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README.md

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+---
+base_model:
+- Salesforce/SFR-Embedding-2_R
+tags:
+- bnb-my-repo
+- mteb
+- sentence-transformers
+- transformers
+model-index:
+- name: Salesforce/SFR-Embedding-2_R
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 92.71641791044776
+    - type: ap
+      value: 69.47931007147756
+    - type: f1
+      value: 88.0252625393374
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 97.31075
+    - type: ap
+      value: 96.26693923450127
+    - type: f1
+      value: 97.31042448894502
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 61.040000000000006
+    - type: f1
+      value: 60.78646832640785
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
+    metrics:
+    - type: map_at_1
+      value: 37.767
+    - type: map_at_10
+      value: 53.908
+    - type: map_at_100
+      value: 54.583000000000006
+    - type: map_at_1000
+      value: 54.583999999999996
+    - type: map_at_20
+      value: 54.50899999999999
+    - type: map_at_3
+      value: 49.514
+    - type: map_at_5
+      value: 52.059999999999995
+    - type: mrr_at_1
+      value: 38.26458036984353
+    - type: mrr_at_10
+      value: 54.120408001987066
+    - type: mrr_at_100
+      value: 54.780719904297406
+    - type: mrr_at_1000
+      value: 54.78174226698592
+    - type: mrr_at_20
+      value: 54.706604527160295
+    - type: mrr_at_3
+      value: 49.71550497866294
+    - type: mrr_at_5
+      value: 52.247510668563436
+    - type: ndcg_at_1
+      value: 37.767
+    - type: ndcg_at_10
+      value: 62.339999999999996
+    - type: ndcg_at_100
+      value: 64.89399999999999
+    - type: ndcg_at_1000
+      value: 64.914
+    - type: ndcg_at_20
+      value: 64.402
+    - type: ndcg_at_3
+      value: 53.33
+    - type: ndcg_at_5
+      value: 57.93899999999999
+    - type: precision_at_1
+      value: 37.767
+    - type: precision_at_10
+      value: 8.905000000000001
+    - type: precision_at_100
+      value: 0.9950000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_20
+      value: 4.8469999999999995
+    - type: precision_at_3
+      value: 21.456
+    - type: precision_at_5
+      value: 15.121
+    - type: recall_at_1
+      value: 37.767
+    - type: recall_at_10
+      value: 89.047
+    - type: recall_at_100
+      value: 99.502
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_20
+      value: 96.942
+    - type: recall_at_3
+      value: 64.36699999999999
+    - type: recall_at_5
+      value: 75.605
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 54.024325012036314
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 48.817300846601675
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 66.71478959728732
+    - type: mrr
+      value: 79.07202216066482
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.79517914982239
+    - type: cos_sim_spearman
+      value: 87.60440576436838
+    - type: euclidean_pearson
+      value: 87.75596873521118
+    - type: euclidean_spearman
+      value: 87.60440576436838
+    - type: manhattan_pearson
+      value: 87.74113773865973
+    - type: manhattan_spearman
+      value: 87.50560833247899
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 90.02272727272727
+    - type: f1
+      value: 89.96681880265936
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 50.75930389699286
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 46.57286439805565
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
+    metrics:
+    - type: map_at_1
+      value: 28.056666666666665
+    - type: map_at_10
+      value: 39.61749999999999
+    - type: map_at_100
+      value: 41.00666666666666
+    - type: map_at_1000
+      value: 41.11358333333334
+    - type: map_at_20
+      value: 40.410250000000005
+    - type: map_at_3
+      value: 35.98591666666667
+    - type: map_at_5
+      value: 38.02
+    - type: mrr_at_1
+      value: 33.73950708467142
+    - type: mrr_at_10
+      value: 44.0987162763402
+    - type: mrr_at_100
+      value: 44.94302678553521
+    - type: mrr_at_1000
+      value: 44.98758207055161
+    - type: mrr_at_20
+      value: 44.61156907536121
+    - type: mrr_at_3
+      value: 41.247253732468415
+    - type: mrr_at_5
+      value: 42.84859071071954
+    - type: ndcg_at_1
+      value: 33.739666666666665
+    - type: ndcg_at_10
+      value: 46.10683333333334
+    - type: ndcg_at_100
+      value: 51.49275000000001
+    - type: ndcg_at_1000
+      value: 53.2585
+    - type: ndcg_at_20
+      value: 48.349
+    - type: ndcg_at_3
+      value: 40.12416666666667
+    - type: ndcg_at_5
+      value: 42.94783333333333
+    - type: precision_at_1
+      value: 33.739666666666665
+    - type: precision_at_10
+      value: 8.46025
+    - type: precision_at_100
+      value: 1.3215833333333333
+    - type: precision_at_1000
+      value: 0.16524999999999998
+    - type: precision_at_20
+      value: 4.9935833333333335
+    - type: precision_at_3
+      value: 19.00516666666667
+    - type: precision_at_5
+      value: 13.72141666666667
+    - type: recall_at_1
+      value: 28.056666666666665
+    - type: recall_at_10
+      value: 60.68825000000001
+    - type: recall_at_100
+      value: 83.74433333333334
+    - type: recall_at_1000
+      value: 95.62299999999999
+    - type: recall_at_20
+      value: 68.77641666666668
+    - type: recall_at_3
+      value: 44.06991666666667
+    - type: recall_at_5
+      value: 51.324999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
+    metrics:
+    - type: map_at_1
+      value: 15.609
+    - type: map_at_10
+      value: 25.584
+    - type: map_at_100
+      value: 27.291999999999998
+    - type: map_at_1000
+      value: 27.471
+    - type: map_at_20
+      value: 26.497
+    - type: map_at_3
+      value: 21.61
+    - type: map_at_5
