000
+      value: 89.46300000000001
+    - type: recall_at_3
+      value: 31.404
+    - type: recall_at_5
+      value: 37.678
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 36.847
+    - type: map_at_10
+      value: 54.269999999999996
+    - type: map_at_100
+      value: 55.152
+    - type: map_at_1000
+      value: 55.223
+    - type: map_at_3
+      value: 51.166
+    - type: map_at_5
+      value: 53.055
+    - type: mrr_at_1
+      value: 73.693
+    - type: mrr_at_10
+      value: 79.975
+    - type: mrr_at_100
+      value: 80.202
+    - type: mrr_at_1000
+      value: 80.214
+    - type: mrr_at_3
+      value: 78.938
+    - type: mrr_at_5
+      value: 79.595
+    - type: ndcg_at_1
+      value: 73.693
+    - type: ndcg_at_10
+      value: 63.334999999999994
+    - type: ndcg_at_100
+      value: 66.452
+    - type: ndcg_at_1000
+      value: 67.869
+    - type: ndcg_at_3
+      value: 58.829
+    - type: ndcg_at_5
+      value: 61.266
+    - type: precision_at_1
+      value: 73.693
+    - type: precision_at_10
+      value: 13.122
+    - type: precision_at_100
+      value: 1.5559999999999998
+    - type: precision_at_1000
+      value: 0.174
+    - type: precision_at_3
+      value: 37.083
+    - type: precision_at_5
+      value: 24.169999999999998
+    - type: recall_at_1
+      value: 36.847
+    - type: recall_at_10
+      value: 65.61099999999999
+    - type: recall_at_100
+      value: 77.792
+    - type: recall_at_1000
+      value: 87.17099999999999
+    - type: recall_at_3
+      value: 55.625
+    - type: recall_at_5
+      value: 60.425
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 82.1096
+    - type: ap
+      value: 76.67089212843918
+    - type: f1
+      value: 82.03535056754939
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.465
+    - type: map_at_10
+      value: 37.072
+    - type: map_at_100
+      value: 38.188
+    - type: map_at_1000
+      value: 38.232
+    - type: map_at_3
+      value: 33.134
+    - type: map_at_5
+      value: 35.453
+    - type: mrr_at_1
+      value: 25.142999999999997
+    - type: mrr_at_10
+      value: 37.669999999999995
+    - type: mrr_at_100
+      value: 38.725
+    - type: mrr_at_1000
+      value: 38.765
+    - type: mrr_at_3
+      value: 33.82
+    - type: mrr_at_5
+      value: 36.111
+    - type: ndcg_at_1
+      value: 25.142999999999997
+    - type: ndcg_at_10
+      value: 44.054
+    - type: ndcg_at_100
+      value: 49.364000000000004
+    - type: ndcg_at_1000
+      value: 50.456
+    - type: ndcg_at_3
+      value: 36.095
+    - type: ndcg_at_5
+      value: 40.23
+    - type: precision_at_1
+      value: 25.142999999999997
+    - type: precision_at_10
+      value: 6.845
+    - type: precision_at_100
+      value: 0.95
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 15.204999999999998
+    - type: precision_at_5
+      value: 11.221
+    - type: recall_at_1
+      value: 24.465
+    - type: recall_at_10
+      value: 65.495
+    - type: recall_at_100
+      value: 89.888
+    - type: recall_at_1000
+      value: 98.165
+    - type: recall_at_3
+      value: 43.964
+    - type: recall_at_5
+      value: 53.891
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 93.86228910168718
+    - type: f1
+      value: 93.69177113259104
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 76.3999088007296
+    - type: f1
+      value: 58.96668664333438
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 73.21788836583727
+    - type: f1
+      value: 71.4545936552952
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 77.39071956960323
+    - type: f1
+      value: 77.12398952847603
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 32.255379528166955
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 29.66423362872814
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 30.782211620375964
+    - type: mrr
+      value: 31.773479703044956
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.863
+    - type: map_at_10
