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README.md

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+---
+tags:
+- mteb
+- sentence-transformers
+- transformers
+- Qwen
+- sentence-similarity
+- llama-cpp
+- gguf-my-repo
+model-index:
+- name: gte-qwen1.5-7b
+  results:
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonCounterfactualClassification (en)
+      type: mteb/amazon_counterfactual
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 83.16417910447761
+    - type: ap
+      value: 49.37655308937739
+    - type: f1
+      value: 77.52987230462615
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonPolarityClassification
+      type: mteb/amazon_polarity
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 96.6959
+    - type: ap
+      value: 94.90885739242472
+    - type: f1
+      value: 96.69477648952649
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonReviewsClassification (en)
+      type: mteb/amazon_reviews_multi
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 62.168
+    - type: f1
+      value: 60.411431278343755
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB ArguAna
+      type: mteb/arguana
+      config: default
+      split: test
+      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
+    metrics:
+    - type: map_at_1
+      value: 36.415
+    - type: map_at_10
+      value: 53.505
+    - type: map_at_100
+      value: 54.013
+    - type: map_at_1000
+      value: 54.013
+    - type: map_at_3
+      value: 48.459
+    - type: map_at_5
+      value: 51.524
+    - type: mrr_at_1
+      value: 36.842000000000006
+    - type: mrr_at_10
+      value: 53.679
+    - type: mrr_at_100
+      value: 54.17999999999999
+    - type: mrr_at_1000
+      value: 54.17999999999999
+    - type: mrr_at_3
+      value: 48.613
+    - type: mrr_at_5
+      value: 51.696
+    - type: ndcg_at_1
+      value: 36.415
+    - type: ndcg_at_10
+      value: 62.644999999999996
+    - type: ndcg_at_100
+      value: 64.60000000000001
+    - type: ndcg_at_1000
+      value: 64.60000000000001
+    - type: ndcg_at_3
+      value: 52.44799999999999
+    - type: ndcg_at_5
+      value: 57.964000000000006
+    - type: precision_at_1
+      value: 36.415
+    - type: precision_at_10
+      value: 9.161
+    - type: precision_at_100
+      value: 0.996
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 21.337
+    - type: precision_at_5
+      value: 15.476999999999999
+    - type: recall_at_1
+      value: 36.415
+    - type: recall_at_10
+      value: 91.607
+    - type: recall_at_100
+      value: 99.644
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 64.011
+    - type: recall_at_5
+      value: 77.383
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ArxivClusteringP2P
+      type: mteb/arxiv-clustering-p2p
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 56.40183100758549
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ArxivClusteringS2S
+      type: mteb/arxiv-clustering-s2s
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 51.44814171373338
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB AskUbuntuDupQuestions
+      type: mteb/askubuntudupquestions-reranking
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 66.00208703259058
+    - type: mrr
+      value: 78.95165545442553
+  - task:
+      type: STS
+    dataset:
+      name: MTEB BIOSSES
+      type: mteb/biosses-sts
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.12591694410098
+    - type: cos_sim_spearman
+      value: 81.11570369802254
+    - type: euclidean_pearson
+      value: 80.91709076204458
+    - type: euclidean_spearman
+      value: 81.11570369802254
+    - type: manhattan_pearson
+      value: 80.71719561024605
+    - type: manhattan_spearman
+      value: 81.21510355327713
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB Banking77Classification
+      type: mteb/banking77
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 81.67857142857142
+    - type: f1
+      value: 80.84103272994895
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BiorxivClusteringP2P
+      type: mteb/biorxiv-clustering-p2p
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 49.008657468552016
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BiorxivClusteringS2S
+      type: mteb/biorxiv-clustering-s2s
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 45.05901064421589
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackAndroidRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: f46a197baaae43b4f621051089b82a364682dfeb
+    metrics:
+    - type: map_at_1
+      value: 32.694
+    - type: map_at_10
+      value: 43.895
+    - type: map_at_100
+      value: 45.797
+    - type: map_at_1000
+      value: 45.922000000000004
+    - type: map_at_3
+      value: 40.141
+    - type: map_at_5
+      value: 42.077
+    - type: mrr_at_1
+      value: 40.2
+    - type: mrr_at_10
+      value: 50.11
+    - type: mrr_at_100
+      value: 51.101
+    - type: mrr_at_1000
+      value: 51.13100000000001
+    - type: mrr_at_3
+      value: 47.735
+    - type: mrr_at_5
+      value: 48.922
+    - type: ndcg_at_1
+      value: 40.2
+    - type: ndcg_at_10
+      value: 50.449999999999996
+    - type: ndcg_at_100
+      value: 56.85
+    - type: ndcg_at_1000
+      value: 58.345
+    - type: ndcg_at_3
+      value: 45.261
+    - type: ndcg_at_5
+      value: 47.298
+    - type: precision_at_1
+      value: 40.2
+    - type: precision_at_10
+      value: 9.742
+    - type: precision_at_100
+      value: 1.6480000000000001
+    - type: precision_at_1000
+      value: 0.214
+    - type: precision_at_3
+      value: 21.841
+    - type: precision_at_5
+      value: 15.68
+    - type: recall_at_1
+      value: 32.694
+    - type: recall_at_10
+      value: 62.751999999999995
+    - type: recall_at_100
+      value: 88.619
+    - type: recall_at_1000
+      value: 97.386
+    - type: recall_at_3
+      value: 47.087
+    - type: recall_at_5
+      value: 53.108999999999995
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackEnglishRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
+    metrics:
+    - type: map_at_1
+      value: 27.849
+    - type: map_at_10
+      value: 37.938
+    - type: map_at_100
+      value: 39.211
+    - type: map_at_1000
+      value: 39.333
+    - type: map_at_3
+      value: 35.314
+    - type: map_at_5
+      value: 36.666
+    - type: mrr_at_1
+      value: 34.904
+    - type: mrr_at_10
+      value: 43.869
+    - type: mrr_at_100
+      value: 44.614
+    - type: mrr_at_1000
+      value: 44.662
+    - type: mrr_at_3
+      value: 41.815000000000005
+    - type: mrr_at_5
+      value: 42.943
+    - type: ndcg_at_1
+      value: 34.904
+    - type: ndcg_at_10
+      value: 43.605
+    - type: ndcg_at_100
+      value: 48.339999999999996
+    - type: ndcg_at_1000
+      value: 50.470000000000006
+    - type: ndcg_at_3
+      value: 39.835
+    - type: ndcg_at_5
+      value: 41.364000000000004
+    - type: precision_at_1
+      value: 34.904
+    - type: precision_at_10
+      value: 8.222999999999999
+    - type: precision_at_100
+      value: 1.332
+    - type: precision_at_1000
+      value: 0.183
+    - type: precision_at_3
+      value: 19.575
+    - type: precision_at_5
+      value: 13.58
+    - type: recall_at_1
+      value: 27.849
+    - type: recall_at_10
+      value: 53.635
+    - type: recall_at_100
+      value: 73.932
+    - type: recall_at_1000
+      value: 87.29599999999999
+    - type: recall_at_3
+      value: 42.019
+    - type: recall_at_5
+      value: 46.58
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackGamingRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
+    metrics:
+    - type: map_at_1
+      value: 29.182999999999996
+    - type: map_at_10
+      value: 41.233
+    - type: map_at_100
+      value: 42.52
+    - type: map_at_1000
+      value: 42.589
+    - type: map_at_3
+      value: 37.284
+    - type: map_at_5
+      value: 39.586
+    - type: mrr_at_1
+      value: 33.793
+    - type: mrr_at_10
+      value: 44.572
+    - type: mrr_at_100
+      value: 45.456
+    - type: mrr_at_1000
+      value: 45.497
+    - type: mrr_at_3
+      value: 41.275
+    - type: mrr_at_5
+      value: 43.278
+    - type: ndcg_at_1
+      value: 33.793
+    - type: ndcg_at_10
+      value: 47.823
+    - type: ndcg_at_100
+      value: 52.994
+    - type: ndcg_at_1000
+      value: 54.400000000000006
+    - type: ndcg_at_3
+      value: 40.82
+    - type: ndcg_at_5
+      value: 44.426
+    - type: precision_at_1
+      value: 33.793
+    - type: precision_at_10
+      value: 8.312999999999999
+    - type: precision_at_100
+      value: 1.191
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 18.662
+    - type: precision_at_5
+      value: 13.668
+    - type: recall_at_1
+      value: 29.182999999999996
+    - type: recall_at_10
+      value: 64.14999999999999
+    - type: recall_at_100
+      value: 86.533
+    - type: recall_at_1000
+      value: 96.492
+    - type: recall_at_3
+      value: 45.7
+    - type: recall_at_5
+      value: 54.330999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackGisRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 5003b3064772da1887988e05400cf3806fe491f2
+    metrics:
+    - type: map_at_1
+      value: 24.389
+    - type: map_at_10
+      value: 33.858
+    - type: map_at_100
+      value: 35.081
+    - type: map_at_1000
+      value: 35.161
+    - type: map_at_3
+      value: 30.793
+    - type: map_at_5
+      value: 32.336
+    - type: mrr_at_1
+      value: 27.006000000000004
+    - type: mrr_at_10
+      value: 36.378
+    - type: mrr_at_100
+      value: 37.345
+    - type: mrr_at_1000
+      value: 37.405
+    - type: mrr_at_3
+      value: 33.578
+    - type: mrr_at_5
+      value: 34.991
+    - type: ndcg_at_1
+      value: 27.006000000000004
+    - type: ndcg_at_10
+      value: 39.612
+    - type: ndcg_at_100
+      value: 45.216
+    - type: ndcg_at_1000
+      value: 47.12
+    - type: ndcg_at_3
+      value: 33.566
+    - type: ndcg_at_5
+      value: 36.105
+    - type: precision_at_1
+      value: 27.006000000000004
+    - type: precision_at_10
+      value: 6.372999999999999
+    - type: precision_at_100
+      value: 0.968
+    - type: precision_at_1000
+      value: 0.11800000000000001
+    - type: precision_at_3
+      value: 14.501
+    - type: precision_at_5
+      value: 10.169
+    - type: recall_at_1
+      value: 24.389
+    - type: recall_at_10
+      value: 55.131
+    - type: recall_at_100
+      value: 80.315
+    - type: recall_at_1000
+      value: 94.284
+    - type: recall_at_3
+      value: 38.643
+    - type: recall_at_5
+      value: 44.725
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackMathematicaRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
+    metrics:
+    - type: map_at_1
+      value: 15.845999999999998
+    - type: map_at_10
+      value: 25.019000000000002
+    - type: map_at_100
+      value: 26.478
+    - type: map_at_1000
+      value: 26.598
+    - type: map_at_3
+      value: 21.595
+    - type: map_at_5
+      value: 23.335
+    - type: mrr_at_1
+      value: 20.274
+    - type: mrr_at_10
+      value: 29.221000000000004
+    - type: mrr_at_100
+      value: 30.354999999999997
+    - type: mrr_at_1000
+      value: 30.419
+    - type: mrr_at_3
+      value: 26.161
+    - type: mrr_at_5
+      value: 27.61
+    - type: ndcg_at_1
+      value: 20.274
+    - type: ndcg_at_10
+      value: 31.014000000000003
+    - type: ndcg_at_100
+      value: 37.699
+    - type: ndcg_at_1000
+      value: 40.363
+    - type: ndcg_at_3
+      value: 24.701999999999998
+    - type: ndcg_at_5
+      value: 27.261999999999997
+    - type: precision_at_1
+      value: 20.274
+    - type: precision_at_10
+      value: 6.219
+    - type: precision_at_100
+      value: 1.101
+    - type: precision_at_1000
+      value: 0.146
+    - type: precision_at_3
+      value: 12.231
+    - type: precision_at_5
+      value: 9.129
+    - type: recall_at_1
+      value: 15.845999999999998
+    - type: recall_at_10
+      value: 45.358
+    - type: recall_at_100
+      value: 74.232
+    - type: recall_at_1000
+      value: 92.985
+    - type: recall_at_3
+      value: 28.050000000000004
+    - type: recall_at_5
+      value: 34.588
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackPhysicsRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
+    metrics:
+    - type: map_at_1
+      value: 33.808
+    - type: map_at_10
+      value: 46.86
+    - type: map_at_100
+      value: 48.237
+    - type: map_at_1000
+      value: 48.331
+    - type: map_at_3
+      value: 42.784
+    - type: map_at_5
+      value: 45.015
+    - type: mrr_at_1
+      value: 41.771
+    - type: mrr_at_10
+      value: 52.35300000000001
+    - type: mrr_at_100
+      value: 53.102000000000004
+    - type: mrr_at_1000
+      value: 53.132999999999996
+    - type: mrr_at_3
+      value: 49.663000000000004
+    - type: mrr_at_5
+      value: 51.27
+    - type: ndcg_at_1
+      value: 41.771
+    - type: ndcg_at_10
+      value: 53.562
+    - type: ndcg_at_100
+      value: 58.809999999999995
+    - type: ndcg_at_1000
+      value: 60.23
+    - type: ndcg_at_3
+      value: 47.514
+    - type: ndcg_at_5
+      value: 50.358999999999995
+    - type: precision_at_1
+      value: 41.771
+    - type: precision_at_10
+      value: 10.038
+    - type: precision_at_100
+      value: 1.473
+    - type: precision_at_1000
+      value: 0.17600000000000002
+    - type: precision_at_3
+      value: 22.875
+    - type: precision_at_5
+      value: 16.477
+    - type: recall_at_1
+      value: 33.808
+    - type: recall_at_10
+      value: 67.721
+    - type: recall_at_100
+      value: 89.261
+    - type: recall_at_1000
+      value: 98.042
+    - type: recall_at_3
+      value: 50.807
+    - type: recall_at_5
+      value: 58.162000000000006
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackProgrammersRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
+    metrics:
+    - type: map_at_1
+      value: 28.105000000000004
+    - type: map_at_10
+      value: 40.354
+    - type: map_at_100
+      value: 41.921
+    - type: map_at_1000
+      value: 42.021
+    - type: map_at_3
+      value: 36.532
+    - type: map_at_5
+      value: 38.671
+    - type: mrr_at_1
+      value: 34.475
+    - type: mrr_at_10
+      value: 45.342
+    - type: mrr_at_100
+      value: 46.300000000000004
+    - type: mrr_at_1000
+      value: 46.343
+    - type: mrr_at_3
+      value: 42.637
+    - type: mrr_at_5
+      value: 44.207
+    - type: ndcg_at_1
+      value: 34.475
+    - type: ndcg_at_10
+      value: 46.945
+    - type: ndcg_at_100
+      value: 52.939
+    - type: ndcg_at_1000
+      value: 54.645999999999994
+    - type: ndcg_at_3
+      value: 41.065000000000005
+    - type: ndcg_at_5
+      value: 43.832
+    - type: precision_at_1
+      value: 34.475
+    - type: precision_at_10
+      value: 8.892999999999999
+    - type: precision_at_100
+      value: 1.377
+    - type: precision_at_1000
+      value: 0.17099999999999999
+    - type: precision_at_3
+      value: 20.091
+    - type: precision_at_5
+      value: 14.452000000000002
+    - type: recall_at_1
+      value: 28.105000000000004
+    - type: recall_at_10
+      value: 61.253
+    - type: recall_at_100
+      value: 85.92
+    - type: recall_at_1000
+      value: 96.799
+    - type: recall_at_3
+      value: 45.094
+    - type: recall_at_5
+      value: 52.455
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+    metrics:
+    - type: map_at_1
+      value: 24.613833333333332
+    - type: map_at_10
+      value: 34.763
+    - type: map_at_100
+      value: 36.17066666666667
+    - type: map_at_1000
+      value: 36.2905
+    - type: map_at_3
+      value: 31.53541666666666
+    - type: map_at_5
+      value: 33.29216666666667
+    - type: mrr_at_1
+      value: 29.48725
+    - type: mrr_at_10
+      value: 38.92066666666667
+    - type: mrr_at_100
+      value: 39.88725000000001
+    - type: mrr_at_1000
+      value: 39.9435
+    - type: mrr_at_3
+      value: 36.284083333333335
+    - type: mrr_at_5
+      value: 37.73941666666667
+    - type: ndcg_at_1
+      value: 29.48725
+    - type: ndcg_at_10
+      value: 40.635083333333334
+    - type: ndcg_at_100
+      value: 46.479416666666665
+    - type: ndcg_at_1000
+      value: 48.63308333333334
+    - type: ndcg_at_3
+      value: 35.19483333333333
+    - type: ndcg_at_5
+      value: 37.68016666666667
+    - type: precision_at_1
+      value: 29.48725
+    - type: precision_at_10
+      value: 7.406499999999998
+    - type: precision_at_100
+      value: 1.2225833333333334
+    - type: precision_at_1000
+      value: 0.16108333333333336
+    - type: precision_at_3
+      value: 16.53375
+    - type: precision_at_5
+      value: 11.919416666666665
+    - type: recall_at_1
+      value: 24.613833333333332
+    - type: recall_at_10
+      value: 53.91766666666666
+    - type: recall_at_100
+      value: 79.18
+    - type: recall_at_1000
+      value: 93.85133333333333
+    - type: recall_at_3
+      value: 38.866166666666665
+    - type: recall_at_5
+      value: 45.21275000000001
+    - type: map_at_1
+      value: 12.328999999999999
+    - type: map_at_10
+      value: 20.078
+    - type: map_at_100
+      value: 21.166999999999998
+    - type: map_at_1000
+      value: 21.308
+    - type: map_at_3
+      value: 17.702
+    - type: map_at_5
+      value: 18.725
+    - type: mrr_at_1
+      value: 13.678
+    - type: mrr_at_10
+      value: 21.859
+    - type: mrr_at_100
+      value: 22.816
+    - type: mrr_at_1000
+      value: 22.926
+    - type: mrr_at_3
+      value: 19.378
+    - type: mrr_at_5
+      value: 20.385
+    - type: ndcg_at_1
+      value: 13.678
+    - type: ndcg_at_10
+      value: 24.993000000000002
+    - type: ndcg_at_100
+      value: 30.464999999999996
+    - type: ndcg_at_1000
+      value: 33.916000000000004
+    - type: ndcg_at_3
+      value: 19.966
+    - type: ndcg_at_5
+      value: 21.712999999999997
+    - type: precision_at_1
+      value: 13.678
+    - type: precision_at_10
+      value: 4.473
+    - type: precision_at_100
+      value: 0.784
+    - type: precision_at_1000
+      value: 0.116
+    - type: precision_at_3
+      value: 9.181000000000001
+    - type: precision_at_5
+      value: 6.506
+    - type: recall_at_1
+      value: 12.328999999999999
+    - type: recall_at_10
+      value: 38.592
+    - type: recall_at_100
+      value: 63.817
+    - type: recall_at_1000
+      value: 89.67500000000001
+    - type: recall_at_3
+      value: 24.726
+    - type: recall_at_5
+      value: 28.959000000000003
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackStatsRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
+    metrics:
+    - type: map_at_1
+      value: 25.106
+    - type: map_at_10
+      value: 33.367999999999995
+    - type: map_at_100
+      value: 34.586
+    - type: map_at_1000
+      value: 34.681
+    - type: map_at_3
+      value: 31.022
+    - type: map_at_5
+      value: 32.548
+    - type: mrr_at_1
+      value: 28.374
+    - type: mrr_at_10
+      value: 36.521
+    - type: mrr_at_100
+      value: 37.55
+    - type: mrr_at_1000
+      value: 37.614999999999995
+    - type: mrr_at_3
+      value: 34.509
+    - type: mrr_at_5
+      value: 35.836
+    - type: ndcg_at_1
+      value: 28.374
+    - type: ndcg_at_10
+      value: 37.893
+    - type: ndcg_at_100
+      value: 43.694
+    - type: ndcg_at_1000
+      value: 46.001999999999995
+    - type: ndcg_at_3
+      value: 33.825
+    - type: ndcg_at_5
+      value: 36.201
+    - type: precision_at_1
+      value: 28.374
+    - type: precision_at_10
+      value: 5.966
+    - type: precision_at_100
+      value: 0.9650000000000001
+    - type: precision_at_1000
+      value: 0.124
+    - type: precision_at_3
+      value: 14.774999999999999
+    - type: precision_at_5
+      value: 10.459999999999999
+    - type: recall_at_1
+      value: 25.106
+    - type: recall_at_10
+      value: 48.607
+    - type: recall_at_100
+      value: 74.66000000000001
+    - type: recall_at_1000
+      value: 91.562
+    - type: recall_at_3
+      value: 37.669999999999995
+    - type: recall_at_5
+      value: 43.484
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackTexRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 46989137a86843e03a6195de44b09deda022eec7
+    metrics:
+    - type: map_at_1
+      value: 13.755
+    - type: map_at_10
+      value: 20.756
+    - type: map_at_100
+      value: 22.05
+    - type: map_at_1000
+      value: 22.201
+    - type: map_at_3
+      value: 18.243000000000002
+    - type: map_at_5
+      value: 19.512
+    - type: mrr_at_1
+      value: 16.93
+    - type: mrr_at_10
+      value: 24.276
+    - type: mrr_at_100
+      value: 25.349
+    - type: mrr_at_1000
+      value: 25.441000000000003
+    - type: mrr_at_3
+      value: 21.897
+    - type: mrr_at_5
+      value: 23.134
+    - type: ndcg_at_1
+      value: 16.93
+    - type: ndcg_at_10
+      value: 25.508999999999997
+    - type: ndcg_at_100
+      value: 31.777
+    - type: ndcg_at_1000
+      value: 35.112
+    - type: ndcg_at_3
+      value: 20.896
+    - type: ndcg_at_5
+      value: 22.857
+    - type: precision_at_1
+      value: 16.93
+    - type: precision_at_10
+      value: 4.972
+    - type: precision_at_100
+      value: 0.963
+    - type: precision_at_1000
+      value: 0.145
+    - type: precision_at_3
+      value: 10.14
+    - type: precision_at_5
+      value: 7.536
+    - type: recall_at_1
+      value: 13.755
+    - type: recall_at_10
+      value: 36.46