+      value: 23.76
+    - type: mrr_at_1
+      value: 34.98371335504886
+    - type: mrr_at_10
+      value: 45.73747479447807
+    - type: mrr_at_100
+      value: 46.4973410206458
+    - type: mrr_at_1000
+      value: 46.53372527933685
+    - type: mrr_at_20
+      value: 46.19978503202757
+    - type: mrr_at_3
+      value: 42.85559174809991
+    - type: mrr_at_5
+      value: 44.65038002171556
+    - type: ndcg_at_1
+      value: 34.984
+    - type: ndcg_at_10
+      value: 34.427
+    - type: ndcg_at_100
+      value: 40.908
+    - type: ndcg_at_1000
+      value: 44.118
+    - type: ndcg_at_20
+      value: 36.885
+    - type: ndcg_at_3
+      value: 29.09
+    - type: ndcg_at_5
+      value: 30.979
+    - type: precision_at_1
+      value: 34.984
+    - type: precision_at_10
+      value: 10.476
+    - type: precision_at_100
+      value: 1.748
+    - type: precision_at_1000
+      value: 0.23500000000000001
+    - type: precision_at_20
+      value: 6.313000000000001
+    - type: precision_at_3
+      value: 21.39
+    - type: precision_at_5
+      value: 16.378
+    - type: recall_at_1
+      value: 15.609
+    - type: recall_at_10
+      value: 39.619
+    - type: recall_at_100
+      value: 61.952
+    - type: recall_at_1000
+      value: 79.861
+    - type: recall_at_20
+      value: 46.489000000000004
+    - type: recall_at_3
+      value: 26.134
+    - type: recall_at_5
+      value: 31.955
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/dbpedia
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
+    metrics:
+    - type: map_at_1
+      value: 10.482
+    - type: map_at_10
+      value: 25.155
+    - type: map_at_100
+      value: 36.606
+    - type: map_at_1000
+      value: 38.617000000000004
+    - type: map_at_20
+      value: 29.676000000000002
+    - type: map_at_3
+      value: 16.881
+    - type: map_at_5
+      value: 20.043
+    - type: mrr_at_1
+      value: 76.0
+    - type: mrr_at_10
+      value: 82.5610119047619
+    - type: mrr_at_100
+      value: 82.74795937825128
+    - type: mrr_at_1000
+      value: 82.75526942226163
+    - type: mrr_at_20
+      value: 82.70580357142858
+    - type: mrr_at_3
+      value: 81.41666666666667
+    - type: mrr_at_5
+      value: 82.26666666666667
+    - type: ndcg_at_1
+      value: 63.625
+    - type: ndcg_at_10
+      value: 51.214000000000006
+    - type: ndcg_at_100
+      value: 56.411
+    - type: ndcg_at_1000
+      value: 63.429
+    - type: ndcg_at_20
+      value: 50.595
+    - type: ndcg_at_3
+      value: 54.989
+    - type: ndcg_at_5
+      value: 52.589
+    - type: precision_at_1
+      value: 76.0
+    - type: precision_at_10
+      value: 41.975
+    - type: precision_at_100
+      value: 13.26
+    - type: precision_at_1000
+      value: 2.493
+    - type: precision_at_20
+      value: 32.15
+    - type: precision_at_3
+      value: 59.0
+    - type: precision_at_5
+      value: 51.24999999999999
+    - type: recall_at_1
+      value: 10.482
+    - type: recall_at_10
+      value: 31.075000000000003
+    - type: recall_at_100
+      value: 63.119
+    - type: recall_at_1000
+      value: 85.32300000000001
+    - type: recall_at_20
+      value: 40.345
+    - type: recall_at_3
+      value: 17.916
+    - type: recall_at_5
+      value: 22.475
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 93.36500000000001
+    - type: f1
+      value: 89.89541440183861
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
+    metrics:
+    - type: map_at_1
+      value: 81.948
+    - type: map_at_10
+      value: 89.47500000000001
+    - type: map_at_100
+      value: 89.66199999999999
+    - type: map_at_1000
+      value: 89.671
+    - type: map_at_20
+      value: 89.582
+    - type: map_at_3
+      value: 88.646
+    - type: map_at_5
+      value: 89.19
+    - type: mrr_at_1
+      value: 88.23882388238825
+    - type: mrr_at_10
+      value: 93.2122736083131
+    - type: mrr_at_100
+      value: 93.23908769526588
+    - type: mrr_at_1000
+      value: 93.23932393435209
+    - type: mrr_at_20
+      value: 93.23217832106207
+    - type: mrr_at_3
+      value: 92.98679867986787
+    - type: mrr_at_5
+      value: 93.16906690669056
+    - type: ndcg_at_1
+      value: 88.239
+    - type: ndcg_at_10
+      value: 92.155
+    - type: ndcg_at_100
+      value: 92.735
+    - type: ndcg_at_1000
+      value: 92.866
+    - type: ndcg_at_20
+      value: 92.39699999999999
+    - type: ndcg_at_3
+      value: 91.188
+    - type: ndcg_at_5
+      value: 91.754
+    - type: precision_at_1
+      value: 88.239
+    - type: precision_at_10
+      value: 10.903
+    - type: precision_at_100
+      value: 1.147
+    - type: precision_at_1000
+      value: 0.117
+    - type: precision_at_20
+      value: 5.5440000000000005
+    - type: precision_at_3
+      value: 34.598
+    - type: precision_at_5
+      value: 21.302
+    - type: recall_at_1
+      value: 81.948
+    - type: recall_at_10
+      value: 96.518
+    - type: recall_at_100
+      value: 98.646
+    - type: recall_at_1000
+      value: 99.399
+    - type: recall_at_20
+      value: 97.262
+    - type: recall_at_3
+      value: 93.89800000000001
+    - type: recall_at_5
+      value: 95.38600000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
+    metrics:
+    - type: map_at_1
+      value: 32.033
+    - type: map_at_10
+      value: 53.55
+    - type: map_at_100
+      value: 55.672
+    - type: map_at_1000
+      value: 55.764
+    - type: map_at_20
+      value: 54.87800000000001
+    - type: map_at_3
+      value: 46.761
+    - type: map_at_5
+      value: 50.529
+    - type: mrr_at_1
+      value: 60.95679012345679
+    - type: mrr_at_10
+      value: 68.70835782872815
+    - type: mrr_at_100
+      value: 69.21918402444501
+    - type: mrr_at_1000
+      value: 69.23608783148705
+    - type: mrr_at_20
+      value: 69.07497388036454
