Update README.md

README.md

@@ -1,3 +1,3316 @@
----
-license: apache-2.0
----
+---
+tags:
+- mteb
+- sentence-transformers
+- transformers
+- Qwen2
+- sentence-similarity
+license: apache-2.0
+model-index:
+- name: gte-qwen2-7B-instruct
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 88.01492537313432
+    - type: ap
+      value: 59.096217055359276
+    - type: f1
+      value: 83.2699173062069
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 97.29805
+    - type: ap
+      value: 95.97973142381882
+    - type: f1
+      value: 97.29773206176378
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 62.798
+    - type: f1
+      value: 61.33195375425034
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
+    metrics:
+    - type: map_at_1
+      value: 36.629
+    - type: map_at_10
+      value: 54.982
+    - type: map_at_100
+      value: 55.355
+    - type: map_at_1000
+      value: 55.355
+    - type: map_at_3
+      value: 50.036
+    - type: map_at_5
+      value: 53.25
+    - type: mrr_at_1
+      value: 37.624
+    - type: mrr_at_10
+      value: 55.376000000000005
+    - type: mrr_at_100
+      value: 55.749
+    - type: mrr_at_1000
+      value: 55.749
+    - type: mrr_at_3
+      value: 50.461999999999996
+    - type: mrr_at_5
+      value: 53.644999999999996
+    - type: ndcg_at_1
+      value: 36.629
+    - type: ndcg_at_10
+      value: 64.35499999999999
+    - type: ndcg_at_100
+      value: 65.778
+    - type: ndcg_at_1000
+      value: 65.778
+    - type: ndcg_at_3
+      value: 54.478
+    - type: ndcg_at_5
+      value: 60.260000000000005
+    - type: precision_at_1
+      value: 36.629
+    - type: precision_at_10
+      value: 9.381
+    - type: precision_at_100
+      value: 0.996
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 22.451
+    - type: precision_at_5
+      value: 16.273
+    - type: recall_at_1
+      value: 36.629
+    - type: recall_at_10
+      value: 93.812
+    - type: recall_at_100
+      value: 99.644
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 67.354
+    - type: recall_at_5
+      value: 81.366
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 56.30960182540703
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 51.858431775176975
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 67.5678414928039
+    - type: mrr
+      value: 79.56305236776153
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.32511136457549
+    - type: cos_sim_spearman
+      value: 79.34518142776068
+    - type: euclidean_pearson
+      value: 81.09762569927126
+    - type: euclidean_spearman
+      value: 79.33554265391781
+    - type: manhattan_pearson
+      value: 81.33942162521643
+    - type: manhattan_spearman
+      value: 79.91206181439438
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 85.99675324675324
+    - type: f1
+      value: 85.5564660877528
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 50.413005916654384
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 46.58170679922341
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: f46a197baaae43b4f621051089b82a364682dfeb
+    metrics:
+    - type: map_at_1
+      value: 34.588
+    - type: map_at_10
+      value: 47.851
+    - type: map_at_100
+      value: 49.484
+    - type: map_at_1000
+      value: 49.6
+    - type: map_at_3
+      value: 43.34
+    - type: map_at_5
+      value: 45.734
+    - type: mrr_at_1
+      value: 42.203
+    - type: mrr_at_10
+      value: 53.315999999999995
+    - type: mrr_at_100
+      value: 53.977
+    - type: mrr_at_1000
+      value: 54.001
+    - type: mrr_at_3
+      value: 50.381
+    - type: mrr_at_5
+      value: 52.198
+    - type: ndcg_at_1
+      value: 42.203
+    - type: ndcg_at_10
+      value: 55.143
+    - type: ndcg_at_100
+      value: 60.278
+    - type: ndcg_at_1000
+      value: 61.497
+    - type: ndcg_at_3
+      value: 48.9
+    - type: ndcg_at_5
+      value: 51.712
+    - type: precision_at_1
+      value: 42.203
+    - type: precision_at_10
+      value: 11.016
+    - type: precision_at_100
+      value: 1.718
+    - type: precision_at_1000
+      value: 0.219
+    - type: precision_at_3
+      value: 24.224999999999998
+    - type: precision_at_5
+      value: 17.711
+    - type: recall_at_1
+      value: 34.588
+    - type: recall_at_10
+      value: 69.91000000000001
+    - type: recall_at_100
+      value: 91.01700000000001
+    - type: recall_at_1000
+      value: 98.02199999999999
+    - type: recall_at_3
+      value: 51.9
+    - type: recall_at_5
+      value: 59.604
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
+    metrics:
+    - type: map_at_1
+      value: 35.649
+    - type: map_at_10
+      value: 47.713
+    - type: map_at_100
+      value: 49.043
+    - type: map_at_1000
+      value: 49.178
+    - type: map_at_3
+      value: 44.355
+    - type: map_at_5
+      value: 46.152
+    - type: mrr_at_1
+      value: 44.268
+    - type: mrr_at_10
+      value: 53.403999999999996
+    - type: mrr_at_100
+      value: 54.035999999999994
+    - type: mrr_at_1000
+      value: 54.078
+    - type: mrr_at_3
+      value: 51.507000000000005
+    - type: mrr_at_5
+      value: 52.583999999999996
+    - type: ndcg_at_1
+      value: 44.268
+    - type: ndcg_at_10
+      value: 53.679
+    - type: ndcg_at_100
+      value: 57.794000000000004
+    - type: ndcg_at_1000
+      value: 59.74
+    - type: ndcg_at_3
+      value: 49.348
+    - type: ndcg_at_5
+      value: 51.266999999999996
+    - type: precision_at_1
+      value: 44.268
+    - type: precision_at_10
+      value: 10.120999999999999
+    - type: precision_at_100
+      value: 1.566
+    - type: precision_at_1000
+      value: 0.20600000000000002
+    - type: precision_at_3
+      value: 23.864
+    - type: precision_at_5
+      value: 16.650000000000002
+    - type: recall_at_1
+      value: 35.649
+    - type: recall_at_10
+      value: 64.152
+    - type: recall_at_100
+      value: 81.096
+    - type: recall_at_1000
+      value: 92.957
+    - type: recall_at_3
+      value: 51.498
+    - type: recall_at_5
+      value: 56.977
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
+    metrics:
+    - type: map_at_1
+      value: 38.372
+    - type: map_at_10
+      value: 52.693
+    - type: map_at_100
+      value: 53.796
+    - type: map_at_1000
+      value: 53.836
+    - type: map_at_3
+      value: 48.818
+    - type: map_at_5
+      value: 51.052
+    - type: mrr_at_1
+      value: 44.013000000000005
+    - type: mrr_at_10
+      value: 55.769999999999996
+    - type: mrr_at_100
+      value: 56.415000000000006
+    - type: mrr_at_1000
+      value: 56.435
+    - type: mrr_at_3
+      value: 52.884
+    - type: mrr_at_5
+      value: 54.552
+    - type: ndcg_at_1
+      value: 44.013000000000005
+    - type: ndcg_at_10
+      value: 59.45
+    - type: ndcg_at_100
+      value: 63.422
+    - type: ndcg_at_1000
+      value: 64.214
+    - type: ndcg_at_3
+      value: 52.829
+    - type: ndcg_at_5
+      value: 56.079
+    - type: precision_at_1
+      value: 44.013000000000005
+    - type: precision_at_10
+      value: 9.912
+    - type: precision_at_100
+      value: 1.286
+    - type: precision_at_1000
+      value: 0.13899999999999998
+    - type: precision_at_3
+      value: 23.992
+    - type: precision_at_5
+      value: 16.803
+    - type: recall_at_1
+      value: 38.372
+    - type: recall_at_10
+      value: 76.279
+    - type: recall_at_100
+      value: 92.842
+    - type: recall_at_1000
+      value: 98.41
+    - type: recall_at_3
+      value: 58.738
+    - type: recall_at_5
+      value: 66.51899999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: 5003b3064772da1887988e05400cf3806fe491f2
+    metrics:
+    - type: map_at_1
+      value: 26.784999999999997
+    - type: map_at_10
+      value: 37.152
+    - type: map_at_100
+      value: 38.371
+    - type: map_at_1000
+      value: 38.437
+    - type: map_at_3
+      value: 34.211999999999996
+    - type: map_at_5
+      value: 35.791000000000004
+    - type: mrr_at_1
+      value: 29.153000000000002
+    - type: mrr_at_10
+      value: 39.312999999999995
+    - type: mrr_at_100
+      value: 40.32
+    - type: mrr_at_1000
+      value: 40.367999999999995
+    - type: mrr_at_3
+      value: 36.760999999999996
+    - type: mrr_at_5
+      value: 38.083
+    - type: ndcg_at_1
+      value: 29.153000000000002
+    - type: ndcg_at_10
+      value: 42.785000000000004
+    - type: ndcg_at_100
+      value: 48.613
+    - type: ndcg_at_1000
+      value: 50.166
+    - type: ndcg_at_3
+      value: 37.255
+    - type: ndcg_at_5
+      value: 39.763999999999996
+    - type: precision_at_1
+      value: 29.153000000000002
+    - type: precision_at_10
+      value: 6.734
+    - type: precision_at_100
+      value: 1.0250000000000001
+    - type: precision_at_1000
+      value: 0.11900000000000001
+    - type: precision_at_3
+      value: 16.234
+    - type: precision_at_5
+      value: 11.232000000000001
+    - type: recall_at_1
+      value: 26.784999999999997
+    - type: recall_at_10
+      value: 57.915000000000006
+    - type: recall_at_100
