Upload 9 files

README.md

@@ -1,3 +1,2668 @@
 ---
+tags:
+- mteb
+- sentence_embedding
+- feature_extraction
+- transformers
+- transformers.js
+model-index:
+- name: UAE-Large-V1
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 75.55223880597015
+    - type: ap
+      value: 38.264070815317794
+    - type: f1
+      value: 69.40977934769845
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 92.84267499999999
+    - type: ap
+      value: 89.57568507997713
+    - type: f1
+      value: 92.82590734337774
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 48.292
+    - type: f1
+      value: 47.90257816032778
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 42.105
+    - type: map_at_10
+      value: 58.181000000000004
+    - type: map_at_100
+      value: 58.653999999999996
+    - type: map_at_1000
+      value: 58.657000000000004
+    - type: map_at_3
+      value: 54.386
+    - type: map_at_5
+      value: 56.757999999999996
+    - type: mrr_at_1
+      value: 42.745
+    - type: mrr_at_10
+      value: 58.437
+    - type: mrr_at_100
+      value: 58.894999999999996
+    - type: mrr_at_1000
+      value: 58.897999999999996
+    - type: mrr_at_3
+      value: 54.635
+    - type: mrr_at_5
+      value: 56.99999999999999
+    - type: ndcg_at_1
+      value: 42.105
+    - type: ndcg_at_10
+      value: 66.14999999999999
+    - type: ndcg_at_100
+      value: 68.048
+    - type: ndcg_at_1000
+      value: 68.11399999999999
+    - type: ndcg_at_3
+      value: 58.477000000000004
+    - type: ndcg_at_5
+      value: 62.768
+    - type: precision_at_1
+      value: 42.105
+    - type: precision_at_10
+      value: 9.110999999999999
+    - type: precision_at_100
+      value: 0.991
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 23.447000000000003
+    - type: precision_at_5
+      value: 16.159000000000002
+    - type: recall_at_1
+      value: 42.105
+    - type: recall_at_10
+      value: 91.11
+    - type: recall_at_100
+      value: 99.14699999999999
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 70.341
+    - type: recall_at_5
+      value: 80.797
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 49.02580759154173
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 43.093601280163554
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 64.19590406875427
+    - type: mrr
+      value: 77.09547992788991
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.86678362843676
+    - type: cos_sim_spearman
+      value: 86.1423242570783
+    - type: euclidean_pearson
+      value: 85.98994198511751
+    - type: euclidean_spearman
+      value: 86.48209103503942
+    - type: manhattan_pearson
+      value: 85.6446436316182
+    - type: manhattan_spearman
+      value: 86.21039809734357
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 87.69155844155844
+    - type: f1
+      value: 87.68109381943547
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 39.37501687500394
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 37.23401405155885
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 30.232
+    - type: map_at_10
+      value: 41.404999999999994
+    - type: map_at_100
+      value: 42.896
+    - type: map_at_1000
+      value: 43.028
+    - type: map_at_3
+      value: 37.925
+    - type: map_at_5
+      value: 39.865
+    - type: mrr_at_1
+      value: 36.338
+    - type: mrr_at_10
+      value: 46.969
+    - type: mrr_at_100
+      value: 47.684
+    - type: mrr_at_1000
+      value: 47.731
+    - type: mrr_at_3
+      value: 44.063
+    - type: mrr_at_5
+      value: 45.908
+    - type: ndcg_at_1
+      value: 36.338
+    - type: ndcg_at_10
+      value: 47.887
+    - type: ndcg_at_100
+      value: 53.357
+    - type: ndcg_at_1000
+      value: 55.376999999999995
+    - type: ndcg_at_3
+      value: 42.588
+    - type: ndcg_at_5
+      value: 45.132
+    - type: precision_at_1
+      value: 36.338
+    - type: precision_at_10
+      value: 9.17
+    - type: precision_at_100
+      value: 1.4909999999999999