+      value: 13.831
+    - type: map_at_100
+      value: 17.534
+    - type: map_at_1000
+      value: 19.012
+    - type: map_at_3
+      value: 10.143
+    - type: map_at_5
+      value: 12.034
+    - type: mrr_at_1
+      value: 46.749
+    - type: mrr_at_10
+      value: 55.376999999999995
+    - type: mrr_at_100
+      value: 56.009
+    - type: mrr_at_1000
+      value: 56.042
+    - type: mrr_at_3
+      value: 53.30200000000001
+    - type: mrr_at_5
+      value: 54.85
+    - type: ndcg_at_1
+      value: 44.582
+    - type: ndcg_at_10
+      value: 36.07
+    - type: ndcg_at_100
+      value: 33.39
+    - type: ndcg_at_1000
+      value: 41.884
+    - type: ndcg_at_3
+      value: 41.441
+    - type: ndcg_at_5
+      value: 39.861000000000004
+    - type: precision_at_1
+      value: 46.129999999999995
+    - type: precision_at_10
+      value: 26.594
+    - type: precision_at_100
+      value: 8.365
+    - type: precision_at_1000
+      value: 2.1260000000000003
+    - type: precision_at_3
+      value: 39.009
+    - type: precision_at_5
+      value: 34.861
+    - type: recall_at_1
+      value: 5.863
+    - type: recall_at_10
+      value: 17.961
+    - type: recall_at_100
+      value: 34.026
+    - type: recall_at_1000
+      value: 64.46499999999999
+    - type: recall_at_3
+      value: 11.242
+    - type: recall_at_5
+      value: 14.493
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 38.601
+    - type: map_at_10
+      value: 55.293000000000006
+    - type: map_at_100
+      value: 56.092
+    - type: map_at_1000
+      value: 56.111999999999995
+    - type: map_at_3
+      value: 51.269
+    - type: map_at_5
+      value: 53.787
+    - type: mrr_at_1
+      value: 43.221
+    - type: mrr_at_10
+      value: 57.882999999999996
+    - type: mrr_at_100
+      value: 58.408
+    - type: mrr_at_1000
+      value: 58.421
+    - type: mrr_at_3
+      value: 54.765
+    - type: mrr_at_5
+      value: 56.809
+    - type: ndcg_at_1
+      value: 43.221
+    - type: ndcg_at_10
+      value: 62.858999999999995
+    - type: ndcg_at_100
+      value: 65.987
+    - type: ndcg_at_1000
+      value: 66.404
+    - type: ndcg_at_3
+      value: 55.605000000000004
+    - type: ndcg_at_5
+      value: 59.723000000000006
+    - type: precision_at_1
+      value: 43.221
+    - type: precision_at_10
+      value: 9.907
+    - type: precision_at_100
+      value: 1.169
+    - type: precision_at_1000
+      value: 0.121
+    - type: precision_at_3
+      value: 25.019000000000002
+    - type: precision_at_5
+      value: 17.474
+    - type: recall_at_1
+      value: 38.601
+    - type: recall_at_10
+      value: 82.966
+    - type: recall_at_100
+      value: 96.154
+    - type: recall_at_1000
+      value: 99.223
+    - type: recall_at_3
+      value: 64.603
+    - type: recall_at_5
+      value: 73.97200000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 70.77
+    - type: map_at_10
+      value: 84.429
+    - type: map_at_100
+      value: 85.04599999999999
+    - type: map_at_1000
+      value: 85.065
+    - type: map_at_3
+      value: 81.461
+    - type: map_at_5
+      value: 83.316
+    - type: mrr_at_1
+      value: 81.51
+    - type: mrr_at_10
+      value: 87.52799999999999
+    - type: mrr_at_100
+      value: 87.631
+    - type: mrr_at_1000
+      value: 87.632
+    - type: mrr_at_3
+      value: 86.533
+    - type: mrr_at_5
+      value: 87.214
+    - type: ndcg_at_1
+      value: 81.47999999999999
+    - type: ndcg_at_10
+      value: 88.181
+    - type: ndcg_at_100
+      value: 89.39200000000001
+    - type: ndcg_at_1000
+      value: 89.52
+    - type: ndcg_at_3
+      value: 85.29299999999999
+    - type: ndcg_at_5
+      value: 86.88
+    - type: precision_at_1
+      value: 81.47999999999999
+    - type: precision_at_10
+      value: 13.367
+    - type: precision_at_100
+      value: 1.5230000000000001
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 37.227
+    - type: precision_at_5