+      value: 84.473
+    - type: recall_at_1000
+      value: 96.011
+    - type: recall_at_3
+      value: 43.105
+    - type: recall_at_5
+      value: 49.15
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
+    metrics:
+    - type: map_at_1
+      value: 20.24
+    - type: map_at_10
+      value: 31.493
+    - type: map_at_100
+      value: 32.771
+    - type: map_at_1000
+      value: 32.883
+    - type: map_at_3
+      value: 27.062
+    - type: map_at_5
+      value: 29.421999999999997
+    - type: mrr_at_1
+      value: 25.622
+    - type: mrr_at_10
+      value: 35.729
+    - type: mrr_at_100
+      value: 36.613
+    - type: mrr_at_1000
+      value: 36.665
+    - type: mrr_at_3
+      value: 32.048
+    - type: mrr_at_5
+      value: 34.169
+    - type: ndcg_at_1
+      value: 25.622
+    - type: ndcg_at_10
+      value: 38.463
+    - type: ndcg_at_100
+      value: 43.909
+    - type: ndcg_at_1000
+      value: 46.21
+    - type: ndcg_at_3
+      value: 30.563000000000002
+    - type: ndcg_at_5
+      value: 34.178999999999995
+    - type: precision_at_1
+      value: 25.622
+    - type: precision_at_10
+      value: 7.7490000000000006
+    - type: precision_at_100
+      value: 1.1780000000000002
+    - type: precision_at_1000
+      value: 0.149
+    - type: precision_at_3
+      value: 15.049999999999999
+    - type: precision_at_5
+      value: 11.616999999999999
+    - type: recall_at_1
+      value: 20.24
+    - type: recall_at_10
+      value: 55.657000000000004
+    - type: recall_at_100
+      value: 78.803
+    - type: recall_at_1000
+      value: 94.801
+    - type: recall_at_3
+      value: 34.171
+    - type: recall_at_5
+      value: 43.16
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
+    metrics:
+    - type: map_at_1
+      value: 32.501000000000005
+    - type: map_at_10
+      value: 46.286
+    - type: map_at_100
+      value: 47.732
+    - type: map_at_1000
+      value: 47.814
+    - type: map_at_3
+      value: 41.957
+    - type: map_at_5
+      value: 44.506
+    - type: mrr_at_1
+      value: 39.75
+    - type: mrr_at_10
+      value: 51.285000000000004
+    - type: mrr_at_100
+      value: 52.051
+    - type: mrr_at_1000
+      value: 52.075
+    - type: mrr_at_3
+      value: 48.315999999999995
+    - type: mrr_at_5
+      value: 50.125
+    - type: ndcg_at_1
+      value: 39.75
+    - type: ndcg_at_10
+      value: 53.361999999999995
+    - type: ndcg_at_100
+      value: 58.703
+    - type: ndcg_at_1000
+      value: 59.962
+    - type: ndcg_at_3
+      value: 46.786
+    - type: ndcg_at_5
+      value: 50.169
+    - type: precision_at_1
+      value: 39.75
+    - type: precision_at_10
+      value: 10.154
+    - type: precision_at_100
+      value: 1.485
+    - type: precision_at_1000
+      value: 0.17600000000000002
+    - type: precision_at_3
+      value: 23.003
+    - type: precision_at_5
+      value: 16.766000000000002
+    - type: recall_at_1
+      value: 32.501000000000005
+    - type: recall_at_10
+      value: 68.901
+    - type: recall_at_100
+      value: 90.527
+    - type: recall_at_1000
+      value: 98.307
+    - type: recall_at_3
+      value: 51.056000000000004
+    - type: recall_at_5
+      value: 59.471
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
+    metrics:
+    - type: map_at_1
+      value: 27.962999999999997
+    - type: map_at_10
+      value: 41.434
+    - type: map_at_100
+      value: 42.961
+    - type: map_at_1000
+      value: 43.051
+    - type: map_at_3
+      value: 37.579
+    - type: map_at_5
+      value: 39.579
+    - type: mrr_at_1
+      value: 34.932
+    - type: mrr_at_10
+      value: 46.455999999999996
+    - type: mrr_at_100
+      value: 47.362
+    - type: mrr_at_1000
+      value: 47.398
+    - type: mrr_at_3
+      value: 43.855
+    - type: mrr_at_5
+      value: 45.322
+    - type: ndcg_at_1
+      value: 34.932
+    - type: ndcg_at_10
+      value: 48.323
+    - type: ndcg_at_100
+      value: 54.173
+    - type: ndcg_at_1000
+      value: 55.69
+    - type: ndcg_at_3
+      value: 42.498000000000005
+    - type: ndcg_at_5
+      value: 44.973
+    - type: precision_at_1
+      value: 34.932
+    - type: precision_at_10
+      value: 9.224
+    - type: precision_at_100
+      value: 1.429
+    - type: precision_at_1000
+      value: 0.172
+    - type: precision_at_3
+      value: 21.005
+    - type: precision_at_5
+      value: 15.0
+    - type: recall_at_1
+      value: 27.962999999999997
+    - type: recall_at_10
+      value: 63.563
+    - type: recall_at_100
+      value: 87.679
+    - type: recall_at_1000
+      value: 97.381
+    - type: recall_at_3
+      value: 47.205999999999996
+    - type: recall_at_5
+      value: 53.784
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+    metrics:
+    - type: map_at_1
+      value: 27.9895
+    - type: map_at_10
+      value: 39.67808333333333
+    - type: map_at_100
+      value: 41.05
+    - type: map_at_1000
+      value: 41.15800000000001
+    - type: map_at_3
+      value: 36.079499999999996
+    - type: map_at_5
+      value: 38.056749999999994
+    - type: mrr_at_1
+      value: 33.405583333333325
+    - type: mrr_at_10
+      value: 43.6965
+    - type: mrr_at_100
+      value: 44.568000000000005
+    - type: mrr_at_1000
+      value: 44.61208333333334
+    - type: mrr_at_3
+      value: 40.96574999999999
+    - type: mrr_at_5
+      value: 42.529833333333336
+    - type: ndcg_at_1
+      value: 33.405583333333325
+    - type: ndcg_at_10
+      value: 46.016
+    - type: ndcg_at_100
+      value: 51.39475
+    - type: ndcg_at_1000
+      value: 53.17333333333334
+    - type: ndcg_at_3
+      value: 40.166666666666664
+    - type: ndcg_at_5
+      value: 42.899750000000004
+    - type: precision_at_1
+      value: 33.405583333333325
+    - type: precision_at_10
+      value: 8.408999999999999
+    - type: precision_at_100
+      value: 1.3129166666666665
+    - type: precision_at_1000
+      value: 0.16583333333333336
+    - type: precision_at_3
+      value: 19.05825
+    - type: precision_at_5
+      value: 13.6845
+    - type: recall_at_1
+      value: 27.9895
+    - type: recall_at_10
+      value: 60.572416666666676
+    - type: recall_at_100
+      value: 83.63975
+    - type: recall_at_1000
+      value: 95.58775
+    - type: recall_at_3
+      value: 44.402750000000005
+    - type: recall_at_5
+      value: 51.40116666666666
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
+    metrics:
+    - type: map_at_1
+      value: 24.451
+    - type: map_at_10
+      value: 34.526
+    - type: map_at_100
+      value: 35.732
+    - type: map_at_1000
+      value: 35.824
+    - type: map_at_3
+      value: 31.503999999999998
+    - type: map_at_5
+      value: 33.241
+    - type: mrr_at_1
+      value: 28.221
+    - type: mrr_at_10
+      value: 37.34
+    - type: mrr_at_100
+      value: 38.389
+    - type: mrr_at_1000
+      value: 38.443
+    - type: mrr_at_3
+      value: 34.714
+    - type: mrr_at_5
+      value: 36.217
+    - type: ndcg_at_1
+      value: 28.221
+    - type: ndcg_at_10
+      value: 40.105000000000004
+    - type: ndcg_at_100
+      value: 45.619
+    - type: ndcg_at_1000
+      value: 47.597
+    - type: ndcg_at_3
+      value: 34.711
+    - type: ndcg_at_5
+      value: 37.38
+    - type: precision_at_1
+      value: 28.221
+    - type: precision_at_10
+      value: 6.7330000000000005
+    - type: precision_at_100
+      value: 1.0170000000000001
+    - type: precision_at_1000
+      value: 0.126
+    - type: precision_at_3
+      value: 15.798000000000002
+    - type: precision_at_5
+      value: 11.227
+    - type: recall_at_1
+      value: 24.451
+    - type: recall_at_10
+      value: 54.332
+    - type: recall_at_100
+      value: 78.842
+    - type: recall_at_1000
+      value: 92.868
+    - type: recall_at_3
+      value: 39.495999999999995
+    - type: recall_at_5
+      value: 46.198
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: 46989137a86843e03a6195de44b09deda022eec7
+    metrics:
+    - type: map_at_1
+      value: 18.989
+    - type: map_at_10
+      value: 28.189999999999998
+    - type: map_at_100
+      value: 29.575000000000003
+    - type: map_at_1000
+      value: 29.705
+    - type: map_at_3
+      value: 25.406000000000002
+    - type: map_at_5
+      value: 26.851000000000003
+    - type: mrr_at_1
+      value: 23.400000000000002
+    - type: mrr_at_10
+      value: 32.231
+    - type: mrr_at_100
+      value: 33.239000000000004
+    - type: mrr_at_1000
+      value: 33.309
+    - type: mrr_at_3
+      value: 29.869
+    - type: mrr_at_5
+      value: 31.102999999999998
+    - type: ndcg_at_1
+      value: 23.400000000000002
+    - type: ndcg_at_10
+      value: 33.634
+    - type: ndcg_at_100
+      value: 39.772999999999996
+    - type: ndcg_at_1000
+      value: 42.385
+    - type: ndcg_at_3
+      value: 28.938999999999997
+    - type: ndcg_at_5
+      value: 30.913
+    - type: precision_at_1
+      value: 23.400000000000002
+    - type: precision_at_10
+      value: 6.366
+    - type: precision_at_100
+      value: 1.1159999999999999