+    - type: mrr_at_3
+      value: 66.76954732510285
+    - type: mrr_at_5
+      value: 67.95781893004109
+    - type: ndcg_at_1
+      value: 60.956999999999994
+    - type: ndcg_at_10
+      value: 61.766
+    - type: ndcg_at_100
+      value: 67.652
+    - type: ndcg_at_1000
+      value: 68.94500000000001
+    - type: ndcg_at_20
+      value: 64.48700000000001
+    - type: ndcg_at_3
+      value: 57.25
+    - type: ndcg_at_5
+      value: 58.64
+    - type: precision_at_1
+      value: 60.956999999999994
+    - type: precision_at_10
+      value: 17.083000000000002
+    - type: precision_at_100
+      value: 2.346
+    - type: precision_at_1000
+      value: 0.257
+    - type: precision_at_20
+      value: 9.807
+    - type: precision_at_3
+      value: 38.477
+    - type: precision_at_5
+      value: 27.962999999999997
+    - type: recall_at_1
+      value: 32.033
+    - type: recall_at_10
+      value: 69.44
+    - type: recall_at_100
+      value: 90.17500000000001
+    - type: recall_at_1000
+      value: 97.90100000000001
+    - type: recall_at_20
+      value: 77.629
+    - type: recall_at_3
+      value: 51.664
+    - type: recall_at_5
+      value: 59.565
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: ab518f4d6fcca38d87c25209f94beba119d02014
+    metrics:
+    - type: map_at_1
+      value: 42.741
+    - type: map_at_10
+      value: 74.811
+    - type: map_at_100
+      value: 75.508
+    - type: map_at_1000
+      value: 75.541
+    - type: map_at_20
+      value: 75.25699999999999
+    - type: map_at_3
+      value: 71.31
+    - type: map_at_5
+      value: 73.69
+    - type: mrr_at_1
+      value: 85.48278190411884
+    - type: mrr_at_10
+      value: 90.20347684425987
+    - type: mrr_at_100
+      value: 90.29734129342121
+    - type: mrr_at_1000
+      value: 90.30017606259217
+    - type: mrr_at_20
+      value: 90.27225310310567
+    - type: mrr_at_3
+      value: 89.67364393427842
+    - type: mrr_at_5
+      value: 90.02408282691847
+    - type: ndcg_at_1
+      value: 85.483
+    - type: ndcg_at_10
+      value: 81.361
+    - type: ndcg_at_100
+      value: 83.588
+    - type: ndcg_at_1000
+      value: 84.19
+    - type: ndcg_at_20
+      value: 82.42699999999999
+    - type: ndcg_at_3
+      value: 76.779
+    - type: ndcg_at_5
+      value: 79.581
+    - type: precision_at_1
+      value: 85.483
+    - type: precision_at_10
+      value: 17.113
+    - type: precision_at_100
+      value: 1.882
+    - type: precision_at_1000
+      value: 0.196
+    - type: precision_at_20
+      value: 8.899
+    - type: precision_at_3
+      value: 50.397999999999996
+    - type: precision_at_5
+      value: 32.443
+    - type: recall_at_1
+      value: 42.741
+    - type: recall_at_10
+      value: 85.564
+    - type: recall_at_100
+      value: 94.07799999999999
+    - type: recall_at_1000
+      value: 97.995
+    - type: recall_at_20
+      value: 88.98700000000001
+    - type: recall_at_3
+      value: 75.598
+    - type: recall_at_5
+      value: 81.107
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 96.80320000000002
+    - type: ap
+      value: 94.98856145360044
+    - type: f1
+      value: 96.80287885839178
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: c5a29a104738b98a9e76336939199e264163d4a0
+    metrics:
+    - type: map_at_1
+      value: 22.539
+    - type: map_at_10
+      value: 35.109
+    - type: map_at_100
+      value: 36.287000000000006
+    - type: map_at_1000
+      value: 36.335
+    - type: map_at_20
+      value: 35.838
+    - type: map_at_3
+      value: 31.11
+    - type: map_at_5
+      value: 33.455
+    - type: mrr_at_1
+      value: 23.15186246418338
+    - type: mrr_at_10
+      value: 35.70532018920268
+    - type: mrr_at_100
+      value: 36.815167506137584
+    - type: mrr_at_1000
+      value: 36.85695349443505
+    - type: mrr_at_20
+      value: 36.39500867880642
+    - type: mrr_at_3
+      value: 31.81232091690535
+    - type: mrr_at_5
+      value: 34.096704871060155
+    - type: ndcg_at_1
+      value: 23.152
+    - type: ndcg_at_10
+      value: 42.181999999999995
+    - type: ndcg_at_100
+      value: 47.847
+    - type: ndcg_at_1000
+      value: 48.988
+    - type: ndcg_at_20
+      value: 44.767
+    - type: ndcg_at_3
+      value: 34.088
+    - type: ndcg_at_5
+      value: 38.257999999999996
+    - type: precision_at_1
+      value: 23.152
+    - type: precision_at_10
+      value: 6.678000000000001
+    - type: precision_at_100
+      value: 0.9530000000000001
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_20
+      value: 3.881
+    - type: precision_at_3
+      value: 14.518
+    - type: precision_at_5
+      value: 10.831
+    - type: recall_at_1
+      value: 22.539
+    - type: recall_at_10
+      value: 63.965
+    - type: recall_at_100
+      value: 90.129
+    - type: recall_at_1000
+      value: 98.721
+    - type: recall_at_20
+      value: 74.00999999999999
+    - type: recall_at_3
+      value: 42.004999999999995
+    - type: recall_at_5
+      value: 52.028
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 98.5750113999088
+    - type: f1
+      value: 98.41576079230245
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 91.29502963976289
+    - type: f1
+      value: 74.84400169335184
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 85.96839273705447
+    - type: f1
+      value: 82.43129186593926
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 90.60860793544047
+    - type: f1
+      value: 89.79415994859477
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 46.661892807041355
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 44.17598473858937
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
+    metrics:
+    - type: map
+      value: 31.260919294024603
+    - type: mrr
+      value: 32.37049108835034
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