+      value: 24.494
+    - type: recall_at_1
+      value: 70.77
+    - type: recall_at_10
+      value: 95.199
+    - type: recall_at_100
+      value: 99.37700000000001
+    - type: recall_at_1000
+      value: 99.973
+    - type: recall_at_3
+      value: 86.895
+    - type: recall_at_5
+      value: 91.396
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 50.686353396858344
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 61.3664675312921
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.7379999999999995
+    - type: map_at_10
+      value: 12.01
+    - type: map_at_100
+      value: 14.02
+    - type: map_at_1000
+      value: 14.310999999999998
+    - type: map_at_3
+      value: 8.459
+    - type: map_at_5
+      value: 10.281
+    - type: mrr_at_1
+      value: 23.3
+    - type: mrr_at_10
+      value: 34.108
+    - type: mrr_at_100
+      value: 35.217
+    - type: mrr_at_1000
+      value: 35.272
+    - type: mrr_at_3
+      value: 30.833
+    - type: mrr_at_5
+      value: 32.768
+    - type: ndcg_at_1
+      value: 23.3
+    - type: ndcg_at_10
+      value: 20.116999999999997
+    - type: ndcg_at_100
+      value: 27.961000000000002
+    - type: ndcg_at_1000
+      value: 33.149
+    - type: ndcg_at_3
+      value: 18.902
+    - type: ndcg_at_5
+      value: 16.742
+    - type: precision_at_1
+      value: 23.3
+    - type: precision_at_10
+      value: 10.47
+    - type: precision_at_100
+      value: 2.177
+    - type: precision_at_1000
+      value: 0.34299999999999997
+    - type: precision_at_3
+      value: 17.567
+    - type: precision_at_5
+      value: 14.78
+    - type: recall_at_1
+      value: 4.7379999999999995
+    - type: recall_at_10
+      value: 21.221999999999998
+    - type: recall_at_100
+      value: 44.242
+    - type: recall_at_1000
+      value: 69.652
+    - type: recall_at_3
+      value: 10.688
+    - type: recall_at_5
+      value: 14.982999999999999
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.84572946827069
+    - type: cos_sim_spearman
+      value: 80.48508130408966
+    - type: euclidean_pearson
+      value: 82.0481530027767
+    - type: euclidean_spearman
+      value: 80.45902876782752
+    - type: manhattan_pearson
+      value: 82.03728222483326
+    - type: manhattan_spearman
+      value: 80.45684282911755
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.33476464677516
+    - type: cos_sim_spearman
+      value: 75.93057758003266
+    - type: euclidean_pearson
+      value: 80.89685744015691
+    - type: euclidean_spearman
+      value: 76.29929953441706
+    - type: manhattan_pearson
+      value: 80.91391345459995
+    - type: manhattan_spearman
+      value: 76.31985463110914
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.63686106359005
+    - type: cos_sim_spearman
+      value: 85.22240034668202
+    - type: euclidean_pearson
+      value: 84.6074814189106
+    - type: euclidean_spearman
+      value: 85.17169644755828
+    - type: manhattan_pearson
+      value: 84.48329306239368
+    - type: manhattan_spearman
+      value: 85.0086508544768
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.95455774064745
+    - type: cos_sim_spearman
+      value: 80.54074646118492
+    - type: euclidean_pearson
+      value: 81.79598955554704
+    - type: euclidean_spearman
+      value: 80.55837617606814
+    - type: manhattan_pearson
+      value: 81.78213797905386
+    - type: manhattan_spearman
+      value: 80.5666746878273
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.92813309124739
+    - type: cos_sim_spearman
+      value: 88.81459873052108
+    - type: euclidean_pearson
+      value: 88.21193118930564
+    - type: euclidean_spearman
+      value: 88.87072745043731
+    - type: manhattan_pearson
+      value: 88.22576929706727
+    - type: manhattan_spearman
+      value: 88.8867671095791
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.6881529671839
+    - type: cos_sim_spearman
+      value: 85.2807092969554