+    - type: precision_at_1000
+      value: 0.153
+    - type: precision_at_3
+      value: 14.212
+    - type: precision_at_5
+      value: 10.151
+    - type: recall_at_1
+      value: 18.989
+    - type: recall_at_10
+      value: 45.837
+    - type: recall_at_100
+      value: 73.04899999999999
+    - type: recall_at_1000
+      value: 91.245
+    - type: recall_at_3
+      value: 32.309
+    - type: recall_at_5
+      value: 37.665
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
+    metrics:
+    - type: map_at_1
+      value: 30.595
+    - type: map_at_10
+      value: 42.286
+    - type: map_at_100
+      value: 43.586999999999996
+    - type: map_at_1000
+      value: 43.669000000000004
+    - type: map_at_3
+      value: 38.888
+    - type: map_at_5
+      value: 40.669
+    - type: mrr_at_1
+      value: 36.287000000000006
+    - type: mrr_at_10
+      value: 46.405
+    - type: mrr_at_100
+      value: 47.282999999999994
+    - type: mrr_at_1000
+      value: 47.327000000000005
+    - type: mrr_at_3
+      value: 43.874
+    - type: mrr_at_5
+      value: 45.414
+    - type: ndcg_at_1
+      value: 36.287000000000006
+    - type: ndcg_at_10
+      value: 48.407
+    - type: ndcg_at_100
+      value: 53.824000000000005
+    - type: ndcg_at_1000
+      value: 55.483000000000004
+    - type: ndcg_at_3
+      value: 42.9
+    - type: ndcg_at_5
+      value: 45.391999999999996
+    - type: precision_at_1
+      value: 36.287000000000006
+    - type: precision_at_10
+      value: 8.414000000000001
+    - type: precision_at_100
+      value: 1.232
+    - type: precision_at_1000
+      value: 0.147
+    - type: precision_at_3
+      value: 20.118
+    - type: precision_at_5
+      value: 13.993
+    - type: recall_at_1
+      value: 30.595
+    - type: recall_at_10
+      value: 62.656
+    - type: recall_at_100
+      value: 85.74199999999999
+    - type: recall_at_1000
+      value: 96.854
+    - type: recall_at_3
+      value: 47.413
+    - type: recall_at_5
+      value: 54.04
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
+    metrics:
+    - type: map_at_1
+      value: 28.236
+    - type: map_at_10
+      value: 39.751
+    - type: map_at_100
+      value: 41.435
+    - type: map_at_1000
+      value: 41.677
+    - type: map_at_3
+      value: 35.957
+    - type: map_at_5
+      value: 38.112
+    - type: mrr_at_1
+      value: 33.794000000000004
+    - type: mrr_at_10
+      value: 44.449
+    - type: mrr_at_100
+      value: 45.268
+    - type: mrr_at_1000
+      value: 45.311
+    - type: mrr_at_3
+      value: 41.502
+    - type: mrr_at_5
+      value: 43.142
+    - type: ndcg_at_1
+      value: 33.794000000000004
+    - type: ndcg_at_10
+      value: 46.787
+    - type: ndcg_at_100
+      value: 52.290000000000006
+    - type: ndcg_at_1000
+      value: 54.336
+    - type: ndcg_at_3
+      value: 40.78
+    - type: ndcg_at_5
+      value: 43.669999999999995
+    - type: precision_at_1
+      value: 33.794000000000004
+    - type: precision_at_10
+      value: 9.051
+    - type: precision_at_100
+      value: 1.7919999999999998
+    - type: precision_at_1000
+      value: 0.259
+    - type: precision_at_3
+      value: 19.368
+    - type: precision_at_5
+      value: 14.229
+    - type: recall_at_1
+      value: 28.236
+    - type: recall_at_10
+      value: 61.358000000000004
+    - type: recall_at_100
+      value: 85.028
+    - type: recall_at_1000
+      value: 97.813
+    - type: recall_at_3
+      value: 44.207
+    - type: recall_at_5
+      value: 51.885000000000005
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+    metrics:
+    - type: map_at_1
+      value: 17.505000000000003
+    - type: map_at_10
+      value: 26.762000000000004
+    - type: map_at_100
+      value: 28.113
+    - type: map_at_1000
+      value: 28.222
+    - type: map_at_3
+      value: 23.876
+    - type: map_at_5
+      value: 25.572
+    - type: mrr_at_1
+      value: 19.224
+    - type: mrr_at_10
+      value: 28.660000000000004
+    - type: mrr_at_100
+      value: 29.863
+    - type: mrr_at_1000
+      value: 29.935000000000002
+    - type: mrr_at_3
+      value: 25.878
+    - type: mrr_at_5
+      value: 27.449
+    - type: ndcg_at_1
+      value: 19.224
+    - type: ndcg_at_10
+      value: 32.054
+    - type: ndcg_at_100
+      value: 38.339
+    - type: ndcg_at_1000
+      value: 40.8
+    - type: ndcg_at_3
+      value: 26.491
+    - type: ndcg_at_5
+      value: 29.298999999999996
+    - type: precision_at_1
+      value: 19.224
+    - type: precision_at_10
+      value: 5.434
+    - type: precision_at_100
+      value: 0.911
+    - type: precision_at_1000
+      value: 0.125
+    - type: precision_at_3
+      value: 11.83
+    - type: precision_at_5
+      value: 8.834999999999999
+    - type: recall_at_1
+      value: 17.505000000000003
+    - type: recall_at_10
+      value: 46.309
+    - type: recall_at_100
+      value: 74.579
+    - type: recall_at_1000
+      value: 92.384
+    - type: recall_at_3
+      value: 31.734
+    - type: recall_at_5
+      value: 38.361000000000004
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 67.085
+    - type: f1
+      value: 61.019909873305686
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
+    metrics:
+    - type: map_at_1
+      value: 32.251999999999995
+    - type: map_at_10
+      value: 53.98500000000001
+    - type: map_at_100
+      value: 56.093
+    - type: map_at_1000
+      value: 56.198
+    - type: map_at_3
+      value: 46.765
+    - type: map_at_5
+      value: 50.739999999999995
+    - type: mrr_at_1
+      value: 60.956999999999994
+    - type: mrr_at_10
+      value: 69.38600000000001
+    - type: mrr_at_100
+      value: 69.877
+    - type: mrr_at_1000
+      value: 69.884
+    - type: mrr_at_3
+      value: 67.052
+    - type: mrr_at_5
+      value: 68.356
+    - type: ndcg_at_1
+      value: 60.956999999999994
+    - type: ndcg_at_10
+      value: 62.78399999999999
+    - type: ndcg_at_100
+      value: 68.743
+    - type: ndcg_at_1000
+      value: 69.92399999999999
+    - type: ndcg_at_3
+      value: 57.336
+    - type: ndcg_at_5
+      value: 59.121
+    - type: precision_at_1
+      value: 60.956999999999994
+    - type: precision_at_10
+      value: 17.346
+    - type: precision_at_100
+      value: 2.3689999999999998
+    - type: precision_at_1000
+      value: 0.259
+    - type: precision_at_3
+      value: 37.912
+    - type: precision_at_5
+      value: 27.900999999999996
+    - type: recall_at_1
+      value: 32.251999999999995
+    - type: recall_at_10
+      value: 71.616
+    - type: recall_at_100
+      value: 92.685
+    - type: recall_at_1000
+      value: 98.983
+    - type: recall_at_3
+      value: 52.064
+    - type: recall_at_5
+      value: 60.49099999999999
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 96.4592
+    - type: ap
+      value: 94.57299077219179
+    - type: f1
+      value: 96.45842059801627
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 98.45873233014134
+    - type: f1
+      value: 98.38426074551533
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 90.01823985408116
+    - type: f1
+      value: 70.71419843084274
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 84.35104236718225
+    - type: f1
+      value: 82.50884520186432
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 88.0665770006725
+    - type: f1
+      value: 87.06928510969733
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 46.053400985420204
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 44.445957227318054
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 33.277065197675775
+    - type: mrr
+      value: 34.654704063060656
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
+    metrics:
+    - type: map_at_1
+      value: 6.728000000000001
+    - type: map_at_10
+      value: 15.052999999999999
+    - type: map_at_100
+      value: 19.901
+    - type: map_at_1000
+      value: 21.72
+    - type: map_at_3
+      value: 10.901
+    - type: map_at_5
+      value: 12.651000000000002
+    - type: mrr_at_1
+      value: 52.322
+    - type: mrr_at_10
+      value: 60.614999999999995
+    - type: mrr_at_100
+      value: 61.199000000000005
+    - type: mrr_at_1000
+      value: 61.227
+    - type: mrr_at_3
+      value: 58.977999999999994
+    - type: mrr_at_5
+      value: 59.907
+    - type: ndcg_at_1
+      value: 50.619
+    - type: ndcg_at_10
+      value: 40.278000000000006
+    - type: ndcg_at_100
+      value: 37.585
+    - type: ndcg_at_1000
+      value: 46.459
+    - type: ndcg_at_3
+      value: 46.143
+    - type: ndcg_at_5
+      value: 43.7
+    - type: precision_at_1
+      value: 52.012
+    - type: precision_at_10
+      value: 30.154999999999998
+    - type: precision_at_100
+      value: 9.87
+    - type: precision_at_1000
+      value: 2.343
+    - type: precision_at_3
+      value: 42.931000000000004
+    - type: precision_at_5
+      value: 37.771
+    - type: recall_at_1
+      value: 6.728000000000001
+    - type: recall_at_10
+      value: 19.372
+    - type: recall_at_100
+      value: 39.044000000000004
+    - type: recall_at_1000