+    metrics:
+    - type: map_at_1
+      value: 6.672000000000001
+    - type: map_at_10
+      value: 15.972
+    - type: map_at_100
+      value: 20.94
+    - type: map_at_1000
+      value: 22.877
+    - type: map_at_20
+      value: 17.986
+    - type: map_at_3
+      value: 11.161
+    - type: map_at_5
+      value: 13.293
+    - type: mrr_at_1
+      value: 53.56037151702786
+    - type: mrr_at_10
+      value: 61.915696103002595
+    - type: mrr_at_100
+      value: 62.4130902631107
+    - type: mrr_at_1000
+      value: 62.45228087711845
+    - type: mrr_at_20
+      value: 62.1983715004112
+    - type: mrr_at_3
+      value: 60.31991744066049
+    - type: mrr_at_5
+      value: 61.27966976264191
+    - type: ndcg_at_1
+      value: 50.929
+    - type: ndcg_at_10
+      value: 41.336
+    - type: ndcg_at_100
+      value: 38.586999999999996
+    - type: ndcg_at_1000
+      value: 48.155
+    - type: ndcg_at_20
+      value: 38.888
+    - type: ndcg_at_3
+      value: 47.0
+    - type: ndcg_at_5
+      value: 44.335
+    - type: precision_at_1
+      value: 53.251000000000005
+    - type: precision_at_10
+      value: 31.146
+    - type: precision_at_100
+      value: 10.040000000000001
+    - type: precision_at_1000
+      value: 2.432
+    - type: precision_at_20
+      value: 23.421
+    - type: precision_at_3
+      value: 45.098
+    - type: precision_at_5
+      value: 39.071
+    - type: recall_at_1
+      value: 6.672000000000001
+    - type: recall_at_10
+      value: 20.764
+    - type: recall_at_100
+      value: 40.759
+    - type: recall_at_1000
+      value: 75.015
+    - type: recall_at_20
+      value: 25.548
+    - type: recall_at_3
+      value: 12.328
+    - type: recall_at_5
+      value: 15.601999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
+    metrics:
+    - type: map_at_1
+      value: 50.944
+    - type: map_at_10
+      value: 67.565
+    - type: map_at_100
+      value: 68.10300000000001
+    - type: map_at_1000
+      value: 68.109
+    - type: map_at_20
+      value: 67.973
+    - type: map_at_3
+      value: 64.176
+    - type: map_at_5
+      value: 66.39699999999999
+    - type: mrr_at_1
+      value: 57.01042873696408
+    - type: mrr_at_10
+      value: 69.76629605105849
+    - type: mrr_at_100
+      value: 70.09927347130204
+    - type: mrr_at_1000
+      value: 70.10309675839956
+    - type: mrr_at_20
+      value: 70.02288627712392
+    - type: mrr_at_3
+      value: 67.46813441483191
+    - type: mrr_at_5
+      value: 68.93105446118189
+    - type: ndcg_at_1
+      value: 57.010000000000005
+    - type: ndcg_at_10
+      value: 73.956
+    - type: ndcg_at_100
+      value: 75.90299999999999
+    - type: ndcg_at_1000
+      value: 76.03999999999999
+    - type: ndcg_at_20
+      value: 75.17
+    - type: ndcg_at_3
+      value: 68.13900000000001
+    - type: ndcg_at_5
+      value: 71.532
+    - type: precision_at_1
+      value: 57.010000000000005
+    - type: precision_at_10
+      value: 10.91
+    - type: precision_at_100
+      value: 1.2
+    - type: precision_at_1000
+      value: 0.121
+    - type: precision_at_20
+      value: 5.753
+    - type: precision_at_3
+      value: 29.828
+    - type: precision_at_5
+      value: 19.971
+    - type: recall_at_1
+      value: 50.944
+    - type: recall_at_10
+      value: 90.754
+    - type: recall_at_100
+      value: 98.699
+    - type: recall_at_1000
+      value: 99.701
+    - type: recall_at_20
+      value: 95.148
+    - type: recall_at_3
+      value: 76.224
+    - type: recall_at_5
+      value: 83.872
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
+    metrics:
+    - type: map_at_1
+      value: 71.856
+    - type: map_at_10
+      value: 86.077
+    - type: map_at_100
+      value: 86.696
+    - type: map_at_1000
+      value: 86.708
+    - type: map_at_20
+      value: 86.493
+    - type: map_at_3
+      value: 83.176
+    - type: map_at_5
+      value: 85.008
+    - type: mrr_at_1
+      value: 82.74000000000001
+    - type: mrr_at_10
+      value: 88.68947222222207
+    - type: mrr_at_100
+      value: 88.78196949571182
+    - type: mrr_at_1000
+      value: 88.78223256200576
+    - type: mrr_at_20
+      value: 88.76455636228219
+    - type: mrr_at_3
+      value: 87.85833333333316
+    - type: mrr_at_5
+      value: 88.43933333333311
+    - type: ndcg_at_1
+      value: 82.74000000000001
+    - type: ndcg_at_10
+      value: 89.583
+    - type: ndcg_at_100
+      value: 90.652
+    - type: ndcg_at_1000
+      value: 90.711
+    - type: ndcg_at_20
+      value: 90.203
+    - type: ndcg_at_3
+      value: 86.967
+    - type: ndcg_at_5
+      value: 88.43299999999999
+    - type: precision_at_1
+      value: 82.74000000000001
+    - type: precision_at_10
+      value: 13.617
+    - type: precision_at_100
+      value: 1.542
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_20
+      value: 7.217999999999999
+    - type: precision_at_3
+      value: 38.163000000000004
+    - type: precision_at_5
+      value: 25.05
+    - type: recall_at_1
+      value: 71.856
+    - type: recall_at_10
+      value: 96.244
+    - type: recall_at_100
+      value: 99.773
+    - type: recall_at_1000
+      value: 99.99900000000001
+    - type: recall_at_20
+      value: 98.221
+    - type: recall_at_3
+      value: 88.715
+    - type: recall_at_5
+      value: 92.88499999999999
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 62.91969510127886
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
+    metrics:
+    - type: v_measure
+      value: 72.74201090913765
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
+    metrics:
+    - type: map_at_1
+      value: 5.8229999999999995
+    - type: map_at_10
+      value: 15.152
+    - type: map_at_100
+      value: 17.936
+    - type: map_at_1000
+      value: 18.292
+    - type: map_at_20