+    - type: precision_at_1000
+      value: 0.196
+    - type: precision_at_3
+      value: 20.315
+    - type: precision_at_5
+      value: 14.793000000000001
+    - type: recall_at_1
+      value: 30.232
+    - type: recall_at_10
+      value: 60.67399999999999
+    - type: recall_at_100
+      value: 83.628
+    - type: recall_at_1000
+      value: 96.209
+    - type: recall_at_3
+      value: 45.48
+    - type: recall_at_5
+      value: 52.354
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.237
+    - type: map_at_10
+      value: 42.829
+    - type: map_at_100
+      value: 44.065
+    - type: map_at_1000
+      value: 44.199
+    - type: map_at_3
+      value: 39.885999999999996
+    - type: map_at_5
+      value: 41.55
+    - type: mrr_at_1
+      value: 40.064
+    - type: mrr_at_10
+      value: 48.611
+    - type: mrr_at_100
+      value: 49.245
+    - type: mrr_at_1000
+      value: 49.29
+    - type: mrr_at_3
+      value: 46.561
+    - type: mrr_at_5
+      value: 47.771
+    - type: ndcg_at_1
+      value: 40.064
+    - type: ndcg_at_10
+      value: 48.388
+    - type: ndcg_at_100
+      value: 52.666999999999994
+    - type: ndcg_at_1000
+      value: 54.67100000000001
+    - type: ndcg_at_3
+      value: 44.504
+    - type: ndcg_at_5
+      value: 46.303
+    - type: precision_at_1
+      value: 40.064
+    - type: precision_at_10
+      value: 9.051
+    - type: precision_at_100
+      value: 1.4500000000000002
+    - type: precision_at_1000
+      value: 0.193
+    - type: precision_at_3
+      value: 21.444
+    - type: precision_at_5
+      value: 15.045
+    - type: recall_at_1
+      value: 32.237
+    - type: recall_at_10
+      value: 57.943999999999996
+    - type: recall_at_100
+      value: 75.98700000000001
+    - type: recall_at_1000
+      value: 88.453
+    - type: recall_at_3
+      value: 46.268
+    - type: recall_at_5
+      value: 51.459999999999994
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 38.797
+    - type: map_at_10
+      value: 51.263000000000005
+    - type: map_at_100
+      value: 52.333
+    - type: map_at_1000
+      value: 52.393
+    - type: map_at_3
+      value: 47.936
+    - type: map_at_5
+      value: 49.844
+    - type: mrr_at_1
+      value: 44.389
+    - type: mrr_at_10
+      value: 54.601
+    - type: mrr_at_100
+      value: 55.300000000000004
+    - type: mrr_at_1000
+      value: 55.333
+    - type: mrr_at_3
+      value: 52.068999999999996
+    - type: mrr_at_5
+      value: 53.627
+    - type: ndcg_at_1
+      value: 44.389
+    - type: ndcg_at_10
+      value: 57.193000000000005
+    - type: ndcg_at_100
+      value: 61.307
+    - type: ndcg_at_1000
+      value: 62.529
+    - type: ndcg_at_3
+      value: 51.607
+    - type: ndcg_at_5
+      value: 54.409
+    - type: precision_at_1
+      value: 44.389
+    - type: precision_at_10
+      value: 9.26
+    - type: precision_at_100
+      value: 1.222
+    - type: precision_at_1000
+      value: 0.13699999999999998
+    - type: precision_at_3
+      value: 23.03
+    - type: precision_at_5
+      value: 15.887
+    - type: recall_at_1
+      value: 38.797
+    - type: recall_at_10
+      value: 71.449
+    - type: recall_at_100
+      value: 88.881
+    - type: recall_at_1000
+      value: 97.52
+    - type: recall_at_3
+      value: 56.503
+    - type: recall_at_5
+      value: 63.392
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.291999999999998
+    - type: map_at_10
+      value: 35.65
+    - type: map_at_100
+      value: 36.689
+    - type: map_at_1000
+      value: 36.753
+    - type: map_at_3
+      value: 32.995000000000005
+    - type: map_at_5
+      value: 34.409
+    - type: mrr_at_1
+      value: 29.04
+    - type: mrr_at_10
+      value: 37.486000000000004
+    - type: mrr_at_100
+      value: 38.394
+    - type: mrr_at_1000
+      value: 38.445
+    - type: mrr_at_3
+      value: 35.028
+    - type: mrr_at_5
+      value: 36.305
+    - type: ndcg_at_1
+      value: 29.04
+    - type: ndcg_at_10
+      value: 40.613