+      value: 71.602
+    - type: recall_at_3
+      value: 12.328
+    - type: recall_at_5
+      value: 14.758
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 72.421
+    - type: map_at_10
+      value: 86.648
+    - type: map_at_100
+      value: 87.258
+    - type: map_at_1000
+      value: 87.26899999999999
+    - type: map_at_3
+      value: 83.82
+    - type: map_at_5
+      value: 85.629
+    - type: mrr_at_1
+      value: 83.21
+    - type: mrr_at_10
+      value: 89.198
+    - type: mrr_at_100
+      value: 89.277
+    - type: mrr_at_1000
+      value: 89.277
+    - type: mrr_at_3
+      value: 88.428
+    - type: mrr_at_5
+      value: 88.98
+    - type: ndcg_at_1
+      value: 83.24000000000001
+    - type: ndcg_at_10
+      value: 90.067
+    - type: ndcg_at_100
+      value: 91.091
+    - type: ndcg_at_1000
+      value: 91.146
+    - type: ndcg_at_3
+      value: 87.6
+    - type: ndcg_at_5
+      value: 89.004
+    - type: precision_at_1
+      value: 83.24000000000001
+    - type: precision_at_10
+      value: 13.644
+    - type: precision_at_100
+      value: 1.542
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 38.437
+    - type: precision_at_5
+      value: 25.194
+    - type: recall_at_1
+      value: 72.421
+    - type: recall_at_10
+      value: 96.49600000000001
+    - type: recall_at_100
+      value: 99.802
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 89.31400000000001
+    - type: recall_at_5
+      value: 93.363
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 73.97491289906442
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 73.49590001712183
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 6.978
+    - type: map_at_10
+      value: 18.307000000000002
+    - type: map_at_100
+      value: 21.605
+    - type: map_at_1000
+      value: 21.965
+    - type: map_at_3
+      value: 12.642000000000001
+    - type: map_at_5
+      value: 15.453
+    - type: mrr_at_1
+      value: 34.300000000000004
+    - type: mrr_at_10
+      value: 46.886
+    - type: mrr_at_100
+      value: 47.78
+    - type: mrr_at_1000
+      value: 47.795
+    - type: mrr_at_3
+      value: 42.467
+    - type: mrr_at_5
+      value: 45.427
+    - type: ndcg_at_1
+      value: 34.300000000000004
+    - type: ndcg_at_10
+      value: 29.372999999999998
+    - type: ndcg_at_100
+      value: 40.355000000000004
+    - type: ndcg_at_1000
+      value: 45.221000000000004
+    - type: ndcg_at_3
+      value: 27.230999999999998
+    - type: ndcg_at_5
+      value: 24.352
+    - type: precision_at_1
+      value: 34.300000000000004
+    - type: precision_at_10
+      value: 15.36
+    - type: precision_at_100
+      value: 3.116
+    - type: precision_at_1000
+      value: 0.426
+    - type: precision_at_3
+      value: 25.367
+    - type: precision_at_5
+      value: 21.62
+    - type: recall_at_1
+      value: 6.978
+    - type: recall_at_10
+      value: 31.142999999999997
+    - type: recall_at_100
+      value: 63.27199999999999
+    - type: recall_at_1000
+      value: 86.512
+    - type: recall_at_3
+      value: 15.433
+    - type: recall_at_5
+      value: 21.918000000000003
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.90996932803432
+    - type: cos_sim_spearman
+      value: 78.73848819688604
+    - type: euclidean_pearson
+      value: 78.82008134820491
+    - type: euclidean_spearman
+      value: 78.73797968799013
+    - type: manhattan_pearson
+      value: 78.98817729907871
+    - type: manhattan_spearman
+      value: 78.88989195290672
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.9169693104017
+    - type: cos_sim_spearman
+      value: 78.6067489618467
+    - type: euclidean_pearson
+      value: 83.04545335395649
+    - type: euclidean_spearman
+      value: 78.6070135484733
+    - type: manhattan_pearson
+      value: 83.49435095447187
+    - type: manhattan_spearman
+      value: 78.9690144080464
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.86389266236574
+    - type: cos_sim_spearman
+      value: 88.88070867328447
+    - type: euclidean_pearson
+      value: 88.52907860408021
+    - type: euclidean_spearman
+      value: 88.88041097815055
+    - type: manhattan_pearson
+      value: 88.65795865729802
+    - type: manhattan_spearman
+      value: 89.09614539167227
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.90258145848692
+    - type: cos_sim_spearman
+      value: 84.16679932371741
+    - type: euclidean_pearson
+      value: 84.95294032883719
+    - type: euclidean_spearman
+      value: 84.16781112349103
+    - type: manhattan_pearson
+      value: 85.18004344325733
+    - type: manhattan_spearman
+      value: 84.52374692147366
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.89191454971963
+    - type: cos_sim_spearman
+      value: 88.44916193520294
+    - type: euclidean_pearson
+      value: 87.85883738567667
+    - type: euclidean_spearman
+      value: 88.44928880968476
+    - type: manhattan_pearson
+      value: 88.1871454451139
+    - type: manhattan_spearman
+      value: 88.94431200065807
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.36716703986853
+    - type: cos_sim_spearman
+      value: 86.16132844716138
+    - type: euclidean_pearson
+      value: 85.25811478217042
+    - type: euclidean_spearman
+      value: 86.16215262183867
+    - type: manhattan_pearson
+      value: 85.43281209842574
+    - type: manhattan_spearman
+      value: 86.44640605346511
+  - 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: 88.29794966742152
+    - type: cos_sim_spearman
+      value: 88.27359278171622
+    - type: euclidean_pearson
+      value: 88.06469525438956
+    - type: euclidean_spearman
+      value: 88.28670070410784
+    - type: manhattan_pearson
+      value: 87.89087342332212
+    - type: manhattan_spearman
+      value: 88.11041644578535
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 66.75199645389645
+    - type: cos_sim_spearman
+      value: 66.20137384486978
+    - type: euclidean_pearson
+      value: 68.622513186352
+    - type: euclidean_spearman
+      value: 66.23640152769464
+    - type: manhattan_pearson
+      value: 68.97988448341921
+    - type: manhattan_spearman
+      value: 66.39142269154794
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.48693548775047
+    - type: cos_sim_spearman
+      value: 86.08823308674964
+    - type: euclidean_pearson
+      value: 85.65692420470154
+    - type: euclidean_spearman
+      value: 86.08859480677167
+    - type: manhattan_pearson
+      value: 85.90164709250936
+    - type: manhattan_spearman
+      value: 86.40785365360473
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 88.80093449044475
+    - type: mrr
+      value: 97.02094655526028
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: 0228b52cf27578f30900b9e5271d331663a030d7
+    metrics:
+    - type: map_at_1
+      value: 59.594
+    - type: map_at_10
+      value: 72.649
+    - type: map_at_100
+      value: 73.051
+    - type: map_at_1000
+      value: 73.056
+    - type: map_at_3
+      value: 69.667
+    - type: map_at_5
+      value: 71.528
+    - type: mrr_at_1
+      value: 62.666999999999994
+    - type: mrr_at_10
+      value: 73.625
+    - type: mrr_at_100
+      value: 73.956
+    - type: mrr_at_1000
+      value: 73.962
+    - type: mrr_at_3
+      value: 71.77799999999999
+    - type: mrr_at_5
+      value: 72.994
+    - type: ndcg_at_1
+      value: 62.666999999999994
+    - type: ndcg_at_10
+      value: 77.981
+    - type: ndcg_at_100
+      value: 79.474
+    - type: ndcg_at_1000
+      value: 79.569
+    - type: ndcg_at_3
+      value: 73.4
+    - type: ndcg_at_5
+      value: 75.806
+    - type: precision_at_1
+      value: 62.666999999999994
+    - type: precision_at_10
+      value: 10.567
+    - type: precision_at_100
+      value: 1.123
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 29.555999999999997
+    - type: precision_at_5
+      value: 19.467000000000002
+    - type: recall_at_1
+      value: 59.594
+    - type: recall_at_10
+      value: 93.167
+    - type: recall_at_100
+      value: 99.333
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 80.72200000000001
+    - type: recall_at_5
+      value: 86.79400000000001
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.67920792079208
+    - type: cos_sim_ap
+      value: 91.12451155203843
+    - type: cos_sim_f1
+      value: 82.7763496143959
+    - type: cos_sim_precision
+      value: 85.18518518518519
+    - type: cos_sim_recall
+      value: 80.5
+    - type: dot_accuracy
+      value: 99.68019801980198
+    - type: dot_ap
+      value: 91.12360077338997
+    - type: dot_f1
+      value: 82.81893004115227
+    - type: dot_precision
+      value: 85.27542372881356
+    - type: dot_recall
+      value: 80.5
+    - type: euclidean_accuracy
+      value: 99.67920792079208
+    - type: euclidean_ap
+      value: 91.12526537243333
+    - type: euclidean_f1
+      value: 82.7763496143959
+    - type: euclidean_precision
+      value: 85.18518518518519
+    - type: euclidean_recall
+      value: 80.5
+    - type: manhattan_accuracy