+      value: 16.526
+    - type: map_at_3
+      value: 10.294
+    - type: map_at_5
+      value: 12.794
+    - type: mrr_at_1
+      value: 28.599999999999998
+    - type: mrr_at_10
+      value: 40.68206349206347
+    - type: mrr_at_100
+      value: 41.673752995361795
+    - type: mrr_at_1000
+      value: 41.71500072915374
+    - type: mrr_at_20
+      value: 41.28552805166964
+    - type: mrr_at_3
+      value: 36.84999999999998
+    - type: mrr_at_5
+      value: 39.19999999999995
+    - type: ndcg_at_1
+      value: 28.599999999999998
+    - type: ndcg_at_10
+      value: 24.866
+    - type: ndcg_at_100
+      value: 34.597
+    - type: ndcg_at_1000
+      value: 39.994
+    - type: ndcg_at_20
+      value: 28.309
+    - type: ndcg_at_3
+      value: 22.749
+    - type: ndcg_at_5
+      value: 20.502000000000002
+    - type: precision_at_1
+      value: 28.599999999999998
+    - type: precision_at_10
+      value: 13.089999999999998
+    - type: precision_at_100
+      value: 2.7119999999999997
+    - type: precision_at_1000
+      value: 0.39899999999999997
+    - type: precision_at_20
+      value: 8.53
+    - type: precision_at_3
+      value: 21.099999999999998
+    - type: precision_at_5
+      value: 18.22
+    - type: recall_at_1
+      value: 5.8229999999999995
+    - type: recall_at_10
+      value: 26.522000000000002
+    - type: recall_at_100
+      value: 55.003
+    - type: recall_at_1000
+      value: 80.977
+    - type: recall_at_20
+      value: 34.618
+    - type: recall_at_3
+      value: 12.848
+    - type: recall_at_5
+      value: 18.477
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.72562067620224
+    - type: cos_sim_spearman
+      value: 77.00710192931953
+    - type: euclidean_pearson
+      value: 78.65843289108192
+    - type: euclidean_spearman
+      value: 77.00710077709005
+    - type: manhattan_pearson
+      value: 78.48859522905846
+    - type: manhattan_spearman
+      value: 76.8213740840866
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.15015325911659
+    - type: cos_sim_spearman
+      value: 75.67268325741222
+    - type: euclidean_pearson
+      value: 75.54004763633206
+    - type: euclidean_spearman
+      value: 75.67262179635058
+    - type: manhattan_pearson
+      value: 75.80681616893116
+    - type: manhattan_spearman
+      value: 75.93721016401406
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.71651874476737
+    - type: cos_sim_spearman
+      value: 82.39667472464997
+    - type: euclidean_pearson
+      value: 82.28256504757712
+    - type: euclidean_spearman
+      value: 82.39663674872656
+    - type: manhattan_pearson
+      value: 82.3192873176068
+    - type: manhattan_spearman
+      value: 82.41915252757059
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.222967367593
+    - type: cos_sim_spearman
+      value: 79.92685877403252
+    - type: euclidean_pearson
+      value: 79.95053542861498
+    - type: euclidean_spearman
+      value: 79.9268858850991
+    - type: manhattan_pearson
+      value: 79.90485851323321
+    - type: manhattan_spearman
+      value: 79.93878025669312
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.27539130156643
+    - type: cos_sim_spearman
+      value: 85.81645767911826
+    - type: euclidean_pearson
+      value: 85.5488615685444
+    - type: euclidean_spearman
+      value: 85.81647022566916
+    - type: manhattan_pearson
+      value: 85.6358149547879
+    - type: manhattan_spearman
+      value: 85.96347118567043
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.43727336154858
+    - type: cos_sim_spearman
+      value: 84.50468882202796
+    - type: euclidean_pearson
+      value: 83.23576727105372
+    - type: euclidean_spearman
+      value: 84.50468882202796
+    - type: manhattan_pearson
+      value: 83.28843314503176
+    - type: manhattan_spearman
+      value: 84.60383766214322
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
+      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.86589365166874
+    - type: cos_sim_spearman
+      value: 88.93117996163835
+    - type: euclidean_pearson
+      value: 89.12271565981082
+    - type: euclidean_spearman
+      value: 88.93117996163835
+    - type: manhattan_pearson
+      value: 88.94419759325545
+    - type: manhattan_spearman
+      value: 88.63073561731899
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 67.96578378422929
+    - type: cos_sim_spearman
+      value: 67.10257461424345
+    - type: euclidean_pearson
+      value: 67.51317866195149
+    - type: euclidean_spearman
+      value: 67.10257461424345
+    - type: manhattan_pearson
+      value: 67.74940912013754
+    - type: manhattan_spearman
+      value: 67.46694183937207
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.55433725920493
+    - type: cos_sim_spearman
+      value: 83.60373857254014
+    - type: euclidean_pearson
+      value: 83.08086082334839
+    - type: euclidean_spearman
+      value: 83.6036864776559
+    - type: manhattan_pearson
+      value: 83.2232267589246
+    - type: manhattan_spearman
+      value: 83.78923946962664
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 87.28566757174322
+    - type: mrr
+      value: 96.63827639317836
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: 0228b52cf27578f30900b9e5271d331663a030d7
+    metrics:
+    - type: map_at_1
+      value: 70.661
+    - type: map_at_10
+      value: 82.051
+    - type: map_at_100
+      value: 82.162
+    - type: map_at_1000
+      value: 82.167
+    - type: map_at_20
+      value: 82.122
+    - type: map_at_3
+      value: 79.919
+    - type: map_at_5
+      value: 81.368
+    - type: mrr_at_1
+      value: 74.33333333333333
+    - type: mrr_at_10
+      value: 82.98452380952381
+    - type: mrr_at_100
+      value: 83.09512420633841
+    - type: mrr_at_1000
+      value: 83.10026279387446