+    - type: recall_at_100
+      value: 64.786
+    - type: recall_at_1000
+      value: 88.287
+    - type: recall_at_3
+      value: 23.681
+    - type: recall_at_5
+      value: 28.615000000000002
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackUnixRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
+    metrics:
+    - type: map_at_1
+      value: 26.99
+    - type: map_at_10
+      value: 38.009
+    - type: map_at_100
+      value: 39.384
+    - type: map_at_1000
+      value: 39.481
+    - type: map_at_3
+      value: 34.593
+    - type: map_at_5
+      value: 36.449999999999996
+    - type: mrr_at_1
+      value: 31.81
+    - type: mrr_at_10
+      value: 41.943000000000005
+    - type: mrr_at_100
+      value: 42.914
+    - type: mrr_at_1000
+      value: 42.962
+    - type: mrr_at_3
+      value: 39.179
+    - type: mrr_at_5
+      value: 40.798
+    - type: ndcg_at_1
+      value: 31.81
+    - type: ndcg_at_10
+      value: 44.086
+    - type: ndcg_at_100
+      value: 50.026
+    - type: ndcg_at_1000
+      value: 51.903999999999996
+    - type: ndcg_at_3
+      value: 38.23
+    - type: ndcg_at_5
+      value: 40.926
+    - type: precision_at_1
+      value: 31.81
+    - type: precision_at_10
+      value: 7.761
+    - type: precision_at_100
+      value: 1.205
+    - type: precision_at_1000
+      value: 0.148
+    - type: precision_at_3
+      value: 17.537
+    - type: precision_at_5
+      value: 12.649
+    - type: recall_at_1
+      value: 26.99
+    - type: recall_at_10
+      value: 58.467
+    - type: recall_at_100
+      value: 83.93
+    - type: recall_at_1000
+      value: 96.452
+    - type: recall_at_3
+      value: 42.685
+    - type: recall_at_5
+      value: 49.341
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackWebmastersRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
+    metrics:
+    - type: map_at_1
+      value: 25.312
+    - type: map_at_10
+      value: 35.788
+    - type: map_at_100
+      value: 37.616
+    - type: map_at_1000
+      value: 37.86
+    - type: map_at_3
+      value: 32.422000000000004
+    - type: map_at_5
+      value: 34.585
+    - type: mrr_at_1
+      value: 30.631999999999998
+    - type: mrr_at_10
+      value: 40.604
+    - type: mrr_at_100
+      value: 41.745
+    - type: mrr_at_1000
+      value: 41.788
+    - type: mrr_at_3
+      value: 37.582
+    - type: mrr_at_5
+      value: 39.499
+    - type: ndcg_at_1
+      value: 30.631999999999998
+    - type: ndcg_at_10
+      value: 42.129
+    - type: ndcg_at_100
+      value: 48.943
+    - type: ndcg_at_1000
+      value: 51.089
+    - type: ndcg_at_3
+      value: 36.658
+    - type: ndcg_at_5
+      value: 39.818999999999996
+    - type: precision_at_1
+      value: 30.631999999999998
+    - type: precision_at_10
+      value: 7.904999999999999
+    - type: precision_at_100
+      value: 1.664
+    - type: precision_at_1000
+      value: 0.256
+    - type: precision_at_3
+      value: 16.996
+    - type: precision_at_5
+      value: 12.727
+    - type: recall_at_1
+      value: 25.312
+    - type: recall_at_10
+      value: 54.886
+    - type: recall_at_100
+      value: 84.155
+    - type: recall_at_1000
+      value: 96.956
+    - type: recall_at_3
+      value: 40.232
+    - type: recall_at_5
+      value: 48.204
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB ClimateFEVER
+      type: mteb/climate-fever
+      config: default
+      split: test
+      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
+    metrics:
+    - type: map_at_1
+      value: 19.147
+    - type: map_at_10
+      value: 33.509
+    - type: map_at_100
+      value: 35.573
+    - type: map_at_1000
+      value: 35.769
+    - type: map_at_3
+      value: 27.983999999999998
+    - type: map_at_5
+      value: 31.012
+    - type: mrr_at_1
+      value: 43.844
+    - type: mrr_at_10
+      value: 56.24
+    - type: mrr_at_100
+      value: 56.801
+    - type: mrr_at_1000
+      value: 56.826
+    - type: mrr_at_3
+      value: 53.290000000000006
+    - type: mrr_at_5
+      value: 55.13
+    - type: ndcg_at_1
+      value: 43.844
+    - type: ndcg_at_10
+      value: 43.996
+    - type: ndcg_at_100
+      value: 50.965
+    - type: ndcg_at_1000
+      value: 53.927
+    - type: ndcg_at_3
+      value: 37.263000000000005
+    - type: ndcg_at_5
+      value: 39.553
+    - type: precision_at_1
+      value: 43.844
+    - type: precision_at_10
+      value: 13.687
+    - type: precision_at_100
+      value: 2.139
+    - type: precision_at_1000
+      value: 0.269
+    - type: precision_at_3
+      value: 28.122000000000003
+    - type: precision_at_5
+      value: 21.303
+    - type: recall_at_1
+      value: 19.147
+    - type: recall_at_10
+      value: 50.449999999999996
+    - type: recall_at_100
+      value: 74.00099999999999
+    - type: recall_at_1000
+      value: 90.098
+    - type: recall_at_3
+      value: 33.343
+    - type: recall_at_5
+      value: 40.744
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB DBPedia
+      type: mteb/dbpedia
+      config: default
+      split: test
+      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
+    metrics:
+    - type: map_at_1
+      value: 8.773
+    - type: map_at_10
+      value: 21.172
+    - type: map_at_100
+      value: 30.244
+    - type: map_at_1000
+      value: 32.127
+    - type: map_at_3
+      value: 14.510000000000002
+    - type: map_at_5
+      value: 17.483
+    - type: mrr_at_1
+      value: 68.25
+    - type: mrr_at_10
+      value: 77.33
+    - type: mrr_at_100
+      value: 77.529
+    - type: mrr_at_1000
+      value: 77.536
+    - type: mrr_at_3
+      value: 75.708
+    - type: mrr_at_5
+      value: 76.72099999999999
+    - type: ndcg_at_1
+      value: 60.0
+    - type: ndcg_at_10
+      value: 48.045
+    - type: ndcg_at_100
+      value: 51.620999999999995
+    - type: ndcg_at_1000
+      value: 58.843999999999994
+    - type: ndcg_at_3
+      value: 52.922000000000004
+    - type: ndcg_at_5
+      value: 50.27
+    - type: precision_at_1
+      value: 68.25
+    - type: precision_at_10
+      value: 37.625
+    - type: precision_at_100
+      value: 11.774999999999999
+    - type: precision_at_1000
+      value: 2.395
+    - type: precision_at_3
+      value: 55.25
+    - type: precision_at_5
+      value: 47.599999999999994
+    - type: recall_at_1
+      value: 8.773
+    - type: recall_at_10
+      value: 27.332
+    - type: recall_at_100
+      value: 55.48499999999999
+    - type: recall_at_1000
+      value: 79.886
+    - type: recall_at_3
+      value: 15.823
+    - type: recall_at_5
+      value: 20.523
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB EmotionClassification
+      type: mteb/emotion
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 54.52999999999999
+    - type: f1
+      value: 47.396628088963645
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB FEVER
+      type: mteb/fever
+      config: default
+      split: test
+      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
+    metrics:
+    - type: map_at_1
+      value: 85.397
+    - type: map_at_10
+      value: 90.917
+    - type: map_at_100
+      value: 91.109
+    - type: map_at_1000
+      value: 91.121
+    - type: map_at_3
+      value: 90.045
+    - type: map_at_5
+      value: 90.602
+    - type: mrr_at_1
+      value: 92.00399999999999
+    - type: mrr_at_10
+      value: 95.39999999999999
+    - type: mrr_at_100
+      value: 95.41
+    - type: mrr_at_1000
+      value: 95.41
+    - type: mrr_at_3
+      value: 95.165
+    - type: mrr_at_5
+      value: 95.348
+    - type: ndcg_at_1
+      value: 92.00399999999999
+    - type: ndcg_at_10
+      value: 93.345
+    - type: ndcg_at_100
+      value: 93.934
+    - type: ndcg_at_1000
+      value: 94.108
+    - type: ndcg_at_3
+      value: 92.32000000000001
+    - type: ndcg_at_5
+      value: 92.899
+    - type: precision_at_1
+      value: 92.00399999999999
+    - type: precision_at_10
+      value: 10.839
+    - type: precision_at_100
+      value: 1.1440000000000001
+    - type: precision_at_1000
+      value: 0.117
+    - type: precision_at_3
+      value: 34.298
+    - type: precision_at_5
+      value: 21.128
+    - type: recall_at_1
+      value: 85.397
+    - type: recall_at_10
+      value: 96.375
+    - type: recall_at_100
+      value: 98.518
+    - type: recall_at_1000
+      value: 99.515
+    - type: recall_at_3
+      value: 93.59100000000001
+    - type: recall_at_5
+      value: 95.134
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB FiQA2018
+      type: mteb/fiqa
+      config: default
+      split: test
+      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
+    metrics:
+    - type: map_at_1
+      value: 27.36
+    - type: map_at_10
+      value: 46.847
+    - type: map_at_100
+      value: 49.259
+    - type: map_at_1000
+      value: 49.389
+    - type: map_at_3
+      value: 41.095
+    - type: map_at_5
+      value: 44.084
+    - type: mrr_at_1
+      value: 51.852
+    - type: mrr_at_10
+      value: 61.67
+    - type: mrr_at_100
+      value: 62.395999999999994
+    - type: mrr_at_1000
+      value: 62.414
+    - type: mrr_at_3
+      value: 59.465
+    - type: mrr_at_5
+      value: 60.584
+    - type: ndcg_at_1
+      value: 51.852
+    - type: ndcg_at_10
+      value: 55.311
+    - type: ndcg_at_100
+      value: 62.6
+    - type: ndcg_at_1000
+      value: 64.206
+    - type: ndcg_at_3
+      value: 51.159
+    - type: ndcg_at_5
+      value: 52.038
+    - type: precision_at_1
+      value: 51.852
+    - type: precision_at_10
+      value: 15.370000000000001
+    - type: precision_at_100
+      value: 2.282
+    - type: precision_at_1000
+      value: 0.258
+    - type: precision_at_3
+      value: 34.721999999999994
+    - type: precision_at_5
+      value: 24.846
+    - type: recall_at_1
+      value: 27.36
+    - type: recall_at_10
+      value: 63.932
+    - type: recall_at_100
+      value: 89.824
+    - type: recall_at_1000
+      value: 98.556
+    - type: recall_at_3
+      value: 47.227999999999994
+    - type: recall_at_5
+      value: 53.724000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB HotpotQA
+      type: mteb/hotpotqa
+      config: default
+      split: test
+      revision: ab518f4d6fcca38d87c25209f94beba119d02014
+    metrics:
+    - type: map_at_1
+      value: 40.655
+    - type: map_at_10
+      value: 63.824999999999996
+    - type: map_at_100
+      value: 64.793
+    - type: map_at_1000
+      value: 64.848
+    - type: map_at_3
+      value: 60.221000000000004
+    - type: map_at_5
+      value: 62.474
+    - type: mrr_at_1
+      value: 81.31
+    - type: mrr_at_10
+      value: 86.509
+    - type: mrr_at_100
+      value: 86.677
+    - type: mrr_at_1000
+      value: 86.682
+    - type: mrr_at_3