+      value: 99.68613861386139
+    - type: manhattan_ap
+      value: 91.52045550487428
+    - type: manhattan_f1
+      value: 83.38461538461539
+    - type: manhattan_precision
+      value: 85.57894736842105
+    - type: manhattan_recall
+      value: 81.3
+    - type: max_accuracy
+      value: 99.68613861386139
+    - type: max_ap
+      value: 91.52045550487428
+    - type: max_f1
+      value: 83.38461538461539
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 79.90649023801956
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 49.681864218959205
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 55.89272881949486
+    - type: mrr
+      value: 56.88128660555132
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.945233723225954
+    - type: cos_sim_spearman
+      value: 31.361651389713284
+    - type: dot_pearson
+      value: 31.96193321438737
+    - type: dot_spearman
+      value: 31.37045148053791
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.244
+    - type: map_at_10
+      value: 2.011
+    - type: map_at_100
+      value: 12.555
+    - type: map_at_1000
+      value: 30.386000000000003
+    - type: map_at_3
+      value: 0.718
+    - type: map_at_5
+      value: 1.118
+    - type: mrr_at_1
+      value: 94.0
+    - type: mrr_at_10
+      value: 97.0
+    - type: mrr_at_100
+      value: 97.0
+    - type: mrr_at_1000
+      value: 97.0
+    - type: mrr_at_3
+      value: 97.0
+    - type: mrr_at_5
+      value: 97.0
+    - type: ndcg_at_1
+      value: 93.0
+    - type: ndcg_at_10
+      value: 81.612
+    - type: ndcg_at_100
+      value: 63.468
+    - type: ndcg_at_1000
+      value: 56.508
+    - type: ndcg_at_3
+      value: 88.81599999999999
+    - type: ndcg_at_5
+      value: 85.599
+    - type: precision_at_1
+      value: 94.0
+    - type: precision_at_10
+      value: 84.0
+    - type: precision_at_100
+      value: 65.18
+    - type: precision_at_1000
+      value: 24.758
+    - type: precision_at_3
+      value: 93.333
+    - type: precision_at_5
+      value: 89.2
+    - type: recall_at_1
+      value: 0.244
+    - type: recall_at_10
+      value: 2.161
+    - type: recall_at_100
+      value: 15.862000000000002
+    - type: recall_at_1000
+      value: 53.146
+    - type: recall_at_3
+      value: 0.738
+    - type: recall_at_5
+      value: 1.167
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 82.948
+    - type: ap
+      value: 26.37282466987438
+    - type: f1
+      value: 66.9868680256644
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 73.78607809847199
+    - type: f1
+      value: 74.1324659804999
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 54.11838832136805
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 87.64975859808071
+    - type: cos_sim_ap
+      value: 79.0918389936708
+    - type: cos_sim_f1
+      value: 72.18518052585232
+    - type: cos_sim_precision
+      value: 68.98292858860303
+    - type: cos_sim_recall
+      value: 75.69920844327177
+    - type: dot_accuracy
+      value: 87.64379805686356
+    - type: dot_ap
+      value: 79.09373814934631
+    - type: dot_f1
+      value: 72.18216318785579
+    - type: dot_precision
+      value: 69.33171324422844
+    - type: dot_recall
+      value: 75.27704485488127
+    - type: euclidean_accuracy
+      value: 87.64975859808071
+    - type: euclidean_ap
+      value: 79.09199976607417
+    - type: euclidean_f1
+      value: 72.17610062893083
+    - type: euclidean_precision
+      value: 68.96634615384616
+    - type: euclidean_recall
+      value: 75.69920844327177
+    - type: manhattan_accuracy
+      value: 87.61399535077786
+    - type: manhattan_ap
+      value: 78.91167634954901
+    - type: manhattan_f1
+      value: 72.0995176440721
+    - type: manhattan_precision
+      value: 69.47162426614481
+    - type: manhattan_recall
+      value: 74.93403693931398
+    - type: max_accuracy
+      value: 87.64975859808071
+    - type: max_ap
+      value: 79.09373814934631
+    - type: max_f1
+      value: 72.18518052585232
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.43415997205729
+    - type: cos_sim_ap
+      value: 86.69200523144308
+    - type: cos_sim_f1
+      value: 79.16424418604652
+    - type: cos_sim_precision
+      value: 74.95871180842279
+    - type: cos_sim_recall
+      value: 83.86972590083154
+    - type: dot_accuracy
+      value: 89.43415997205729
+    - type: dot_ap
+      value: 86.69346224233253
+    - type: dot_f1
+      value: 79.15884340968833
+    - type: dot_precision
+      value: 77.26139862190294
+    - type: dot_recall
+      value: 81.15183246073299
+    - type: euclidean_accuracy
+      value: 89.43221950556915
+    - type: euclidean_ap
+      value: 86.69176407206174
+    - type: euclidean_f1
+      value: 79.16409231328366
+    - type: euclidean_precision
+      value: 74.97074413161698
+    - type: euclidean_recall
+      value: 83.85432707114259
+    - type: manhattan_accuracy
+      value: 89.49237396670159
+    - type: manhattan_ap
+      value: 86.72274876446832
+    - type: manhattan_f1
+      value: 79.18286510672633
+    - type: manhattan_precision
+      value: 75.6058271466592
+    - type: manhattan_recall
+      value: 83.1151832460733
+    - type: max_accuracy
+      value: 89.49237396670159
+    - type: max_ap
+      value: 86.72274876446832
+    - type: max_f1
+      value: 79.18286510672633
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/AFQMC
+      name: MTEB AFQMC
+      config: default
+      split: validation
+      revision: b44c3b011063adb25877c13823db83bb193913c4
+    metrics:
+    - type: cos_sim_pearson
+      value: 65.7103214280117
+    - type: cos_sim_spearman
+      value: 72.62249544256886
+    - type: euclidean_pearson
+      value: 71.36812167041296
+    - type: euclidean_spearman
+      value: 72.62325941111307
+    - type: manhattan_pearson
+      value: 71.25613851615468
+    - type: manhattan_spearman
+      value: 72.54244015155267
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/ATEC
+      name: MTEB ATEC
+      config: default
+      split: test
+      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
+    metrics:
+    - type: cos_sim_pearson
+      value: 59.903467713912974
+    - type: cos_sim_spearman
+      value: 62.8205444560593
+    - type: euclidean_pearson
+      value: 67.06329904158285
+    - type: euclidean_spearman
+      value: 62.82051743557576
+    - type: manhattan_pearson
+      value: 66.97943759454319
+    - type: manhattan_spearman
+      value: 62.763028353169325
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (zh)
+      config: zh
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 53.57399999999999
+    - type: f1
+      value: 50.57496370390049
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/BQ
+      name: MTEB BQ
+      config: default
+      split: test
+      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
+    metrics:
+    - type: cos_sim_pearson
+      value: 79.09488668095824
+    - type: cos_sim_spearman
+      value: 81.34731850197655
+    - type: euclidean_pearson
+      value: 82.19030116395511
+    - type: euclidean_spearman
+      value: 81.34699287691117
+    - type: manhattan_pearson
+      value: 82.19510202220734
+    - type: manhattan_spearman
+      value: 81.35888167395795
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/CLSClusteringP2P
+      name: MTEB CLSClusteringP2P
+      config: default
+      split: test
+      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
+    metrics:
+    - type: v_measure
+      value: 48.60079470735067
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/CLSClusteringS2S
+      name: MTEB CLSClusteringS2S
+      config: default
+      split: test
+      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
+    metrics:
+    - type: v_measure
+      value: 46.125672623152155
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/CMedQAv1-reranking
+      name: MTEB CMedQAv1
+      config: default
+      split: test
+      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
+    metrics:
+    - type: map
+      value: 88.0714642862605
+    - type: mrr
+      value: 90.17428571428572
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/CMedQAv2-reranking
+      name: MTEB CMedQAv2
+      config: default
+      split: test
+      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
+    metrics:
+    - type: map
+      value: 88.51263170426526
+    - type: mrr
+      value: 90.53325396825396
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/CmedqaRetrieval
+      name: MTEB CmedqaRetrieval
+      config: default
+      split: dev
+      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
+    metrics:
+    - type: map_at_1
+      value: 29.610999999999997
+    - type: map_at_10
+      value: 42.832
+    - type: map_at_100
+      value: 44.639
+    - type: map_at_1000
+      value: 44.738
+    - type: map_at_3
+      value: 38.549
+    - type: map_at_5
+      value: 40.905
+    - type: mrr_at_1
+      value: 44.461
+    - type: mrr_at_10
+      value: 52.274
+    - type: mrr_at_100
+      value: 53.179
+    - type: mrr_at_1000
+      value: 53.213