+    - type: mrr_at_20
+      value: 83.05460927960928
+    - type: mrr_at_3
+      value: 81.8888888888889
+    - type: mrr_at_5
+      value: 82.65555555555557
+    - type: ndcg_at_1
+      value: 74.333
+    - type: ndcg_at_10
+      value: 85.914
+    - type: ndcg_at_100
+      value: 86.473
+    - type: ndcg_at_1000
+      value: 86.602
+    - type: ndcg_at_20
+      value: 86.169
+    - type: ndcg_at_3
+      value: 83.047
+    - type: ndcg_at_5
+      value: 84.72
+    - type: precision_at_1
+      value: 74.333
+    - type: precision_at_10
+      value: 10.933
+    - type: precision_at_100
+      value: 1.1199999999999999
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_20
+      value: 5.5169999999999995
+    - type: precision_at_3
+      value: 32.444
+    - type: precision_at_5
+      value: 20.8
+    - type: recall_at_1
+      value: 70.661
+    - type: recall_at_10
+      value: 96.333
+    - type: recall_at_100
+      value: 99.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_20
+      value: 97.333
+    - type: recall_at_3
+      value: 88.64999999999999
+    - type: recall_at_5
+      value: 93.089
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.89108910891089
+    - type: cos_sim_ap
+      value: 97.61815451002174
+    - type: cos_sim_f1
+      value: 94.51097804391219
+    - type: cos_sim_precision
+      value: 94.32270916334662
+    - type: cos_sim_recall
+      value: 94.69999999999999
+    - type: dot_accuracy
+      value: 99.89108910891089
+    - type: dot_ap
+      value: 97.61815451002175
+    - type: dot_f1
+      value: 94.51097804391219
+    - type: dot_precision
+      value: 94.32270916334662
+    - type: dot_recall
+      value: 94.69999999999999
+    - type: euclidean_accuracy
+      value: 99.89108910891089
+    - type: euclidean_ap
+      value: 97.61815534251431
+    - type: euclidean_f1
+      value: 94.51097804391219
+    - type: euclidean_precision
+      value: 94.32270916334662
+    - type: euclidean_recall
+      value: 94.69999999999999
+    - type: manhattan_accuracy
+      value: 99.8940594059406
+    - type: manhattan_ap
+      value: 97.66124472227202
+    - type: manhattan_f1
+      value: 94.65267366316841
+    - type: manhattan_precision
+      value: 94.60539460539461
+    - type: manhattan_recall
+      value: 94.69999999999999
+    - type: max_accuracy
+      value: 99.8940594059406
+    - type: max_ap
+      value: 97.66124472227202
+    - type: max_f1
+      value: 94.65267366316841
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 76.482776391195
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 48.29023235124473
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 55.3190739691685
+    - type: mrr
+      value: 56.40441972243442
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.98570594378664
+    - type: cos_sim_spearman
+      value: 30.712965330802174
+    - type: dot_pearson
+      value: 31.98570540209124
+    - type: dot_spearman
+      value: 30.712965330802174
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
+    metrics:
+    - type: map_at_1
+      value: 0.25
+    - type: map_at_10
+      value: 2.2640000000000002
+    - type: map_at_100
+      value: 14.447
+    - type: map_at_1000
+      value: 35.452
+    - type: map_at_20
+      value: 4.163
+    - type: map_at_3
+      value: 0.715
+    - type: map_at_5
+      value: 1.1780000000000002
+    - type: mrr_at_1
+      value: 94.0
+    - type: mrr_at_10
+      value: 96.66666666666667
+    - type: mrr_at_100
+      value: 96.66666666666667
+    - type: mrr_at_1000
+      value: 96.66666666666667
+    - type: mrr_at_20
+      value: 96.66666666666667
+    - type: mrr_at_3
+      value: 96.66666666666667
+    - type: mrr_at_5
+      value: 96.66666666666667
+    - type: ndcg_at_1
+      value: 92.0
+    - type: ndcg_at_10
+      value: 87.26899999999999
+    - type: ndcg_at_100
+      value: 68.586
+    - type: ndcg_at_1000
+      value: 61.056999999999995
+    - type: ndcg_at_20
+      value: 83.452
+    - type: ndcg_at_3
+      value: 90.11200000000001
+    - type: ndcg_at_5
+      value: 89.103
+    - type: precision_at_1
+      value: 94.0
+    - type: precision_at_10
+      value: 91.2
+    - type: precision_at_100
+      value: 70.12
+    - type: precision_at_1000
+      value: 26.773999999999997
+    - type: precision_at_20
+      value: 87.3
+    - type: precision_at_3
+      value: 92.667
+    - type: precision_at_5
+      value: 92.4
+    - type: recall_at_1
+      value: 0.25
+    - type: recall_at_10
+      value: 2.3970000000000002
+    - type: recall_at_100
+      value: 17.233999999999998
+    - type: recall_at_1000
+      value: 57.879000000000005
+    - type: recall_at_20
+      value: 4.508
+    - type: recall_at_3
+      value: 0.734
+    - type: recall_at_5
+      value: 1.2269999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
+    metrics:
+    - type: map_at_1
+      value: 2.806
+    - type: map_at_10
+      value: 11.369
+    - type: map_at_100
+      value: 17.791
+    - type: map_at_1000
+      value: 19.363
+    - type: map_at_20
+      value: 14.038999999999998
+    - type: map_at_3
+      value: 5.817
+    - type: map_at_5
+      value: 8.331
+    - type: mrr_at_1
+      value: 36.734693877551024
+    - type: mrr_at_10
+      value: 53.355199222546155
+    - type: mrr_at_100
+      value: 53.648197984932665
+    - type: mrr_at_1000
+      value: 53.648197984932665
+    - type: mrr_at_20
+      value: 53.500971817298336
+    - type: mrr_at_3
+      value: 48.63945578231292
+    - type: mrr_at_5
+      value: 51.29251700680272
+    - type: ndcg_at_1
+      value: 35.714
+    - type: ndcg_at_10
+      value: 28.18
+    - type: ndcg_at_100
+      value: 39.22
+    - type: ndcg_at_1000
+      value: 50.807
+    - type: ndcg_at_20
+      value: 28.979
+    - type: ndcg_at_3
+      value: 31.114000000000004