+    - type: euclidean_pearson
+      value: 84.62334178652704
+    - type: euclidean_spearman
+      value: 85.2116373296784
+    - type: manhattan_pearson
+      value: 84.54948211541777
+    - type: manhattan_spearman
+      value: 85.10737722637882
+  - 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: 88.55963694458408
+    - type: cos_sim_spearman
+      value: 89.36731628848683
+    - type: euclidean_pearson
+      value: 89.64975952985465
+    - type: euclidean_spearman
+      value: 89.29689484033007
+    - type: manhattan_pearson
+      value: 89.61234491713135
+    - type: manhattan_spearman
+      value: 89.20302520255782
+  - 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: 62.411800961903886
+    - type: cos_sim_spearman
+      value: 62.99105515749963
+    - type: euclidean_pearson
+      value: 65.29826669549443
+    - type: euclidean_spearman
+      value: 63.29880964105775
+    - type: manhattan_pearson
+      value: 65.00126190601183
+    - type: manhattan_spearman
+      value: 63.32011025899179
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.83498531837608
+    - type: cos_sim_spearman
+      value: 87.21366640615442
+    - type: euclidean_pearson
+      value: 86.74764288798261
+    - type: euclidean_spearman
+      value: 87.06060470780834
+    - type: manhattan_pearson
+      value: 86.65971223951476
+    - type: manhattan_spearman
+      value: 86.99814399831457
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 83.94448463485881
+    - type: mrr
+      value: 95.36291867174221
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 59.928000000000004
+    - type: map_at_10
+      value: 68.577
+    - type: map_at_100
+      value: 69.35900000000001
+    - type: map_at_1000
+      value: 69.37299999999999
+    - type: map_at_3
+      value: 66.217
+    - type: map_at_5
+      value: 67.581
+    - type: mrr_at_1
+      value: 63.0
+    - type: mrr_at_10
+      value: 69.994
+    - type: mrr_at_100
+      value: 70.553
+    - type: mrr_at_1000
+      value: 70.56700000000001
+    - type: mrr_at_3
+      value: 68.167
+    - type: mrr_at_5
+      value: 69.11699999999999
+    - type: ndcg_at_1
+      value: 63.0
+    - type: ndcg_at_10
+      value: 72.58
+    - type: ndcg_at_100
+      value: 75.529
+    - type: ndcg_at_1000
+      value: 76.009
+    - type: ndcg_at_3
+      value: 68.523
+    - type: ndcg_at_5
+      value: 70.301
+    - type: precision_at_1
+      value: 63.0
+    - type: precision_at_10
+      value: 9.333
+    - type: precision_at_100
+      value: 1.09
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 26.444000000000003
+    - type: precision_at_5
+      value: 17.067
+    - type: recall_at_1
+      value: 59.928000000000004
+    - type: recall_at_10
+      value: 83.544
+    - type: recall_at_100
+      value: 96.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 72.072
+    - type: recall_at_5
+      value: 76.683
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.82178217821782
+    - type: cos_sim_ap
+      value: 95.41507679819003
+    - type: cos_sim_f1
+      value: 90.9456740442656
+    - type: cos_sim_precision
+      value: 91.49797570850203
+    - type: cos_sim_recall
+      value: 90.4
+    - type: dot_accuracy
+      value: 99.77227722772277
+    - type: dot_ap
+      value: 92.50123869445967
+    - type: dot_f1
+      value: 88.18414322250638
+    - type: dot_precision
+      value: 90.26178010471205
+    - type: dot_recall
+      value: 86.2
+    - type: euclidean_accuracy
+      value: 99.81782178217821
+    - type: euclidean_ap
+      value: 95.3935066749006
+    - type: euclidean_f1
+      value: 90.66128218071681
+    - type: euclidean_precision
+      value: 91.53924566768603
+    - type: euclidean_recall
+      value: 89.8
+    - type: manhattan_accuracy
+      value: 99.81881188118813
+    - type: manhattan_ap
+      value: 95.39767454613512
+    - type: manhattan_f1
+      value: 90.62019477191186
+    - type: manhattan_precision