+    - type: mrr_at_3
+      value: 49.917
+    - type: mrr_at_5
+      value: 51.13799999999999
+    - type: ndcg_at_1
+      value: 44.461
+    - type: ndcg_at_10
+      value: 49.557
+    - type: ndcg_at_100
+      value: 56.432
+    - type: ndcg_at_1000
+      value: 58.050000000000004
+    - type: ndcg_at_3
+      value: 44.419
+    - type: ndcg_at_5
+      value: 46.386
+    - type: precision_at_1
+      value: 44.461
+    - type: precision_at_10
+      value: 10.673
+    - type: precision_at_100
+      value: 1.6310000000000002
+    - type: precision_at_1000
+      value: 0.184
+    - type: precision_at_3
+      value: 24.656
+    - type: precision_at_5
+      value: 17.619
+    - type: recall_at_1
+      value: 29.610999999999997
+    - type: recall_at_10
+      value: 60.112
+    - type: recall_at_100
+      value: 88.346
+    - type: recall_at_1000
+      value: 98.993
+    - type: recall_at_3
+      value: 44.243
+    - type: recall_at_5
+      value: 50.64300000000001
+  - task:
+      type: PairClassification
+    dataset:
+      type: C-MTEB/CMNLI
+      name: MTEB Cmnli
+      config: default
+      split: validation
+      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
+    metrics:
+    - type: cos_sim_accuracy
+      value: 82.17678893565845
+    - type: cos_sim_ap
+      value: 89.77899888165327
+    - type: cos_sim_f1
+      value: 83.03306727480046
+    - type: cos_sim_precision
+      value: 81.0371689294458
+    - type: cos_sim_recall
+      value: 85.1297638531681
+    - type: dot_accuracy
+      value: 82.1647624774504
+    - type: dot_ap
+      value: 89.78074283382892
+    - type: dot_f1
+      value: 83.03306727480046
+    - type: dot_precision
+      value: 81.0371689294458
+    - type: dot_recall
+      value: 85.1297638531681
+    - type: euclidean_accuracy
+      value: 82.1888153938665
+    - type: euclidean_ap
+      value: 89.77917362529757
+    - type: euclidean_f1
+      value: 83.03306727480046
+    - type: euclidean_precision
+      value: 81.0371689294458
+    - type: euclidean_recall
+      value: 85.1297638531681
+    - type: manhattan_accuracy
+      value: 81.82802164762477
+    - type: manhattan_ap
+      value: 89.56708721584408
+    - type: manhattan_f1
+      value: 82.72179938657275
+    - type: manhattan_precision
+      value: 80.44631020768891
+    - type: manhattan_recall
+      value: 85.1297638531681
+    - type: max_accuracy
+      value: 82.1888153938665
+    - type: max_ap
+      value: 89.78074283382892
+    - type: max_f1
+      value: 83.03306727480046
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/CovidRetrieval
+      name: MTEB CovidRetrieval
+      config: default
+      split: dev
+      revision: 1271c7809071a13532e05f25fb53511ffce77117
+    metrics:
+    - type: map_at_1
+      value: 66.807
+    - type: map_at_10
+      value: 75.47399999999999
+    - type: map_at_100
+      value: 75.837
+    - type: map_at_1000
+      value: 75.84
+    - type: map_at_3
+      value: 73.67399999999999
+    - type: map_at_5
+      value: 74.558
+    - type: mrr_at_1
+      value: 66.913
+    - type: mrr_at_10
+      value: 75.467
+    - type: mrr_at_100
+      value: 75.823
+    - type: mrr_at_1000
+      value: 75.82600000000001
+    - type: mrr_at_3
+      value: 73.67399999999999
+    - type: mrr_at_5
+      value: 74.586
+    - type: ndcg_at_1
+      value: 66.913
+    - type: ndcg_at_10
+      value: 79.591
+    - type: ndcg_at_100
+      value: 81.15
+    - type: ndcg_at_1000
+      value: 81.229
+    - type: ndcg_at_3
+      value: 75.83800000000001
+    - type: ndcg_at_5
+      value: 77.45
+    - type: precision_at_1
+      value: 66.913
+    - type: precision_at_10
+      value: 9.325999999999999
+    - type: precision_at_100
+      value: 1.0030000000000001
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 27.432000000000002
+    - type: precision_at_5
+      value: 17.281
+    - type: recall_at_1
+      value: 66.807
+    - type: recall_at_10
+      value: 92.46600000000001
+    - type: recall_at_100
+      value: 99.262
+    - type: recall_at_1000
+      value: 99.895
+    - type: recall_at_3
+      value: 82.086
+    - type: recall_at_5
+      value: 85.985
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/DuRetrieval
+      name: MTEB DuRetrieval
+      config: default
+      split: dev
+      revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
+    metrics:
+    - type: map_at_1
+      value: 26.599
+    - type: map_at_10
+      value: 81.577
+    - type: map_at_100
+      value: 84.368
+    - type: map_at_1000
+      value: 84.39999999999999
+    - type: map_at_3
+      value: 56.825
+    - type: map_at_5
+      value: 71.462
+    - type: mrr_at_1
+      value: 90.5
+    - type: mrr_at_10
+      value: 93.798
+    - type: mrr_at_100
+      value: 93.851
+    - type: mrr_at_1000
+      value: 93.853
+    - type: mrr_at_3
+      value: 93.5
+    - type: mrr_at_5
+      value: 93.672
+    - type: ndcg_at_1
+      value: 90.5
+    - type: ndcg_at_10
+      value: 88.633
+    - type: ndcg_at_100
+      value: 91.217
+    - type: ndcg_at_1000
+      value: 91.484
+    - type: ndcg_at_3
+      value: 87.29599999999999
+    - type: ndcg_at_5
+      value: 86.31299999999999
+    - type: precision_at_1
+      value: 90.5
+    - type: precision_at_10
+      value: 42.18
+    - type: precision_at_100
+      value: 4.839
+    - type: precision_at_1000
+      value: 0.49
+    - type: precision_at_3
+      value: 78.133
+    - type: precision_at_5
+      value: 65.82000000000001
+    - type: recall_at_1
+      value: 26.599
+    - type: recall_at_10
+      value: 90.137
+    - type: recall_at_100
+      value: 98.393
+    - type: recall_at_1000
+      value: 99.747
+    - type: recall_at_3
+      value: 59.199999999999996
+    - type: recall_at_5
+      value: 76.173
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/EcomRetrieval
+      name: MTEB EcomRetrieval
+      config: default
+      split: dev
+      revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
+    metrics:
+    - type: map_at_1
+      value: 55.2
+    - type: map_at_10
+      value: 64.925
+    - type: map_at_100
+      value: 65.446
+    - type: map_at_1000
+      value: 65.459
+    - type: map_at_3
+      value: 62.266999999999996
+    - type: map_at_5
+      value: 64.107
+    - type: mrr_at_1
+      value: 55.2
+    - type: mrr_at_10
+      value: 64.925
+    - type: mrr_at_100
+      value: 65.446
+    - type: mrr_at_1000
+      value: 65.459
+    - type: mrr_at_3
+      value: 62.266999999999996
+    - type: mrr_at_5
+      value: 64.107
+    - type: ndcg_at_1
+      value: 55.2
+    - type: ndcg_at_10
+      value: 69.85900000000001
+    - type: ndcg_at_100
+      value: 72.194
+    - type: ndcg_at_1000
+      value: 72.506
+    - type: ndcg_at_3
+      value: 64.538
+    - type: ndcg_at_5
+      value: 67.843
+    - type: precision_at_1
+      value: 55.2
+    - type: precision_at_10
+      value: 8.540000000000001
+    - type: precision_at_100
+      value: 0.959
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 23.7
+    - type: precision_at_5
+      value: 15.82
+    - type: recall_at_1
+      value: 55.2
+    - type: recall_at_10
+      value: 85.39999999999999
+    - type: recall_at_100
+      value: 95.89999999999999
+    - type: recall_at_1000
+      value: 98.3
+    - type: recall_at_3
+      value: 71.1
+    - type: recall_at_5
+      value: 79.10000000000001
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/IFlyTek-classification
+      name: MTEB IFlyTek
+      config: default
+      split: validation
+      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
+    metrics:
+    - type: accuracy
+      value: 53.92843401308196
+    - type: f1
+      value: 40.44614048360205
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/JDReview-classification
+      name: MTEB JDReview
+      config: default
+      split: test
+      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
+    metrics:
+    - type: accuracy
+      value: 86.22889305816133
+    - type: ap
+      value: 55.542660925360835
+    - type: f1
+      value: 81.26964576055315
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/LCQMC
+      name: MTEB LCQMC
+      config: default
+      split: test
+      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
+    metrics:
+    - type: cos_sim_pearson
+      value: 68.50234587951512
+    - type: cos_sim_spearman
+      value: 73.04229322574785
+    - type: euclidean_pearson
+      value: 71.76475440799503
+    - type: euclidean_spearman
+      value: 73.04203161533454
+    - type: manhattan_pearson
+      value: 71.75530397681868
+    - type: manhattan_spearman
+      value: 73.01054099221574
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/Mmarco-reranking
+      name: MTEB MMarcoReranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 22.67056873798454
+    - type: mrr
+      value: 21.63888888888889
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/MMarcoRetrieval
+      name: MTEB MMarcoRetrieval
+      config: default
+      split: dev