+      value: 85.717
+    - type: mrr_at_5
+      value: 86.21
+    - type: ndcg_at_1
+      value: 81.31
+    - type: ndcg_at_10
+      value: 72.251
+    - type: ndcg_at_100
+      value: 75.536
+    - type: ndcg_at_1000
+      value: 76.558
+    - type: ndcg_at_3
+      value: 67.291
+    - type: ndcg_at_5
+      value: 70.045
+    - type: precision_at_1
+      value: 81.31
+    - type: precision_at_10
+      value: 15.082999999999998
+    - type: precision_at_100
+      value: 1.764
+    - type: precision_at_1000
+      value: 0.19
+    - type: precision_at_3
+      value: 42.971
+    - type: precision_at_5
+      value: 27.956999999999997
+    - type: recall_at_1
+      value: 40.655
+    - type: recall_at_10
+      value: 75.41499999999999
+    - type: recall_at_100
+      value: 88.224
+    - type: recall_at_1000
+      value: 94.943
+    - type: recall_at_3
+      value: 64.456
+    - type: recall_at_5
+      value: 69.892
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB ImdbClassification
+      type: mteb/imdb
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 95.58120000000001
+    - type: ap
+      value: 93.0407063004784
+    - type: f1
+      value: 95.57849992996822
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MSMARCO
+      type: mteb/msmarco
+      config: default
+      split: dev
+      revision: c5a29a104738b98a9e76336939199e264163d4a0
+    metrics:
+    - type: map_at_1
+      value: 22.031
+    - type: map_at_10
+      value: 34.628
+    - type: map_at_100
+      value: 35.833
+    - type: map_at_1000
+      value: 35.881
+    - type: map_at_3
+      value: 30.619000000000003
+    - type: map_at_5
+      value: 32.982
+    - type: mrr_at_1
+      value: 22.736
+    - type: mrr_at_10
+      value: 35.24
+    - type: mrr_at_100
+      value: 36.381
+    - type: mrr_at_1000
+      value: 36.424
+    - type: mrr_at_3
+      value: 31.287
+    - type: mrr_at_5
+      value: 33.617000000000004
+    - type: ndcg_at_1
+      value: 22.736
+    - type: ndcg_at_10
+      value: 41.681000000000004
+    - type: ndcg_at_100
+      value: 47.371
+    - type: ndcg_at_1000
+      value: 48.555
+    - type: ndcg_at_3
+      value: 33.553
+    - type: ndcg_at_5
+      value: 37.771
+    - type: precision_at_1
+      value: 22.736
+    - type: precision_at_10
+      value: 6.625
+    - type: precision_at_100
+      value: 0.9450000000000001
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_3
+      value: 14.331
+    - type: precision_at_5
+      value: 10.734
+    - type: recall_at_1
+      value: 22.031
+    - type: recall_at_10
+      value: 63.378
+    - type: recall_at_100
+      value: 89.47699999999999
+    - type: recall_at_1000
+      value: 98.48400000000001
+    - type: recall_at_3
+      value: 41.388000000000005
+    - type: recall_at_5
+      value: 51.522999999999996
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPDomainClassification (en)
+      type: mteb/mtop_domain
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 95.75239398084815
+    - type: f1
+      value: 95.51228043205194
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPIntentClassification (en)
+      type: mteb/mtop_intent
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 84.25900592795259
+    - type: f1
+      value: 62.14790420114562
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveIntentClassification (en)
+      type: mteb/amazon_massive_intent
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 78.47007397444519
+    - type: f1
+      value: 76.92133583932912
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveScenarioClassification (en)
+      type: mteb/amazon_massive_scenario
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 78.19098856758575
+    - type: f1
+      value: 78.10820805879119
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MedrxivClusteringP2P
+      type: mteb/medrxiv-clustering-p2p
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 44.37013684222983
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MedrxivClusteringS2S
+      type: mteb/medrxiv-clustering-s2s
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 42.003012591979704
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB MindSmallReranking
+      type: mteb/mind_small
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 32.70743071063257
+    - type: mrr
+      value: 33.938337390083994
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB NFCorpus
+      type: mteb/nfcorpus
+      config: default
+      split: test
+      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
+    metrics:
+    - type: map_at_1
+      value: 6.369
+    - type: map_at_10
+      value: 14.313
+    - type: map_at_100
+      value: 18.329
+    - type: map_at_1000
+      value: 20.017
+    - type: map_at_3
+      value: 10.257
+    - type: map_at_5
+      value: 12.264999999999999
+    - type: mrr_at_1
+      value: 49.536
+    - type: mrr_at_10
+      value: 58.464000000000006
+    - type: mrr_at_100
+      value: 59.016000000000005
+    - type: mrr_at_1000
+      value: 59.053
+    - type: mrr_at_3
+      value: 56.294999999999995
+    - type: mrr_at_5
+      value: 57.766
+    - type: ndcg_at_1
+      value: 47.678
+    - type: ndcg_at_10
+      value: 38.246
+    - type: ndcg_at_100
+      value: 35.370000000000005
+    - type: ndcg_at_1000
+      value: 44.517
+    - type: ndcg_at_3
+      value: 43.368
+    - type: ndcg_at_5
+      value: 41.892
+    - type: precision_at_1
+      value: 49.536
+    - type: precision_at_10
+      value: 28.235
+    - type: precision_at_100
+      value: 9.014999999999999
+    - type: precision_at_1000
+      value: 2.257
+    - type: precision_at_3
+      value: 40.557
+    - type: precision_at_5
+      value: 36.409000000000006
+    - type: recall_at_1
+      value: 6.369
+    - type: recall_at_10
+      value: 19.195999999999998
+    - type: recall_at_100
+      value: 37.042
+    - type: recall_at_1000
+      value: 69.203
+    - type: recall_at_3
+      value: 11.564
+    - type: recall_at_5
+      value: 15.264
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB NQ
+      type: mteb/nq
+      config: default
+      split: test
+      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
+    metrics:
+    - type: map_at_1
+      value: 39.323
+    - type: map_at_10
+      value: 54.608999999999995
+    - type: map_at_100
+      value: 55.523
+    - type: map_at_1000
+      value: 55.544000000000004
+    - type: map_at_3
+      value: 50.580000000000005
+    - type: map_at_5
+      value: 53.064
+    - type: mrr_at_1
+      value: 44.263999999999996
+    - type: mrr_at_10
+      value: 57.416
+    - type: mrr_at_100
+      value: 58.037000000000006
+    - type: mrr_at_1000
+      value: 58.05200000000001
+    - type: mrr_at_3
+      value: 54.330999999999996
+    - type: mrr_at_5
+      value: 56.302
+    - type: ndcg_at_1
+      value: 44.263999999999996
+    - type: ndcg_at_10
+      value: 61.785999999999994
+    - type: ndcg_at_100
+      value: 65.40599999999999
+    - type: ndcg_at_1000
+      value: 65.859
+    - type: ndcg_at_3
+      value: 54.518
+    - type: ndcg_at_5
+      value: 58.53699999999999
+    - type: precision_at_1
+      value: 44.263999999999996
+    - type: precision_at_10
+      value: 9.652
+    - type: precision_at_100
+      value: 1.169
+    - type: precision_at_1000
+      value: 0.121
+    - type: precision_at_3
+      value: 24.15
+    - type: precision_at_5
+      value: 16.848
+    - type: recall_at_1
+      value: 39.323
+    - type: recall_at_10
+      value: 80.663
+    - type: recall_at_100
+      value: 96.072
+    - type: recall_at_1000
+      value: 99.37700000000001
+    - type: recall_at_3
+      value: 62.23
+    - type: recall_at_5
+      value: 71.379
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB QuoraRetrieval
+      type: mteb/quora
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 72.02499999999999
+    - type: map_at_10
+      value: 86.14500000000001
+    - type: map_at_100
+      value: 86.764
+    - type: map_at_1000
+      value: 86.776
+    - type: map_at_3
+      value: 83.249
+    - type: map_at_5
+      value: 85.083
+    - type: mrr_at_1
+      value: 82.83
+    - type: mrr_at_10
+      value: 88.70599999999999
+    - type: mrr_at_100
+      value: 88.791
+    - type: mrr_at_1000
+      value: 88.791
+    - type: mrr_at_3
+      value: 87.815
+    - type: mrr_at_5
+      value: 88.435
+    - type: ndcg_at_1
+      value: 82.84
+    - type: ndcg_at_10
+      value: 89.61200000000001
+    - type: ndcg_at_100
+      value: 90.693
+    - type: ndcg_at_1000
+      value: 90.752
+    - type: ndcg_at_3
+      value: 86.96199999999999
+    - type: ndcg_at_5
+      value: 88.454
+    - type: precision_at_1
+      value: 82.84
+    - type: precision_at_10
+      value: 13.600000000000001
+    - type: precision_at_100
+      value: 1.543
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 38.092999999999996
+    - type: precision_at_5
+      value: 25.024
+    - type: recall_at_1
+      value: 72.02499999999999
+    - type: recall_at_10
+      value: 96.21600000000001
+    - type: recall_at_100
+      value: 99.76
+    - type: recall_at_1000
+      value: 99.996
+    - type: recall_at_3
+      value: 88.57000000000001
+    - type: recall_at_5
+      value: 92.814
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB RedditClustering
+      type: mteb/reddit-clustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 73.37297191949929
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB RedditClusteringP2P
+      type: mteb/reddit-clustering-p2p
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 72.50752304246946
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SCIDOCS
+      type: mteb/scidocs
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 6.4479999999999995
+    - type: map_at_10
+      value: 17.268
+    - type: map_at_100
+      value: 20.502000000000002
+    - type: map_at_1000
+      value: 20.904
+    - type: map_at_3
+      value: 11.951
+    - type: map_at_5
+      value: 14.494000000000002
+    - type: mrr_at_1
+      value: 31.900000000000002
+    - type: mrr_at_10
+      value: 45.084999999999994
+    - type: mrr_at_100
+      value: 46.145
+    - type: mrr_at_1000
+      value: 46.164
+    - type: mrr_at_3
+      value: 41.6
+    - type: mrr_at_5
+      value: 43.76
+    - type: ndcg_at_1
+      value: 31.900000000000002
+    - type: ndcg_at_10
+      value: 27.694000000000003
+    - type: ndcg_at_100
+      value: 39.016
+    - type: ndcg_at_1000
+      value: 44.448
+    - type: ndcg_at_3
+      value: 26.279999999999998
+    - type: ndcg_at_5
+      value: 22.93
+    - type: precision_at_1
+      value: 31.900000000000002
+    - type: precision_at_10
+      value: 14.399999999999999
+    - type: precision_at_100