+    - type: ndcg_at_5
+      value: 29.687
+    - type: precision_at_1
+      value: 36.735
+    - type: precision_at_10
+      value: 24.898
+    - type: precision_at_100
+      value: 7.918
+    - type: precision_at_1000
+      value: 1.5779999999999998
+    - type: precision_at_20
+      value: 18.878
+    - type: precision_at_3
+      value: 31.293
+    - type: precision_at_5
+      value: 29.387999999999998
+    - type: recall_at_1
+      value: 2.806
+    - type: recall_at_10
+      value: 17.776
+    - type: recall_at_100
+      value: 49.41
+    - type: recall_at_1000
+      value: 84.97200000000001
+    - type: recall_at_20
+      value: 26.589000000000002
+    - type: recall_at_3
+      value: 6.866999999999999
+    - type: recall_at_5
+      value: 10.964
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
+    metrics:
+    - type: accuracy
+      value: 91.1376953125
+    - type: ap
+      value: 40.51219896084815
+    - type: f1
+      value: 77.5195445434559
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 79.69722693831352
+    - type: f1
+      value: 80.02969178591319
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 66.42427742893598
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 87.81069321094355
+    - type: cos_sim_ap
+      value: 78.57014017906349
+    - type: cos_sim_f1
+      value: 72.38883143743536
+    - type: cos_sim_precision
+      value: 70.95793208312215
+    - type: cos_sim_recall
+      value: 73.87862796833772
+    - type: dot_accuracy
+      value: 87.81069321094355
+    - type: dot_ap
+      value: 78.5701399541226
+    - type: dot_f1
+      value: 72.38883143743536
+    - type: dot_precision
+      value: 70.95793208312215
+    - type: dot_recall
+      value: 73.87862796833772
+    - type: euclidean_accuracy
+      value: 87.81069321094355
+    - type: euclidean_ap
+      value: 78.57015336777854
+    - type: euclidean_f1
+      value: 72.38883143743536
+    - type: euclidean_precision
+      value: 70.95793208312215
+    - type: euclidean_recall
+      value: 73.87862796833772
+    - type: manhattan_accuracy
+      value: 87.57227156225785
+    - type: manhattan_ap
+      value: 78.19109731614216
+    - type: manhattan_f1
+      value: 71.87819856704198
+    - type: manhattan_precision
+      value: 69.77148534525584
+    - type: manhattan_recall
+      value: 74.1160949868074
+    - type: max_accuracy
+      value: 87.81069321094355
+    - type: max_ap
+      value: 78.57015336777854
+    - type: max_f1
+      value: 72.38883143743536
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.95032405790352
+    - type: cos_sim_ap
+      value: 88.03104739249996
+    - type: cos_sim_f1
+      value: 80.34377190070451
+    - type: cos_sim_precision
+      value: 77.11534376548892
+    - type: cos_sim_recall
+      value: 83.85432707114259
+    - type: dot_accuracy
+      value: 89.95032405790352
+    - type: dot_ap
+      value: 88.03105328515932
+    - type: dot_f1
+      value: 80.34377190070451
+    - type: dot_precision
+      value: 77.11534376548892
+    - type: dot_recall
+      value: 83.85432707114259
+    - type: euclidean_accuracy
+      value: 89.95032405790352
+    - type: euclidean_ap
+      value: 88.03105084564575
+    - type: euclidean_f1
+      value: 80.34377190070451
+    - type: euclidean_precision
+      value: 77.11534376548892
+    - type: euclidean_recall
+      value: 83.85432707114259
+    - type: manhattan_accuracy
+      value: 89.88046726433035
+    - type: manhattan_ap
+      value: 88.01484191858279
+    - type: manhattan_f1
+      value: 80.34005593993817
+    - type: manhattan_precision
+      value: 76.95290468133108
+    - type: manhattan_recall
+      value: 84.03911302740991
+    - type: max_accuracy
+      value: 89.95032405790352
+    - type: max_ap
+      value: 88.03105328515932
+    - type: max_f1
+      value: 80.34377190070451
+language:
+- en
+license: cc-by-nc-4.0
+---
+# Salesforce/SFR-Embedding-2_R (Quantized)
+
+## Description
+This model is a quantized version of the original model [`Salesforce/SFR-Embedding-2_R`](https://huggingface.co/Salesforce/SFR-Embedding-2_R). 
+
+It's quantized using the BitsAndBytes library to 4-bit using the [bnb-my-repo](https://huggingface.co/spaces/bnb-community/bnb-my-repo) space.
+
+## Quantization Details
+- **Quantization Type**: int4
+- **bnb_4bit_quant_type**: nf4
+- **bnb_4bit_use_double_quant**: True
+- **bnb_4bit_compute_dtype**: bfloat16
+- **bnb_4bit_quant_storage**: uint8
+
+
+
+# 📄 Original Model Information
+
+
+
+<h1 align="center">Salesforce/SFR-Embedding-2_R</h1>
+
+**SFR-Embedding by Salesforce Research.**
+
+The model is for **research purposes only**.
+
+More technical details will be updated later. Meanwhile, please refer to our previous work [SFR-Embedding](https://www.salesforce.com/blog/sfr-embedding/) for details.
+
+### Ethical Considerations
+This release is for research purposes only in support of an academic paper. Our models, datasets, and code are not specifically designed or evaluated for all downstream purposes. We strongly recommend users evaluate and address potential concerns related to accuracy, safety, and fairness before deploying this model. We encourage users to consider the common limitations of AI, comply with applicable laws, and leverage best practices when selecting use cases, particularly for high-risk scenarios where errors or misuse could significantly impact people’s lives, rights, or safety. For further guidance on use cases, refer to our [AUP](https://www.salesforce.com/content/dam/web/en_us/www/documents/legal/Agreements/policies/ExternalFacing_Services_Policy.pdf) and [AI AUP](https://www.salesforce.com/content/dam/web/en_us/www/documents/legal/Agreements/policies/ai-acceptable-use-policy.pdf).
+
+
+SFR-Embedding Team (∗indicates equal contributors, † indicates co-leaders).