+      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
+    metrics:
+    - type: map_at_1
+      value: 67.65
+    - type: map_at_10
+      value: 76.726
+    - type: map_at_100
+      value: 77.03
+    - type: map_at_1000
+      value: 77.042
+    - type: map_at_3
+      value: 74.924
+    - type: map_at_5
+      value: 76.08200000000001
+    - type: mrr_at_1
+      value: 69.87100000000001
+    - type: mrr_at_10
+      value: 77.238
+    - type: mrr_at_100
+      value: 77.492
+    - type: mrr_at_1000
+      value: 77.503
+    - type: mrr_at_3
+      value: 75.633
+    - type: mrr_at_5
+      value: 76.678
+    - type: ndcg_at_1
+      value: 69.87100000000001
+    - type: ndcg_at_10
+      value: 80.37100000000001
+    - type: ndcg_at_100
+      value: 81.658
+    - type: ndcg_at_1000
+      value: 81.94200000000001
+    - type: ndcg_at_3
+      value: 76.94
+    - type: ndcg_at_5
+      value: 78.926
+    - type: precision_at_1
+      value: 69.87100000000001
+    - type: precision_at_10
+      value: 9.681
+    - type: precision_at_100
+      value: 1.032
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_3
+      value: 28.906
+    - type: precision_at_5
+      value: 18.404
+    - type: recall_at_1
+      value: 67.65
+    - type: recall_at_10
+      value: 91.078
+    - type: recall_at_100
+      value: 96.767
+    - type: recall_at_1000
+      value: 98.933
+    - type: recall_at_3
+      value: 82.02000000000001
+    - type: recall_at_5
+      value: 86.771
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (zh-CN)
+      config: zh-CN
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 79.7848016139879
+    - type: f1
+      value: 76.99189501152489
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (zh-CN)
+      config: zh-CN
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 83.64492266308001
+    - type: f1
+      value: 82.84955852311293
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/MedicalRetrieval
+      name: MTEB MedicalRetrieval
+      config: default
+      split: dev
+      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
+    metrics:
+    - type: map_at_1
+      value: 54.400000000000006
+    - type: map_at_10
+      value: 60.529999999999994
+    - type: map_at_100
+      value: 61.114999999999995
+    - type: map_at_1000
+      value: 61.153999999999996
+    - type: map_at_3
+      value: 59.150000000000006
+    - type: map_at_5
+      value: 59.955000000000005
+    - type: mrr_at_1
+      value: 54.50000000000001
+    - type: mrr_at_10
+      value: 60.58
+    - type: mrr_at_100
+      value: 61.165000000000006
+    - type: mrr_at_1000
+      value: 61.204
+    - type: mrr_at_3
+      value: 59.199999999999996
+    - type: mrr_at_5
+      value: 60.004999999999995
+    - type: ndcg_at_1
+      value: 54.400000000000006
+    - type: ndcg_at_10
+      value: 63.522999999999996
+    - type: ndcg_at_100
+      value: 66.742
+    - type: ndcg_at_1000
+      value: 67.818
+    - type: ndcg_at_3
+      value: 60.702999999999996
+    - type: ndcg_at_5
+      value: 62.149
+    - type: precision_at_1
+      value: 54.400000000000006
+    - type: precision_at_10
+      value: 7.290000000000001
+    - type: precision_at_100
+      value: 0.8880000000000001
+    - type: precision_at_1000
+      value: 0.097
+    - type: precision_at_3
+      value: 21.733
+    - type: precision_at_5
+      value: 13.74
+    - type: recall_at_1
+      value: 54.400000000000006
+    - type: recall_at_10
+      value: 72.89999999999999
+    - type: recall_at_100
+      value: 88.8
+    - type: recall_at_1000
+      value: 97.39999999999999
+    - type: recall_at_3
+      value: 65.2
+    - type: recall_at_5
+      value: 68.7
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/MultilingualSentiment-classification
+      name: MTEB MultilingualSentiment
+      config: default
+      split: validation
+      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
+    metrics:
+    - type: accuracy
+      value: 77.16000000000001
+    - type: f1
+      value: 76.97953105264186
+  - task:
+      type: PairClassification
+    dataset:
+      type: C-MTEB/OCNLI
+      name: MTEB Ocnli
+      config: default
+      split: validation
+      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
+    metrics:
+    - type: cos_sim_accuracy
+      value: 79.48023822414727
+    - type: cos_sim_ap
+      value: 84.483894203704
+    - type: cos_sim_f1
+      value: 80.55130168453292
+    - type: cos_sim_precision
+      value: 77.96442687747036
+    - type: cos_sim_recall
+      value: 83.31573389651531
+    - type: dot_accuracy
+      value: 79.48023822414727
+    - type: dot_ap
+      value: 84.49261973641154
+    - type: dot_f1
+      value: 80.55130168453292
+    - type: dot_precision
+      value: 77.96442687747036
+    - type: dot_recall
+      value: 83.31573389651531
+    - type: euclidean_accuracy
+      value: 79.48023822414727
+    - type: euclidean_ap
+      value: 84.48068994534293
+    - type: euclidean_f1
+      value: 80.55130168453292
+    - type: euclidean_precision
+      value: 77.96442687747036
+    - type: euclidean_recall
+      value: 83.31573389651531
+    - type: manhattan_accuracy
+      value: 79.37195452084461
+    - type: manhattan_ap
+      value: 84.45931914984077
+    - type: manhattan_f1
+      value: 80.53142565150742
+    - type: manhattan_precision
+      value: 78.01980198019803
+    - type: manhattan_recall
+      value: 83.21013727560718
+    - type: max_accuracy
+      value: 79.48023822414727
+    - type: max_ap
+      value: 84.49261973641154
+    - type: max_f1
+      value: 80.55130168453292
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/OnlineShopping-classification
+      name: MTEB OnlineShopping
+      config: default
+      split: test
+      revision: e610f2ebd179a8fda30ae534c3878750a96db120
+    metrics:
+    - type: accuracy
+      value: 94.3
+    - type: ap
+      value: 92.84324255663363
+    - type: f1
+      value: 94.29275233313747
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/PAWSX
+      name: MTEB PAWSX
+      config: default
+      split: test
+      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
+    metrics:
+    - type: cos_sim_pearson
+      value: 50.25954594958544
+    - type: cos_sim_spearman
+      value: 55.1554675848278
+    - type: euclidean_pearson
+      value: 53.71113201288935
+    - type: euclidean_spearman
+      value: 55.1558156481826
+    - type: manhattan_pearson
+      value: 53.816355416293646
+    - type: manhattan_spearman
+      value: 55.14310001157623
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/QBQTC
+      name: MTEB QBQTC
+      config: default
+      split: test
+      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
+    metrics:
+    - type: cos_sim_pearson
+      value: 29.187751074660845
+    - type: cos_sim_spearman
+      value: 30.889291180505868
+    - type: euclidean_pearson
+      value: 28.73210543314964
+    - type: euclidean_spearman
+      value: 30.889662787316784
+    - type: manhattan_pearson
+      value: 29.21703764852649
+    - type: manhattan_spearman
+      value: 31.47317743982721
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (zh)
+      config: zh
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 61.1898272680276
+    - type: cos_sim_spearman
+      value: 64.93927648503598
+    - type: euclidean_pearson
+      value: 61.11026474293018
+    - type: euclidean_spearman
+      value: 64.94229072933243
+    - type: manhattan_pearson
+      value: 62.19814132782434
+    - type: manhattan_spearman
+      value: 65.2583560877569
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/STSB
+      name: MTEB STSB
+      config: default
+      split: test
+      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
+    metrics:
+    - type: cos_sim_pearson
+      value: 78.76122365246462
+    - type: cos_sim_spearman
+      value: 78.68211802616669
+    - type: euclidean_pearson
+      value: 77.17265704615994
+    - type: euclidean_spearman
+      value: 78.68087191872655
+    - type: manhattan_pearson
+      value: 77.61313585452194
+    - type: manhattan_spearman
+      value: 79.22153641729726
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/T2Reranking
+      name: MTEB T2Reranking
+      config: default
+      split: dev
+      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
+    metrics:
+    - type: map
+      value: 67.80243119237458
+    - type: mrr
+      value: 78.00406497512118
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/T2Retrieval
+      name: MTEB T2Retrieval
+      config: default
+      split: dev
+      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
+    metrics:
+    - type: map_at_1
+      value: 28.936
+    - type: map_at_10
+      value: 82.256
+    - type: map_at_100
+      value: 85.688
+    - type: map_at_1000
+      value: 85.727
+    - type: map_at_3
+      value: 57.655
+    - type: map_at_5
+      value: 71.05
+    - type: mrr_at_1
+      value: 92.548
+    - type: mrr_at_10
+      value: 94.586
+    - type: mrr_at_100
+      value: 94.64399999999999
+    - type: mrr_at_1000
+      value: 94.646