+      value: 3.082
+    - type: precision_at_1000
+      value: 0.436
+    - type: precision_at_3
+      value: 24.667
+    - type: precision_at_5
+      value: 20.200000000000003
+    - type: recall_at_1
+      value: 6.4479999999999995
+    - type: recall_at_10
+      value: 29.243000000000002
+    - type: recall_at_100
+      value: 62.547
+    - type: recall_at_1000
+      value: 88.40299999999999
+    - type: recall_at_3
+      value: 14.988000000000001
+    - type: recall_at_5
+      value: 20.485
+  - task:
+      type: STS
+    dataset:
+      name: MTEB SICK-R
+      type: mteb/sickr-sts
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.37839336866843
+    - type: cos_sim_spearman
+      value: 79.14737320486729
+    - type: euclidean_pearson
+      value: 78.74010870392799
+    - type: euclidean_spearman
+      value: 79.1472505448557
+    - type: manhattan_pearson
+      value: 78.76735626972086
+    - type: manhattan_spearman
+      value: 79.18509055331465
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS12
+      type: mteb/sts12-sts
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.98947740740309
+    - type: cos_sim_spearman
+      value: 76.52068694652895
+    - type: euclidean_pearson
+      value: 81.10952542010847
+    - type: euclidean_spearman
+      value: 76.52162808897668
+    - type: manhattan_pearson
+      value: 81.13752577872523
+    - type: manhattan_spearman
+      value: 76.55073892851847
+    - type: cos_sim_pearson
+      value: 84.99292517797305
+    - type: cos_sim_spearman
+      value: 76.52287451692155
+    - type: euclidean_pearson
+      value: 81.11616055544546
+    - type: euclidean_spearman
+      value: 76.525387473028
+    - type: manhattan_pearson
+      value: 81.14367598670032
+    - type: manhattan_spearman
+      value: 76.55571799438607
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS13
+      type: mteb/sts13-sts
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.14795728641734
+    - type: cos_sim_spearman
+      value: 88.62720469210905
+    - type: euclidean_pearson
+      value: 87.96160445129142
+    - type: euclidean_spearman
+      value: 88.62615925428736
+    - type: manhattan_pearson
+      value: 87.86760858379527
+    - type: manhattan_spearman
+      value: 88.5613166629411
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS14
+      type: mteb/sts14-sts
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.06444249948838
+    - type: cos_sim_spearman
+      value: 83.32346434965837
+    - type: euclidean_pearson
+      value: 83.86264166785146
+    - type: euclidean_spearman
+      value: 83.32323156068114
+    - type: manhattan_pearson
+      value: 83.87253909108084
+    - type: manhattan_spearman
+      value: 83.42760090819642
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS15
+      type: mteb/sts15-sts
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.00847937091636
+    - type: cos_sim_spearman
+      value: 87.50432670473445
+    - type: euclidean_pearson
+      value: 87.21611485565168
+    - type: euclidean_spearman
+      value: 87.50387351928698
+    - type: manhattan_pearson
+      value: 87.30690660623411
+    - type: manhattan_spearman
+      value: 87.61147161393255
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS16
+      type: mteb/sts16-sts
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.51456553517488
+    - type: cos_sim_spearman
+      value: 86.39208323626035
+    - type: euclidean_pearson
+      value: 85.74698473006475
+    - type: euclidean_spearman
+      value: 86.3892506146807
+    - type: manhattan_pearson
+      value: 85.77493611949014
+    - type: manhattan_spearman
+      value: 86.42961510735024
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS17 (en-en)
+      type: mteb/sts17-crosslingual-sts
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.63402051628222
+    - type: cos_sim_spearman
+      value: 87.78994504115502
+    - type: euclidean_pearson
+      value: 88.44861926968403
+    - type: euclidean_spearman
+      value: 87.80670473078185
+    - type: manhattan_pearson
+      value: 88.4773722010208
+    - type: manhattan_spearman
+      value: 87.85175600656768
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (en)
+      type: mteb/sts22-crosslingual-sts
+      config: en
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 65.9659729672951
+    - type: cos_sim_spearman
+      value: 66.39891735341361
+    - type: euclidean_pearson
+      value: 68.040150710449
+    - type: euclidean_spearman
+      value: 66.41777234484414
+    - type: manhattan_pearson
+      value: 68.16264809387305
+    - type: manhattan_spearman
+      value: 66.31608161700346
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSBenchmark
+      type: mteb/stsbenchmark-sts
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.91024857159385
+    - type: cos_sim_spearman
+      value: 87.35031011815016
+    - type: euclidean_pearson
+      value: 86.94569462996033
+    - type: euclidean_spearman
+      value: 87.34929703462852
+    - type: manhattan_pearson
+      value: 86.94404111225616
+    - type: manhattan_spearman
+      value: 87.37827218003393
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB SciDocsRR
+      type: mteb/scidocs-reranking
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 87.89077927002596
+    - type: mrr
+      value: 96.94650937297997
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SciFact
+      type: mteb/scifact
+      config: default
+      split: test
+      revision: 0228b52cf27578f30900b9e5271d331663a030d7
+    metrics:
+    - type: map_at_1
+      value: 57.994
+    - type: map_at_10
+      value: 70.07100000000001
+    - type: map_at_100
+      value: 70.578
+    - type: map_at_1000
+      value: 70.588
+    - type: map_at_3
+      value: 67.228
+    - type: map_at_5
+      value: 68.695
+    - type: mrr_at_1
+      value: 61.333000000000006
+    - type: mrr_at_10
+      value: 71.342
+    - type: mrr_at_100
+      value: 71.739
+    - type: mrr_at_1000
+      value: 71.75
+    - type: mrr_at_3
+      value: 69.389
+    - type: mrr_at_5
+      value: 70.322
+    - type: ndcg_at_1
+      value: 61.333000000000006
+    - type: ndcg_at_10
+      value: 75.312
+    - type: ndcg_at_100
+      value: 77.312
+    - type: ndcg_at_1000
+      value: 77.50200000000001
+    - type: ndcg_at_3
+      value: 70.72
+    - type: ndcg_at_5
+      value: 72.616
+    - type: precision_at_1
+      value: 61.333000000000006
+    - type: precision_at_10
+      value: 10.167
+    - type: precision_at_100
+      value: 1.117
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 28.111000000000004
+    - type: precision_at_5
+      value: 18.333
+    - type: recall_at_1
+      value: 57.994
+    - type: recall_at_10
+      value: 89.944
+    - type: recall_at_100
+      value: 98.667
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 77.694
+    - type: recall_at_5
+      value: 82.339
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB SprintDuplicateQuestions
+      type: mteb/sprintduplicatequestions-pairclassification
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.81485148514851
+    - type: cos_sim_ap
+      value: 95.99339654021689
+    - type: cos_sim_f1
+      value: 90.45971329708354
+    - type: cos_sim_precision
+      value: 89.44281524926686
+    - type: cos_sim_recall
+      value: 91.5
+    - type: dot_accuracy
+      value: 99.81485148514851
+    - type: dot_ap
+      value: 95.990792367539
+    - type: dot_f1
+      value: 90.54187192118228
+    - type: dot_precision
+      value: 89.2233009708738
+    - type: dot_recall
+      value: 91.9
+    - type: euclidean_accuracy
+      value: 99.81386138613861
+    - type: euclidean_ap
+      value: 95.99403827746491
+    - type: euclidean_f1
+      value: 90.45971329708354
+    - type: euclidean_precision
+      value: 89.44281524926686
+    - type: euclidean_recall
+      value: 91.5
+    - type: manhattan_accuracy
+      value: 99.81485148514851
+    - type: manhattan_ap
+      value: 96.06741547889861
+    - type: manhattan_f1
+      value: 90.55666003976144
+    - type: manhattan_precision
+      value: 90.01976284584981
+    - type: manhattan_recall
+      value: 91.10000000000001
+    - type: max_accuracy
+      value: 99.81485148514851
+    - type: max_ap
+      value: 96.06741547889861
+    - type: max_f1
+      value: 90.55666003976144
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB StackExchangeClustering
+      type: mteb/stackexchange-clustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 79.0667992003181
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB StackExchangeClusteringP2P
+      type: mteb/stackexchange-clustering-p2p
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 49.57086425048946
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB StackOverflowDupQuestions
+      type: mteb/stackoverflowdupquestions-reranking
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 53.929415255105894
+    - type: mrr
+      value: 54.93889790764791
+  - task:
+      type: Summarization
+    dataset:
+      name: MTEB SummEval
+      type: mteb/summeval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.050700527286658
+    - type: cos_sim_spearman
+      value: 31.46077656458546
+    - type: dot_pearson
+      value: 31.056448416258263
+    - type: dot_spearman
+      value: 31.435272601921042
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB TRECCOVID
+      type: mteb/trec-covid
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.23500000000000001
+    - type: map_at_10
+      value: 1.812
+    - type: map_at_100
+      value: 10.041
+    - type: map_at_1000
+      value: 24.095
+    - type: map_at_3
+      value: 0.643
+    - type: map_at_5
+      value: 1.0
+    - type: mrr_at_1
+      value: 86.0
+    - type: mrr_at_10
+      value: 92.0
+    - type: mrr_at_100
+      value: 92.0
+    - type: mrr_at_1000
+      value: 92.0
+    - type: mrr_at_3
+      value: 91.667
+    - type: mrr_at_5
+      value: 91.667
+    - type: ndcg_at_1
+      value: 79.0
+    - type: ndcg_at_10
+      value: 72.72
+    - type: ndcg_at_100
+      value: 55.82899999999999
+    - type: ndcg_at_1000
+      value: 50.72
+    - type: ndcg_at_3
+      value: 77.715
+    - type: ndcg_at_5
+      value: 75.036
+    - type: precision_at_1
+      value: 86.0
+    - type: precision_at_10
+      value: 77.60000000000001
+    - type: precision_at_100
+      value: 56.46
+    - type: precision_at_1000
+      value: 22.23
+    - type: precision_at_3
+      value: 82.667
+    - type: precision_at_5
+      value: 80.4
+    - type: recall_at_1
+      value: 0.23500000000000001
+    - type: recall_at_10
+      value: 2.046
+    - type: recall_at_100
+      value: 13.708
+    - type: recall_at_1000
+      value: 47.451