+* Rui Meng*
+* Ye Liu*
+* Tong Niu
+* Shafiq Rayhan Joty
+* Caiming Xiong †
+* Yingbo Zhou †
+* Semih Yavuz †
+
+### Citation
+```bibtex
+@misc{SFR-embedding-2,
+  title={SFR-Embedding-2: Advanced Text Embedding with Multi-stage Training},
+  author={Rui Meng*, Ye Liu*, Shafiq Rayhan Joty, Caiming Xiong, Yingbo Zhou, Semih Yavuz},
+  year={2024},
+  url={https://huggingface.co/Salesforce/SFR-Embedding-2_R}
+}
+```
+
+
+## How to run
+
+#### Transformers
+The models can be used as follows:
+```python
+import torch
+import torch.nn.functional as F
+from torch import Tensor
+from transformers import AutoTokenizer, AutoModel
+
+def last_token_pool(last_hidden_states: Tensor,
+                 attention_mask: Tensor) -> Tensor:
+    left_padding = (attention_mask[:, -1].sum() == attention_mask.shape[0])
+    if left_padding:
+        return last_hidden_states[:, -1]
+    else:
+        sequence_lengths = attention_mask.sum(dim=1) - 1
+        batch_size = last_hidden_states.shape[0]
+        return last_hidden_states[torch.arange(batch_size, device=last_hidden_states.device), sequence_lengths]
+
+def get_detailed_instruct(task_description: str, query: str) -> str:
+    return f'Instruct: {task_description}\nQuery: {query}'
+
+# Each query must come with a one-sentence instruction that describes the task
+task = 'Given a web search query, retrieve relevant passages that answer the query'
+queries = [
+    get_detailed_instruct(task, 'How to bake a chocolate cake'),
+    get_detailed_instruct(task, 'Symptoms of the flu')
+]
+# No need to add instruction for retrieval documents
+passages = [
+    "To bake a delicious chocolate cake, you'll need the following ingredients: all-purpose flour, sugar, cocoa powder, baking powder, baking soda, salt, eggs, milk, vegetable oil, and vanilla extract. Start by preheating your oven to 350°F (175°C). In a mixing bowl, combine the dry ingredients (flour, sugar, cocoa powder, baking powder, baking soda, and salt). In a separate bowl, whisk together the wet ingredients (eggs, milk, vegetable oil, and vanilla extract). Gradually add the wet mixture to the dry ingredients, stirring until well combined. Pour the batter into a greased cake pan and bake for 30-35 minutes. Let it cool before frosting with your favorite chocolate frosting. Enjoy your homemade chocolate cake!",
+    "The flu, or influenza, is an illness caused by influenza viruses. Common symptoms of the flu include a high fever, chills, cough, sore throat, runny or stuffy nose, body aches, headache, fatigue, and sometimes nausea and vomiting. These symptoms can come on suddenly and are usually more severe than the common cold. It's important to get plenty of rest, stay hydrated, and consult a healthcare professional if you suspect you have the flu. In some cases, antiviral medications can help alleviate symptoms and reduce the duration of the illness."
+]
+
+# load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained('Salesforce/SFR-Embedding-2_R')
+model = AutoModel.from_pretrained('Salesforce/SFR-Embedding-2_R')
+
+# get the embeddings
+max_length = 4096
+input_texts = queries + passages
+batch_dict = tokenizer(input_texts, max_length=max_length, padding=True, truncation=True, return_tensors="pt")
+outputs = model(**batch_dict)
+embeddings = last_token_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())
+# [[40.132083892822266, 25.032529830932617], [15.006855010986328, 39.93733215332031]]
+```
+
+### Sentence Transformers
+```python
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer("Salesforce/SFR-Embedding-2_R")
+
+def get_detailed_instruct(task_description: str, query: str) -> str:
+    return f'Instruct: {task_description}\nQuery: {query}'
+
+# Each query must come with a one-sentence instruction that describes the task
+task = 'Given a web search query, retrieve relevant passages that answer the query'
+queries = [
+    get_detailed_instruct(task, 'How to bake a chocolate cake'),
+    get_detailed_instruct(task, 'Symptoms of the flu')
+]
+# No need to add instruction for retrieval documents
+passages = [
+    "To bake a delicious chocolate cake, you'll need the following ingredients: all-purpose flour, sugar, cocoa powder, baking powder, baking soda, salt, eggs, milk, vegetable oil, and vanilla extract. Start by preheating your oven to 350°F (175°C). In a mixing bowl, combine the dry ingredients (flour, sugar, cocoa powder, baking powder, baking soda, and salt). In a separate bowl, whisk together the wet ingredients (eggs, milk, vegetable oil, and vanilla extract). Gradually add the wet mixture to the dry ingredients, stirring until well combined. Pour the batter into a greased cake pan and bake for 30-35 minutes. Let it cool before frosting with your favorite chocolate frosting. Enjoy your homemade chocolate cake!",
+    "The flu, or influenza, is an illness caused by influenza viruses. Common symptoms of the flu include a high fever, chills, cough, sore throat, runny or stuffy nose, body aches, headache, fatigue, and sometimes nausea and vomiting. These symptoms can come on suddenly and are usually more severe than the common cold. It's important to get plenty of rest, stay hydrated, and consult a healthcare professional if you suspect you have the flu. In some cases, antiviral medications can help alleviate symptoms and reduce the duration of the illness."
+]
+
+embeddings = model.encode(queries + passages)
+scores = model.similarity(embeddings[:2], embeddings[2:]) * 100
+print(scores.tolist())
+# [[40.13203811645508, 25.032546997070312], [15.00684642791748, 39.937339782714844]]
+```
+
+
+
+
+

config.json

@@ -0,0 +1,43 @@
+{
+  "_name_or_path": "Salesforce/SFR-Embedding-2_R",
+  "architectures": [
+    "MistralModel"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": 2,
+  "quantization_config": {
+    "_load_in_4bit": true,
+    "_load_in_8bit": false,
+    "bnb_4bit_compute_dtype": "bfloat16",
+    "bnb_4bit_quant_storage": "uint8",
+    "bnb_4bit_quant_type": "nf4",
+    "bnb_4bit_use_double_quant": true,
+    "llm_int8_enable_fp32_cpu_offload": false,
+    "llm_int8_has_fp16_weight": false,
+    "llm_int8_skip_modules": null,
+    "llm_int8_threshold": 6.0,
+    "load_in_4bit": true,
+    "load_in_8bit": false,
+    "quant_method": "bitsandbytes"
+  },
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.49.0",
+  "use_cache": false,
+  "vocab_size": 32000
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d39efefc6adbd5adc86cbd9f1c7ed3f2fbcd67420b93de65ca2a55be0d9fe957
+size 4126214972

special_tokens_map.json

@@ -0,0 +1,35 @@
+{
+  "additional_special_tokens": [
+    "<unk>",
+    "<s>",
+    "</s>"
+  ],
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,55 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": true,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<unk>",
+    "<s>",
+    "</s>"
+  ],
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "extra_special_tokens": {},
+  "legacy": true,
+  "max_length": 512,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_to_multiple_of": null,
+  "pad_token": "</s>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "stride": 0,
+  "tokenizer_class": "LlamaTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}