+    - type: mrr_at_3
+      value: 94.255
+    - type: mrr_at_5
+      value: 94.464
+    - type: ndcg_at_1
+      value: 92.548
+    - type: ndcg_at_10
+      value: 88.74600000000001
+    - type: ndcg_at_100
+      value: 91.58500000000001
+    - type: ndcg_at_1000
+      value: 91.953
+    - type: ndcg_at_3
+      value: 89.578
+    - type: ndcg_at_5
+      value: 88.584
+    - type: precision_at_1
+      value: 92.548
+    - type: precision_at_10
+      value: 43.954
+    - type: precision_at_100
+      value: 5.099
+    - type: precision_at_1000
+      value: 0.518
+    - type: precision_at_3
+      value: 78.213
+    - type: precision_at_5
+      value: 65.839
+    - type: recall_at_1
+      value: 28.936
+    - type: recall_at_10
+      value: 87.869
+    - type: recall_at_100
+      value: 97.286
+    - type: recall_at_1000
+      value: 99.173
+    - type: recall_at_3
+      value: 59.157000000000004
+    - type: recall_at_5
+      value: 74.02499999999999
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/TNews-classification
+      name: MTEB TNews
+      config: default
+      split: validation
+      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
+    metrics:
+    - type: accuracy
+      value: 53.269
+    - type: f1
+      value: 50.68236445411186
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/ThuNewsClusteringP2P
+      name: MTEB ThuNewsClusteringP2P
+      config: default
+      split: test
+      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
+    metrics:
+    - type: v_measure
+      value: 86.47994658950259
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/ThuNewsClusteringS2S
+      name: MTEB ThuNewsClusteringS2S
+      config: default
+      split: test
+      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
+    metrics:
+    - type: v_measure
+      value: 85.34791895793325
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/VideoRetrieval
+      name: MTEB VideoRetrieval
+      config: default
+      split: dev
+      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
+    metrics:
+    - type: map_at_1
+      value: 65.5
+    - type: map_at_10
+      value: 74.134
+    - type: map_at_100
+      value: 74.49799999999999
+    - type: map_at_1000
+      value: 74.509
+    - type: map_at_3
+      value: 72.467
+    - type: map_at_5
+      value: 73.462
+    - type: mrr_at_1
+      value: 65.5
+    - type: mrr_at_10
+      value: 74.134
+    - type: mrr_at_100
+      value: 74.49799999999999
+    - type: mrr_at_1000
+      value: 74.509
+    - type: mrr_at_3
+      value: 72.467
+    - type: mrr_at_5
+      value: 73.462
+    - type: ndcg_at_1
+      value: 65.5
+    - type: ndcg_at_10
+      value: 78.144
+    - type: ndcg_at_100
+      value: 79.726
+    - type: ndcg_at_1000
+      value: 79.97800000000001
+    - type: ndcg_at_3
+      value: 74.735
+    - type: ndcg_at_5
+      value: 76.55999999999999
+    - type: precision_at_1
+      value: 65.5
+    - type: precision_at_10
+      value: 9.06
+    - type: precision_at_100
+      value: 0.976
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 27.1
+    - type: precision_at_5
+      value: 17.16
+    - type: recall_at_1
+      value: 65.5
+    - type: recall_at_10
+      value: 90.60000000000001
+    - type: recall_at_100
+      value: 97.6
+    - type: recall_at_1000
+      value: 99.5
+    - type: recall_at_3
+      value: 81.3
+    - type: recall_at_5
+      value: 85.8
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/waimai-classification
+      name: MTEB Waimai
+      config: default
+      split: test
+      revision: 339287def212450dcaa9df8c22bf93e9980c7023
+    metrics:
+    - type: accuracy
+      value: 89.43999999999998
+    - type: ap
+      value: 75.53653890653014
+    - type: f1
+      value: 87.91597334503136
+---
+
+## gte-Qwen2-7B-instruct
+
+**gte-Qwen2-7B-instruct** is the latest model in the gte (General Text Embedding) model family. 
+
+Recently, the [**Qwen team**](https://huggingface.co/Qwen) released the Qwen2 series models, and we have trained the **gte-Qwen2-7B-instruct** model based on the [Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) LLM model. Compared to the [gte-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) model, the **gte-Qwen2-7B-instruct** model uses the same training data and training strategies during the finetuning stage, with the only difference being the upgraded base model to Qwen2-7B. Considering the improvements in the Qwen2 series models compared to the Qwen1.5 series, we can also expect consistent performance enhancements in the embedding models.
+
+The model incorporates several key advancements:
+
+- Integration of bidirectional attention mechanisms, enriching its contextual understanding.
+- Instruction tuning, applied solely on the query side for streamlined efficiency
+- Comprehensive training across a vast, multilingual text corpus spanning diverse domains and scenarios. This training leverages both weakly supervised and supervised data, ensuring the model's applicability across numerous languages and a wide array of downstream tasks.
+
+
+## Model Information
+- Model Size: 7B
+- Embedding Dimension: 4096
+- Max Input Tokens: 32k
+
+## Requirements
+```
+transformers>=4.39.2
+flash_attn>=2.5.6
+```
+## Usage 
+
+### Sentence Transformers
+
+```python
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer("Alibaba-NLP/gte-Qwen2-7B-instruct", trust_remote_code=True)
+# In case you want to reduce the maximum length:
+model.max_seq_length = 8192
+
+queries = [
+    "how much protein should a female eat",
+    "summit define",
+]
+documents = [
+    "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.",
+    "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.",
+]
+
+query_embeddings = model.encode(queries, prompt_name="query")
+document_embeddings = model.encode(documents)
+
+scores = (query_embeddings @ document_embeddings.T) * 100
+print(scores.tolist())
+```
+
+Observe the [config_sentence_transformers.json](config_sentence_transformers.json) to see all pre-built prompt names. Otherwise, you can use `model.encode(queries, prompt="Instruct: ...\nQuery: "` to use a custom prompt of your choice.
+
+### Transformers
+
+```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 much protein should a female eat'),
+    get_detailed_instruct(task, 'summit define')
+]
+# No need to add instruction for retrieval documents
+documents = [
+    "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.",
+    "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."
+]
+input_texts = queries + documents
+
+tokenizer = AutoTokenizer.from_pretrained('Alibaba-NLP/gte-Qwen2-7B-instruct', trust_remote_code=True)
+model = AutoModel.from_pretrained('Alibaba-NLP/gte-Qwen2-7B-instruct', trust_remote_code=True)
+
+max_length = 8192
+
+# Tokenize the input texts
+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())
+```
+
+## Evaluation
+
+### MTEB & C-MTEB
+
+You can use the [scripts/eval_mteb.py](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct/blob/main/scripts/eval_mteb.py) to reproduce the following result of **gte-Qwen2-7B-instruct** on MTEB(English)/C-MTEB(Chinese):
+
+| Model Name | MTEB(56)  | C-MTEB(35) | 
+|:----:|:---------:|:----------:| 
+| [bge-base-en-1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) |   64.23   |     -      | 
+| [bge-large-en-1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) |   63.55   |     -      |
+| [gte-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) |   65.39   |     -      |
+| [gte-base-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) |   64.11   |     -      |
+| [mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) |   64.68   |     -      |
+| [acge_text_embedding](https://huggingface.co/aspire/acge_text_embedding) |     -     |   69.07    | 
+| [stella-mrl-large-zh-v3.5-1792d](https://huggingface.co/infgrad/stella-mrl-large-zh-v3.5-1792d) |     -     |   68.55    |
+| [gte-large-zh](https://huggingface.co/thenlper/gte-large-zh) |     -     |   66.72    |
+| [multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) |   59.45   |   56.21    | 
+| [multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) |   61.50   |   58.81    | 
+| [e5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) |   66.63   |   60.81    | 
+| [gte-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) |   67.34   |   69.52    |
+| [NV-Embed-v1](https://huggingface.co/nvidia/NV-Embed-v1) |   69.32   |     -      |
+| [**gte-Qwen2-7B-instruct**](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct) | **70.04** | **71.98**  |
+
+### GTE Models
+
+The gte series models have consistently released two types of models: encoder-only models (based on the BERT architecture) and decode-only models (based on the LLM architecture). 
+
+## Citation
+
+If you find our paper or models helpful, please consider cite:
+
+```
+@article{li2023towards,
+  title={Towards general text embeddings with multi-stage contrastive learning},
+  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
+  journal={arXiv preprint arXiv:2308.03281},
+  year={2023}
+}
+```