+      value: 92.95478443743428
+    - type: manhattan_recall
+      value: 88.4
+    - type: max_accuracy
+      value: 99.82178217821782
+    - type: max_ap
+      value: 95.41507679819003
+    - type: max_f1
+      value: 90.9456740442656
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 64.96313921233748
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 33.602625720956745
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 51.32659230651731
+    - type: mrr
+      value: 52.33861726508785
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 25.658532855940212
+    - type: cos_sim_spearman
+      value: 25.202702076359323
+    - type: dot_pearson
+      value: 21.585479641185145
+    - type: dot_spearman
+      value: 23.03461045573253
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.22
+    - type: map_at_10
+      value: 1.9539999999999997
+    - type: map_at_100
+      value: 11.437
+    - type: map_at_1000
+      value: 27.861000000000004
+    - type: map_at_3
+      value: 0.6479999999999999
+    - type: map_at_5
+      value: 1.0410000000000001
+    - type: mrr_at_1
+      value: 84.0
+    - type: mrr_at_10
+      value: 90.333
+    - type: mrr_at_100
+      value: 90.333
+    - type: mrr_at_1000
+      value: 90.333
+    - type: mrr_at_3
+      value: 90.333
+    - type: mrr_at_5
+      value: 90.333
+    - type: ndcg_at_1
+      value: 80.0
+    - type: ndcg_at_10
+      value: 78.31700000000001
+    - type: ndcg_at_100
+      value: 59.396
+    - type: ndcg_at_1000
+      value: 52.733
+    - type: ndcg_at_3
+      value: 81.46900000000001
+    - type: ndcg_at_5
+      value: 80.74
+    - type: precision_at_1
+      value: 84.0
+    - type: precision_at_10
+      value: 84.0
+    - type: precision_at_100
+      value: 60.980000000000004
+    - type: precision_at_1000
+      value: 23.432
+    - type: precision_at_3
+      value: 87.333
+    - type: precision_at_5
+      value: 86.8
+    - type: recall_at_1
+      value: 0.22
+    - type: recall_at_10
+      value: 2.156
+    - type: recall_at_100
+      value: 14.557999999999998
+    - type: recall_at_1000
+      value: 49.553999999999995
+    - type: recall_at_3
+      value: 0.685
+    - type: recall_at_5
+      value: 1.121
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 3.373
+    - type: map_at_10
+      value: 11.701
+    - type: map_at_100
+      value: 17.144000000000002
+    - type: map_at_1000
+      value: 18.624
+    - type: map_at_3
+      value: 6.552
+    - type: map_at_5
+      value: 9.372
+    - type: mrr_at_1
+      value: 38.775999999999996
+    - type: mrr_at_10
+      value: 51.975
+    - type: mrr_at_100
+      value: 52.873999999999995
+    - type: mrr_at_1000
+      value: 52.873999999999995
+    - type: mrr_at_3
+      value: 47.619
+    - type: mrr_at_5
+      value: 50.578
+    - type: ndcg_at_1
+      value: 36.735
+    - type: ndcg_at_10
+      value: 27.212999999999997
+    - type: ndcg_at_100
+      value: 37.245
+    - type: ndcg_at_1000
+      value: 48.602000000000004
+    - type: ndcg_at_3
+      value: 30.916
+    - type: ndcg_at_5
+      value: 30.799
+    - type: precision_at_1
+      value: 38.775999999999996
+    - type: precision_at_10
+      value: 23.469
+    - type: precision_at_100
+      value: 7.327
+    - type: precision_at_1000
+      value: 1.486
+    - type: precision_at_3
+      value: 31.973000000000003
+    - type: precision_at_5
+      value: 32.245000000000005
+    - type: recall_at_1
+      value: 3.373
+    - type: recall_at_10
+      value: 17.404
+    - type: recall_at_100
+      value: 46.105000000000004
+    - type: recall_at_1000
+      value: 80.35
+    - type: recall_at_3
+      value: 7.4399999999999995
+    - type: recall_at_5
+      value: 12.183
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 70.5592
+    - type: ap
+      value: 14.330910591410134
+    - type: f1
+      value: 54.45745186286521
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 61.20543293718167