+    - type: recall_at_3
+      value: 0.6709999999999999
+    - type: recall_at_5
+      value: 1.078
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB Touche2020
+      type: mteb/touche2020
+      config: default
+      split: test
+      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
+    metrics:
+    - type: map_at_1
+      value: 2.252
+    - type: map_at_10
+      value: 7.958
+    - type: map_at_100
+      value: 12.293
+    - type: map_at_1000
+      value: 13.832
+    - type: map_at_3
+      value: 4.299
+    - type: map_at_5
+      value: 5.514
+    - type: mrr_at_1
+      value: 30.612000000000002
+    - type: mrr_at_10
+      value: 42.329
+    - type: mrr_at_100
+      value: 43.506
+    - type: mrr_at_1000
+      value: 43.506
+    - type: mrr_at_3
+      value: 38.775999999999996
+    - type: mrr_at_5
+      value: 39.592
+    - type: ndcg_at_1
+      value: 28.571
+    - type: ndcg_at_10
+      value: 20.301
+    - type: ndcg_at_100
+      value: 30.703999999999997
+    - type: ndcg_at_1000
+      value: 43.155
+    - type: ndcg_at_3
+      value: 22.738
+    - type: ndcg_at_5
+      value: 20.515
+    - type: precision_at_1
+      value: 30.612000000000002
+    - type: precision_at_10
+      value: 17.347
+    - type: precision_at_100
+      value: 6.327000000000001
+    - type: precision_at_1000
+      value: 1.443
+    - type: precision_at_3
+      value: 22.448999999999998
+    - type: precision_at_5
+      value: 19.184
+    - type: recall_at_1
+      value: 2.252
+    - type: recall_at_10
+      value: 13.206999999999999
+    - type: recall_at_100
+      value: 40.372
+    - type: recall_at_1000
+      value: 78.071
+    - type: recall_at_3
+      value: 5.189
+    - type: recall_at_5
+      value: 7.338
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB ToxicConversationsClassification
+      type: mteb/toxic_conversations_50k
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 78.75399999999999
+    - type: ap
+      value: 19.666483622175363
+    - type: f1
+      value: 61.575187470329176
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB TweetSentimentExtractionClassification
+      type: mteb/tweet_sentiment_extraction
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 66.00452744765137
+    - type: f1
+      value: 66.18291586829227
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB TwentyNewsgroupsClustering
+      type: mteb/twentynewsgroups-clustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 51.308747717084316
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB TwitterSemEval2015
+      type: mteb/twittersemeval2015-pairclassification
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 87.81069321094355
+    - type: cos_sim_ap
+      value: 79.3576921453847
+    - type: cos_sim_f1
+      value: 71.75811286328685
+    - type: cos_sim_precision
+      value: 70.89878959567345
+    - type: cos_sim_recall
+      value: 72.63852242744063
+    - type: dot_accuracy
+      value: 87.79877212850927
+    - type: dot_ap
+      value: 79.35550320857683
+    - type: dot_f1
+      value: 71.78153446033811
+    - type: dot_precision
+      value: 70.76923076923077
+    - type: dot_recall
+      value: 72.82321899736148
+    - type: euclidean_accuracy
+      value: 87.80473266972642
+    - type: euclidean_ap
+      value: 79.35792655436586
+    - type: euclidean_f1
+      value: 71.75672148264161
+    - type: euclidean_precision
+      value: 70.99690082644628
+    - type: euclidean_recall
+      value: 72.53298153034301
+    - type: manhattan_accuracy
+      value: 87.76300888120642
+    - type: manhattan_ap
+      value: 79.33615959143606
+    - type: manhattan_f1
+      value: 71.73219978746015
+    - type: manhattan_precision
+      value: 72.23113964686998
+    - type: manhattan_recall
+      value: 71.2401055408971
+    - type: max_accuracy
+      value: 87.81069321094355
+    - type: max_ap
+      value: 79.35792655436586
+    - type: max_f1
+      value: 71.78153446033811
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB TwitterURLCorpus
+      type: mteb/twitterurlcorpus-pairclassification
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.3778864439011
+    - type: cos_sim_ap
+      value: 86.79005637312795
+    - type: cos_sim_f1
+      value: 79.14617791685293
+    - type: cos_sim_precision
+      value: 76.66714780600462
+    - type: cos_sim_recall
+      value: 81.79088389282414
+    - type: dot_accuracy
+      value: 89.37206504443668
+    - type: dot_ap
+      value: 86.78770290102123
+    - type: dot_f1
+      value: 79.14741392159786
+    - type: dot_precision
+      value: 76.6897746967071
+    - type: dot_recall
+      value: 81.76778564829073
+    - type: euclidean_accuracy
+      value: 89.37594597741297
+    - type: euclidean_ap
+      value: 86.7900899669397
+    - type: euclidean_f1
+      value: 79.13920845898953
+    - type: euclidean_precision
+      value: 76.62028692956528
+    - type: euclidean_recall
+      value: 81.8293809670465
+    - type: manhattan_accuracy
+      value: 89.38758877634183
+    - type: manhattan_ap
+      value: 86.78862564973224
+    - type: manhattan_f1
+      value: 79.1130985653065
+    - type: manhattan_precision
+      value: 76.6592041597458
+    - type: manhattan_recall
+      value: 81.72928857406838
+    - type: max_accuracy
+      value: 89.38758877634183
+    - type: max_ap
+      value: 86.7900899669397
+    - type: max_f1
+      value: 79.14741392159786
+  - task:
+      type: STS
+    dataset:
+      name: MTEB AFQMC
+      type: C-MTEB/AFQMC
+      config: default
+      split: validation
+      revision: b44c3b011063adb25877c13823db83bb193913c4
+    metrics:
+    - type: cos_sim_pearson
+      value: 50.01571015887356
+    - type: cos_sim_spearman
+      value: 58.47419994907958
+    - type: euclidean_pearson
+      value: 55.63582004345212
+    - type: euclidean_spearman
+      value: 58.47514484211099
+    - type: manhattan_pearson
+      value: 55.58487268871911
+    - type: manhattan_spearman
+      value: 58.411916843600075
+  - task:
+      type: STS
+    dataset:
+      name: MTEB ATEC
+      type: C-MTEB/ATEC
+      config: default
+      split: test
+      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
+    metrics:
+    - type: cos_sim_pearson
+      value: 44.99231617937922
+    - type: cos_sim_spearman
+      value: 55.459227458516416
+    - type: euclidean_pearson
+      value: 52.98483376548224
+    - type: euclidean_spearman
+      value: 55.45938733128155
+    - type: manhattan_pearson
+      value: 52.946854805143964
+    - type: manhattan_spearman
+      value: 55.4272663113618
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonReviewsClassification (zh)
+      type: mteb/amazon_reviews_multi
+      config: zh
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 52.946000000000005
+    - type: f1
+      value: 49.299873931232725
+  - task:
+      type: STS
+    dataset:
+      name: MTEB BQ
+      type: C-MTEB/BQ
+      config: default
+      split: test
+      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
+    metrics:
+    - type: cos_sim_pearson
+      value: 74.66979530294986
+    - type: cos_sim_spearman
+      value: 77.59153258548018
+    - type: euclidean_pearson
+      value: 76.5862988380262
+    - type: euclidean_spearman
+      value: 77.59094368703879
+    - type: manhattan_pearson
+      value: 76.6034419552102
+    - type: manhattan_spearman
+      value: 77.6000715948404
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB CLSClusteringP2P
+      type: C-MTEB/CLSClusteringP2P
+      config: default
+      split: test
+      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
+    metrics:
+    - type: v_measure
+      value: 47.20931915009524
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB CLSClusteringS2S
+      type: C-MTEB/CLSClusteringS2S
+      config: default
+      split: test
+      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
+    metrics:
+    - type: v_measure
+      value: 45.787353610995474
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB CMedQAv1
+      type: C-MTEB/CMedQAv1-reranking
+      config: default
+      split: test
+      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
+    metrics:
+    - type: map
+      value: 86.37146026784607
+    - type: mrr
+      value: 88.52309523809524
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB CMedQAv2
+      type: C-MTEB/CMedQAv2-reranking
+      config: default
+      split: test
+      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
+    metrics:
+    - type: map
+      value: 87.40699302584699
+    - type: mrr
+      value: 89.51591269841269
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CmedqaRetrieval
+      type: C-MTEB/CmedqaRetrieval
+      config: default
+      split: dev
+      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
+    metrics:
+    - type: map_at_1
+      value: 24.465
+    - type: map_at_10
+      value: 36.689
+    - type: map_at_100
+      value: 38.605000000000004
+    - type: map_at_1000
+      value: 38.718
+    - type: map_at_3
+      value: 32.399
+    - type: map_at_5
+      value: 34.784
+    - type: mrr_at_1
+      value: 37.234
+    - type: mrr_at_10
+      value: 45.634
+    - type: mrr_at_100
+      value: 46.676
+    - type: mrr_at_1000
+      value: 46.717
+    - type: mrr_at_3
+      value: 42.94
+    - type: mrr_at_5
+      value: 44.457
+    - type: ndcg_at_1
+      value: 37.234
+    - type: ndcg_at_10
+      value: 43.469
+    - type: ndcg_at_100
+      value: 51.048
+    - type: ndcg_at_1000
+      value: 52.925999999999995
+    - type: ndcg_at_3
+      value: 37.942
+    - type: ndcg_at_5
+      value: 40.253
+    - type: precision_at_1
+      value: 37.234
+    - type: precision_at_10
+      value: 9.745
+    - type: precision_at_100
+      value: 1.5879999999999999
+    - type: precision_at_1000
+      value: 0.183
+    - type: precision_at_3
+      value: 21.505
+    - type: precision_at_5
+      value: 15.729000000000001
+    - type: recall_at_1
+      value: 24.465
+    - type: recall_at_10
+      value: 54.559999999999995
+    - type: recall_at_100
+      value: 85.97200000000001
+    - type: recall_at_1000
+      value: 98.32499999999999
+    - type: recall_at_3
+      value: 38.047
+    - type: recall_at_5
+      value: 45.08
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB Cmnli
+      type: C-MTEB/CMNLI
+      config: default
+      split: validation
+      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
+    metrics:
+    - type: cos_sim_accuracy
+      value: 84.50992182802165
+    - type: cos_sim_ap
+      value: 91.81488661281966
+    - type: cos_sim_f1
+      value: 85.46855802524294
+    - type: cos_sim_precision
+      value: 81.82207014542344
+    - type: cos_sim_recall
+      value: 89.4552256254384
+    - type: dot_accuracy
+      value: 84.50992182802165
+    - type: dot_ap
+      value: 91.80547588176556
+    - type: dot_f1
+      value: 85.46492111446794
+    - type: dot_precision
+      value: 81.95278969957081
+    - type: dot_recall
+      value: 89.29155950432546
+    - type: euclidean_accuracy
+      value: 84.49789536981359
+    - type: euclidean_ap
+      value: 91.81495039620808
+    - type: euclidean_f1
+      value: 85.46817317373308
+    - type: euclidean_precision
+      value: 81.93908193908193
+    - type: euclidean_recall
+      value: 89.31494037877017
+    - type: manhattan_accuracy
+      value: 84.46181599518941
+    - type: manhattan_ap
+      value: 91.85400573633447
+    - type: manhattan_f1
+      value: 85.54283809312146
+    - type: manhattan_precision
+      value: 81.51207115628971
+    - type: manhattan_recall
+      value: 89.99298573766659
+    - type: max_accuracy
+      value: 84.50992182802165
+    - type: max_ap
+      value: 91.85400573633447
+    - type: max_f1
+      value: 85.54283809312146
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CovidRetrieval
+      type: C-MTEB/CovidRetrieval
+      config: default
+      split: dev
+      revision: 1271c7809071a13532e05f25fb53511ffce77117
+    metrics:
+    - type: map_at_1
+      value: 68.072
+    - type: map_at_10
+      value: 76.82900000000001
+    - type: map_at_100
+      value: 77.146
+    - type: map_at_1000
+      value: 77.14999999999999
+    - type: map_at_3
+      value: 74.939
+    - type: map_at_5
+      value: 76.009
+    - type: mrr_at_1
+      value: 68.282
+    - type: mrr_at_10
+      value: 76.818
+    - type: mrr_at_100
+      value: 77.13600000000001
+    - type: mrr_at_1000
+      value: 77.14
+    - type: mrr_at_3
+      value: 74.956
+    - type: mrr_at_5
+      value: 76.047
+    - type: ndcg_at_1
+      value: 68.282
+    - type: ndcg_at_10
+      value: 80.87299999999999
+    - type: ndcg_at_100
+      value: 82.191
+    - type: ndcg_at_1000
+      value: 82.286
+    - type: ndcg_at_3
+      value: 77.065
+    - type: ndcg_at_5
+      value: 78.965
+    - type: precision_at_1
+      value: 68.282
+    - type: precision_at_10
+      value: 9.452
+    - type: precision_at_100
+      value: 1.002
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 27.889000000000003
+    - type: precision_at_5
+      value: 17.682000000000002
+    - type: recall_at_1
+      value: 68.072
+    - type: recall_at_10
+      value: 93.467
+    - type: recall_at_100
+      value: 99.157
+    - type: recall_at_1000
+      value: 99.895
+    - type: recall_at_3
+      value: 83.14
+    - type: recall_at_5
+      value: 87.67099999999999
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB DuRetrieval
+      type: C-MTEB/DuRetrieval
+      config: default
+      split: dev
+      revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
+    metrics:
+    - type: map_at_1
+      value: 26.107999999999997
+    - type: map_at_10
+      value: 78.384
+    - type: map_at_100
+      value: 81.341
+    - type: map_at_1000
+      value: 81.384
+    - type: map_at_3
+      value: 54.462999999999994
+    - type: map_at_5
+      value: 68.607
+    - type: mrr_at_1
+      value: 88.94999999999999
+    - type: mrr_at_10
+      value: 92.31
+    - type: mrr_at_100
+      value: 92.379
+    - type: mrr_at_1000
+      value: 92.38300000000001
+    - type: mrr_at_3
+      value: 91.85799999999999
+    - type: mrr_at_5
+      value: 92.146
+    - type: ndcg_at_1
+      value: 88.94999999999999
+    - type: ndcg_at_10
+      value: 86.00999999999999
+    - type: ndcg_at_100
+      value: 89.121
+    - type: ndcg_at_1000
+      value: 89.534
+    - type: ndcg_at_3
+      value: 84.69200000000001
+    - type: ndcg_at_5
+      value: 83.678
+    - type: precision_at_1
+      value: 88.94999999999999
+    - type: precision_at_10
+      value: 41.065000000000005
+    - type: precision_at_100
+      value: 4.781
+    - type: precision_at_1000
+      value: 0.488
+    - type: precision_at_3
+      value: 75.75
+    - type: precision_at_5
+      value: 63.93
+    - type: recall_at_1
+      value: 26.107999999999997
+    - type: recall_at_10
+      value: 87.349
+    - type: recall_at_100
+      value: 97.14699999999999
+    - type: recall_at_1000
+      value: 99.287
+    - type: recall_at_3
+      value: 56.601
+    - type: recall_at_5
+      value: 73.381
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB EcomRetrieval
+      type: C-MTEB/EcomRetrieval
+      config: default
+      split: dev
+      revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
+    metrics:
+    - type: map_at_1
+      value: 50.7
+    - type: map_at_10
+      value: 61.312999999999995
+    - type: map_at_100
+      value: 61.88399999999999
+    - type: map_at_1000
+      value: 61.9
+    - type: map_at_3
+      value: 58.983
+    - type: map_at_5
+      value: 60.238
+    - type: mrr_at_1
+      value: 50.7
+    - type: mrr_at_10
+      value: 61.312999999999995
+    - type: mrr_at_100
+      value: 61.88399999999999
+    - type: mrr_at_1000
+      value: 61.9
+    - type: mrr_at_3
+      value: 58.983
+    - type: mrr_at_5
+      value: 60.238
+    - type: ndcg_at_1
+      value: 50.7
+    - type: ndcg_at_10
+      value: 66.458
+    - type: ndcg_at_100
+      value: 69.098
+    - type: ndcg_at_1000
+      value: 69.539
+    - type: ndcg_at_3
+      value: 61.637
+    - type: ndcg_at_5
+      value: 63.92099999999999
+    - type: precision_at_1
+      value: 50.7
+    - type: precision_at_10
+      value: 8.260000000000002
+    - type: precision_at_100
+      value: 0.946
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 23.1
+    - type: precision_at_5
+      value: 14.979999999999999
+    - type: recall_at_1
+      value: 50.7
+    - type: recall_at_10
+      value: 82.6
+    - type: recall_at_100
+      value: 94.6
+    - type: recall_at_1000
+      value: 98.1
+    - type: recall_at_3
+      value: 69.3
+    - type: recall_at_5
+      value: 74.9
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB IFlyTek
+      type: C-MTEB/IFlyTek-classification
+      config: default
+      split: validation
+      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
+    metrics:
+    - type: accuracy
+      value: 53.76683339746056
+    - type: f1
+      value: 40.026100192683714
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB JDReview
+      type: C-MTEB/JDReview-classification
+      config: default
+      split: test
+      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
+    metrics:
+    - type: accuracy
+      value: 88.19887429643526
+    - type: ap
+      value: 59.02998120976959
+    - type: f1
+      value: 83.3659125921227
+  - task:
+      type: STS
+    dataset:
+      name: MTEB LCQMC
+      type: C-MTEB/LCQMC
+      config: default
+      split: test
+      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
+    metrics:
+    - type: cos_sim_pearson
+      value: 72.53955204856854
+    - type: cos_sim_spearman
+      value: 76.28996886746215
+    - type: euclidean_pearson
+      value: 75.31184890026394
+    - type: euclidean_spearman
+      value: 76.28984471300522
+    - type: manhattan_pearson
+      value: 75.36930361638623
+    - type: manhattan_spearman
+      value: 76.34021995551348
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB MMarcoReranking
+      type: C-MTEB/Mmarco-reranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 23.63666512532725
+    - type: mrr
+      value: 22.49642857142857
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MMarcoRetrieval
+      type: C-MTEB/MMarcoRetrieval
+      config: default
+      split: dev
+      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
+    metrics:
+    - type: map_at_1
+      value: 60.645
+    - type: map_at_10
+      value: 69.733
+    - type: map_at_100
+      value: 70.11699999999999
+    - type: map_at_1000
+      value: 70.135
+    - type: map_at_3
+      value: 67.585
+    - type: map_at_5
+      value: 68.904
+    - type: mrr_at_1
+      value: 62.765
+    - type: mrr_at_10
+      value: 70.428
+    - type: mrr_at_100
+      value: 70.77
+    - type: mrr_at_1000
+      value: 70.785
+    - type: mrr_at_3
+      value: 68.498
+    - type: mrr_at_5
+      value: 69.69
+    - type: ndcg_at_1
+      value: 62.765
+    - type: ndcg_at_10
+      value: 73.83
+    - type: ndcg_at_100
+      value: 75.593
+    - type: ndcg_at_1000
+      value: 76.05199999999999
+    - type: ndcg_at_3
+      value: 69.66499999999999
+    - type: ndcg_at_5
+      value: 71.929
+    - type: precision_at_1
+      value: 62.765
+    - type: precision_at_10
+      value: 9.117
+    - type: precision_at_100
+      value: 1.0
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 26.323
+    - type: precision_at_5
+      value: 16.971
+    - type: recall_at_1
+      value: 60.645
+    - type: recall_at_10
+      value: 85.907
+    - type: recall_at_100
+      value: 93.947
+    - type: recall_at_1000
+      value: 97.531
+    - type: recall_at_3
+      value: 74.773
+    - type: recall_at_5
+      value: 80.16799999999999
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveIntentClassification (zh-CN)
+      type: mteb/amazon_massive_intent
+      config: zh-CN
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 76.25084061869536
+    - type: f1
+      value: 73.65064492827022
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveScenarioClassification (zh-CN)
+      type: mteb/amazon_massive_scenario
+      config: zh-CN
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 77.2595830531271
+    - type: f1
+      value: 77.15217273559321
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MedicalRetrieval
+      type: C-MTEB/MedicalRetrieval
+      config: default
+      split: dev
+      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
+    metrics:
+    - type: map_at_1
+      value: 52.400000000000006
+    - type: map_at_10
+      value: 58.367000000000004
+    - type: map_at_100
+      value: 58.913000000000004
+    - type: map_at_1000
+      value: 58.961
+    - type: map_at_3
+      value: 56.882999999999996
+    - type: map_at_5
+      value: 57.743
+    - type: mrr_at_1
+      value: 52.400000000000006
+    - type: mrr_at_10
+      value: 58.367000000000004
+    - type: mrr_at_100
+      value: 58.913000000000004
+    - type: mrr_at_1000
+      value: 58.961
+    - type: mrr_at_3
+      value: 56.882999999999996
+    - type: mrr_at_5
+      value: 57.743
+    - type: ndcg_at_1
+      value: 52.400000000000006
+    - type: ndcg_at_10
+      value: 61.329
+    - type: ndcg_at_100
+      value: 64.264
+    - type: ndcg_at_1000
+      value: 65.669
+    - type: ndcg_at_3
+      value: 58.256
+    - type: ndcg_at_5
+      value: 59.813
+    - type: precision_at_1
+      value: 52.400000000000006