+    - type: f1
+      value: 61.45365480309872
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 43.81162998944145
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 86.69011146212075
+    - type: cos_sim_ap
+      value: 76.09792353652536
+    - type: cos_sim_f1
+      value: 70.10202763786646
+    - type: cos_sim_precision
+      value: 68.65671641791045
+    - type: cos_sim_recall
+      value: 71.60949868073878
+    - type: dot_accuracy
+      value: 85.33110806461227
+    - type: dot_ap
+      value: 70.19304383327554
+    - type: dot_f1
+      value: 67.22494202525122
+    - type: dot_precision
+      value: 65.6847935548842
+    - type: dot_recall
+      value: 68.83905013192611
+    - type: euclidean_accuracy
+      value: 86.5410979316922
+    - type: euclidean_ap
+      value: 75.91906915651882
+    - type: euclidean_f1
+      value: 69.6798975672215
+    - type: euclidean_precision
+      value: 67.6865671641791
+    - type: euclidean_recall
+      value: 71.79419525065963
+    - type: manhattan_accuracy
+      value: 86.60070334386363
+    - type: manhattan_ap
+      value: 75.94617413885031
+    - type: manhattan_f1
+      value: 69.52689565780946
+    - type: manhattan_precision
+      value: 68.3312101910828
+    - type: manhattan_recall
+      value: 70.76517150395777
+    - type: max_accuracy
+      value: 86.69011146212075
+    - type: max_ap
+      value: 76.09792353652536
+    - type: max_f1
+      value: 70.10202763786646
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.25951798812434
+    - type: cos_sim_ap
+      value: 86.31476416599727
+    - type: cos_sim_f1
+      value: 78.52709971038477
+    - type: cos_sim_precision
+      value: 76.7629972792117
+    - type: cos_sim_recall
+      value: 80.37419156144134
+    - type: dot_accuracy
+      value: 88.03896456708192
+    - type: dot_ap
+      value: 83.26963599196237
+    - type: dot_f1
+      value: 76.72696459492317
+    - type: dot_precision
+      value: 73.56411162133521
+    - type: dot_recall
+      value: 80.17400677548507
+    - type: euclidean_accuracy
+      value: 89.21682772538519
+    - type: euclidean_ap
+      value: 86.29306071289969
+    - type: euclidean_f1
+      value: 78.40827030519554
+    - type: euclidean_precision
+      value: 77.42250243939053
+    - type: euclidean_recall
+      value: 79.41946412072683
+    - type: manhattan_accuracy
+      value: 89.22458959133776
+    - type: manhattan_ap
+      value: 86.2901934710645
+    - type: manhattan_f1
+      value: 78.54211378440453
+    - type: manhattan_precision
+      value: 76.85505858079729
+    - type: manhattan_recall
+      value: 80.30489682784109
+    - type: max_accuracy
+      value: 89.25951798812434
+    - type: max_ap
+      value: 86.31476416599727
+    - type: max_f1
+      value: 78.54211378440453
+---
+
+## E5-large
+
+[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 384.
+
+## 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
+from transformers.modeling_outputs import BaseModelOutput
+
+
+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-large')
+model = AutoModel.from_pretrained('intfloat/e5-large')
+
+# Tokenize the input texts
+batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')
+
+outputs: BaseModelOutput = 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[: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).
+

config.json

@@ -0,0 +1,25 @@
+{
+  "_name_or_path": "tmp/",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.15.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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+oid sha256:c2895f5b85318ea318234e2f9a5b81b957fdee46a24b196050d5c6df56c83200
+size 1340718961

special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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+{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "amlt/1101_large_qd_prompt_lr1e4_t001_ft_random_swap_nli/all_kd_ft/checkpoint-6000", "tokenizer_class": "BertTokenizer"}