+    - type: precision_at_10
+      value: 7.07
+    - type: precision_at_100
+      value: 0.851
+    - type: precision_at_1000
+      value: 0.096
+    - type: precision_at_3
+      value: 20.732999999999997
+    - type: precision_at_5
+      value: 13.200000000000001
+    - type: recall_at_1
+      value: 52.400000000000006
+    - type: recall_at_10
+      value: 70.7
+    - type: recall_at_100
+      value: 85.1
+    - type: recall_at_1000
+      value: 96.39999999999999
+    - type: recall_at_3
+      value: 62.2
+    - type: recall_at_5
+      value: 66.0
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MultilingualSentiment
+      type: C-MTEB/MultilingualSentiment-classification
+      config: default
+      split: validation
+      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
+    metrics:
+    - type: accuracy
+      value: 77.42333333333333
+    - type: f1
+      value: 77.24849313989888
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB Ocnli
+      type: C-MTEB/OCNLI
+      config: default
+      split: validation
+      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
+    metrics:
+    - type: cos_sim_accuracy
+      value: 80.12994044396319
+    - type: cos_sim_ap
+      value: 85.21793541189636
+    - type: cos_sim_f1
+      value: 81.91489361702128
+    - type: cos_sim_precision
+      value: 75.55753791257806
+    - type: cos_sim_recall
+      value: 89.44033790918691
+    - type: dot_accuracy
+      value: 80.12994044396319
+    - type: dot_ap
+      value: 85.22568672443236
+    - type: dot_f1
+      value: 81.91489361702128
+    - type: dot_precision
+      value: 75.55753791257806
+    - type: dot_recall
+      value: 89.44033790918691
+    - type: euclidean_accuracy
+      value: 80.12994044396319
+    - type: euclidean_ap
+      value: 85.21643342357407
+    - type: euclidean_f1
+      value: 81.8830242510699
+    - type: euclidean_precision
+      value: 74.48096885813149
+    - type: euclidean_recall
+      value: 90.91869060190075
+    - type: manhattan_accuracy
+      value: 80.5630752571738
+    - type: manhattan_ap
+      value: 85.27682975032671
+    - type: manhattan_f1
+      value: 82.03883495145631
+    - type: manhattan_precision
+      value: 75.92093441150045
+    - type: manhattan_recall
+      value: 89.22914466737065
+    - type: max_accuracy
+      value: 80.5630752571738
+    - type: max_ap
+      value: 85.27682975032671
+    - type: max_f1
+      value: 82.03883495145631
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB OnlineShopping
+      type: C-MTEB/OnlineShopping-classification
+      config: default
+      split: test
+      revision: e610f2ebd179a8fda30ae534c3878750a96db120
+    metrics:
+    - type: accuracy
+      value: 94.47999999999999
+    - type: ap
+      value: 92.81177660844013
+    - type: f1
+      value: 94.47045470502114
+  - task:
+      type: STS
+    dataset:
+      name: MTEB PAWSX
+      type: C-MTEB/PAWSX
+      config: default
+      split: test
+      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
+    metrics:
+    - type: cos_sim_pearson
+      value: 46.13154582182421
+    - type: cos_sim_spearman
+      value: 50.21718723757444
+    - type: euclidean_pearson
+      value: 49.41535243569054
+    - type: euclidean_spearman
+      value: 50.21831909208907
+    - type: manhattan_pearson
+      value: 49.50756578601167
+    - type: manhattan_spearman
+      value: 50.229118655684566
+  - task:
+      type: STS
+    dataset:
+      name: MTEB QBQTC
+      type: C-MTEB/QBQTC
+      config: default
+      split: test
+      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.787794367421956
+    - type: cos_sim_spearman
+      value: 31.81774306987836
+    - type: euclidean_pearson
+      value: 29.809436608089495
+    - type: euclidean_spearman
+      value: 31.817379098812165
+    - type: manhattan_pearson
+      value: 30.377027186607787
+    - type: manhattan_spearman
+      value: 32.42286865176827
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (zh)
+      type: mteb/sts22-crosslingual-sts
+      config: zh
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 61.29839896616376
+    - type: cos_sim_spearman
+      value: 67.36328213286453
+    - type: euclidean_pearson
+      value: 64.33899267794008
+    - type: euclidean_spearman
+      value: 67.36552580196211
+    - type: manhattan_pearson
+      value: 65.20010308796022
+    - type: manhattan_spearman
+      value: 67.50982972902
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSB
+      type: C-MTEB/STSB
+      config: default
+      split: test
+      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.23278996774297
+    - type: cos_sim_spearman
+      value: 81.369375466486
+    - type: euclidean_pearson
+      value: 79.91030863727944
+    - type: euclidean_spearman
+      value: 81.36824495466793
+    - type: manhattan_pearson
+      value: 79.88047052896854
+    - type: manhattan_spearman
+      value: 81.3369604332008
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB T2Reranking
+      type: C-MTEB/T2Reranking
+      config: default
+      split: dev
+      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
+    metrics:
+    - type: map
+      value: 68.109205221286
+    - type: mrr
+      value: 78.40703619520477
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB T2Retrieval
+      type: C-MTEB/T2Retrieval
+      config: default
+      split: dev
+      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
+    metrics:
+    - type: map_at_1
+      value: 26.704
+    - type: map_at_10
+      value: 75.739
+    - type: map_at_100
+      value: 79.606
+    - type: map_at_1000
+      value: 79.666
+    - type: map_at_3
+      value: 52.803
+    - type: map_at_5
+      value: 65.068
+    - type: mrr_at_1
+      value: 88.48899999999999
+    - type: mrr_at_10
+      value: 91.377
+    - type: mrr_at_100
+      value: 91.474
+    - type: mrr_at_1000
+      value: 91.47800000000001
+    - type: mrr_at_3
+      value: 90.846
+    - type: mrr_at_5
+      value: 91.18
+    - type: ndcg_at_1
+      value: 88.48899999999999
+    - type: ndcg_at_10
+      value: 83.581
+    - type: ndcg_at_100
+      value: 87.502
+    - type: ndcg_at_1000
+      value: 88.1
+    - type: ndcg_at_3
+      value: 84.433
+    - type: ndcg_at_5
+      value: 83.174
+    - type: precision_at_1
+      value: 88.48899999999999
+    - type: precision_at_10
+      value: 41.857
+    - type: precision_at_100
+      value: 5.039
+    - type: precision_at_1000
+      value: 0.517
+    - type: precision_at_3
+      value: 73.938
+    - type: precision_at_5
+      value: 62.163000000000004
+    - type: recall_at_1
+      value: 26.704
+    - type: recall_at_10
+      value: 83.092
+    - type: recall_at_100
+      value: 95.659
+    - type: recall_at_1000
+      value: 98.779
+    - type: recall_at_3
+      value: 54.678000000000004
+    - type: recall_at_5
+      value: 68.843
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB TNews
+      type: C-MTEB/TNews-classification
+      config: default
+      split: validation
+      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
+    metrics:
+    - type: accuracy
+      value: 51.235
+    - type: f1
+      value: 48.14373844331604
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ThuNewsClusteringP2P
+      type: C-MTEB/ThuNewsClusteringP2P
+      config: default
+      split: test
+      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
+    metrics:
+    - type: v_measure
+      value: 87.42930040493792
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ThuNewsClusteringS2S
+      type: C-MTEB/ThuNewsClusteringS2S
+      config: default
+      split: test
+      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
+    metrics:
+    - type: v_measure
+      value: 87.90254094650042
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB VideoRetrieval
+      type: C-MTEB/VideoRetrieval
+      config: default
+      split: dev
+      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
+    metrics:
+    - type: map_at_1
+      value: 54.900000000000006
+    - type: map_at_10
+      value: 64.92
+    - type: map_at_100
+      value: 65.424
+    - type: map_at_1000
+      value: 65.43900000000001
+    - type: map_at_3
+      value: 63.132999999999996
+    - type: map_at_5
+      value: 64.208
+    - type: mrr_at_1
+      value: 54.900000000000006
+    - type: mrr_at_10
+      value: 64.92
+    - type: mrr_at_100
+      value: 65.424
+    - type: mrr_at_1000
+      value: 65.43900000000001
+    - type: mrr_at_3
+      value: 63.132999999999996
+    - type: mrr_at_5
+      value: 64.208
+    - type: ndcg_at_1
+      value: 54.900000000000006
+    - type: ndcg_at_10
+      value: 69.41199999999999
+    - type: ndcg_at_100
+      value: 71.824
+    - type: ndcg_at_1000
+      value: 72.301
+    - type: ndcg_at_3
+      value: 65.79700000000001
+    - type: ndcg_at_5
+      value: 67.713
+    - type: precision_at_1
+      value: 54.900000000000006
+    - type: precision_at_10
+      value: 8.33
+    - type: precision_at_100
+      value: 0.9450000000000001
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 24.5
+    - type: precision_at_5
+      value: 15.620000000000001
+    - type: recall_at_1
+      value: 54.900000000000006
+    - type: recall_at_10
+      value: 83.3
+    - type: recall_at_100
+      value: 94.5
+    - type: recall_at_1000
+      value: 98.4
+    - type: recall_at_3
+      value: 73.5
+    - type: recall_at_5
+      value: 78.10000000000001
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB Waimai
+      type: C-MTEB/waimai-classification
+      config: default
+      split: test
+      revision: 339287def212450dcaa9df8c22bf93e9980c7023
+    metrics:
+    - type: accuracy
+      value: 88.63
+    - type: ap
+      value: 73.78658340897097
+    - type: f1
+      value: 87.16764294033919
+---
+
+# agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF
+This model was converted to GGUF format from [`Alibaba-NLP/gte-Qwen1.5-7B-instruct`](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) for more details on the model.
+## Use with llama.cpp
+Install llama.cpp through brew.
+```bash
+brew install ggerganov/ggerganov/llama.cpp
+```
+Invoke the llama.cpp server or the CLI.
+CLI:
+```bash
+llama-cli --hf-repo agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF --model gte-qwen1.5-7b-instruct-q5_k_m.gguf -p "The meaning to life and the universe is"
+```
+Server:
+```bash
+llama-server --hf-repo agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF --model gte-qwen1.5-7b-instruct-q5_k_m.gguf -c 2048
+```
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+```
+git clone https://github.com/ggerganov/llama.cpp && \
+cd llama.cpp && \
+make && \
+./main -m gte-qwen1.5-7b-instruct-q5_k_m.gguf -n 128
+```