+    - type: ndcg_at_100
+      value: 45.733000000000004
+    - type: ndcg_at_1000
+      value: 47.447
+    - type: ndcg_at_3
+      value: 35.339999999999996
+    - type: ndcg_at_5
+      value: 37.706
+    - type: precision_at_1
+      value: 29.04
+    - type: precision_at_10
+      value: 6.192
+    - type: precision_at_100
+      value: 0.9249999999999999
+    - type: precision_at_1000
+      value: 0.11
+    - type: precision_at_3
+      value: 14.802000000000001
+    - type: precision_at_5
+      value: 10.305
+    - type: recall_at_1
+      value: 27.291999999999998
+    - type: recall_at_10
+      value: 54.25299999999999
+    - type: recall_at_100
+      value: 77.773
+    - type: recall_at_1000
+      value: 90.795
+    - type: recall_at_3
+      value: 39.731
+    - type: recall_at_5
+      value: 45.403999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 18.326
+    - type: map_at_10
+      value: 26.290999999999997
+    - type: map_at_100
+      value: 27.456999999999997
+    - type: map_at_1000
+      value: 27.583000000000002
+    - type: map_at_3
+      value: 23.578
+    - type: map_at_5
+      value: 25.113000000000003
+    - type: mrr_at_1
+      value: 22.637
+    - type: mrr_at_10
+      value: 31.139
+    - type: mrr_at_100
+      value: 32.074999999999996
+    - type: mrr_at_1000
+      value: 32.147
+    - type: mrr_at_3
+      value: 28.483000000000004
+    - type: mrr_at_5
+      value: 29.963
+    - type: ndcg_at_1
+      value: 22.637
+    - type: ndcg_at_10
+      value: 31.717000000000002
+    - type: ndcg_at_100
+      value: 37.201
+    - type: ndcg_at_1000
+      value: 40.088
+    - type: ndcg_at_3
+      value: 26.686
+    - type: ndcg_at_5
+      value: 29.076999999999998
+    - type: precision_at_1
+      value: 22.637
+    - type: precision_at_10
+      value: 5.7090000000000005
+    - type: precision_at_100
+      value: 0.979
+    - type: precision_at_1000
+      value: 0.13799999999999998
+    - type: precision_at_3
+      value: 12.894
+    - type: precision_at_5
+      value: 9.328
+    - type: recall_at_1
+      value: 18.326
+    - type: recall_at_10
+      value: 43.824999999999996
+    - type: recall_at_100
+      value: 67.316
+    - type: recall_at_1000
+      value: 87.481
+    - type: recall_at_3
+      value: 29.866999999999997
+    - type: recall_at_5
+      value: 35.961999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 29.875
+    - type: map_at_10
+      value: 40.458
+    - type: map_at_100
+      value: 41.772
+    - type: map_at_1000
+      value: 41.882999999999996
+    - type: map_at_3
+      value: 37.086999999999996
+    - type: map_at_5
+      value: 39.153
+    - type: mrr_at_1
+      value: 36.381
+    - type: mrr_at_10
+      value: 46.190999999999995
+    - type: mrr_at_100
+      value: 46.983999999999995
+    - type: mrr_at_1000
+      value: 47.032000000000004
+    - type: mrr_at_3
+      value: 43.486999999999995
+    - type: mrr_at_5
+      value: 45.249
+    - type: ndcg_at_1
+      value: 36.381
+    - type: ndcg_at_10
+      value: 46.602
+    - type: ndcg_at_100
+      value: 51.885999999999996
+    - type: ndcg_at_1000
+      value: 53.895
+    - type: ndcg_at_3
+      value: 41.155
+    - type: ndcg_at_5
+      value: 44.182
+    - type: precision_at_1
+      value: 36.381
+    - type: precision_at_10
+      value: 8.402
+    - type: precision_at_100
+      value: 1.278
+    - type: precision_at_1000
+      value: 0.16199999999999998
+    - type: precision_at_3
+      value: 19.346
+    - type: precision_at_5
+      value: 14.09
+    - type: recall_at_1
+      value: 29.875
+    - type: recall_at_10
+      value: 59.065999999999995
+    - type: recall_at_100
+      value: 80.923
+    - type: recall_at_1000
+      value: 93.927
+    - type: recall_at_3
+      value: 44.462
+    - type: recall_at_5
+      value: 51.89
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.94
+    - type: map_at_10
+      value: 35.125
+    - type: map_at_100
+      value: 36.476
+    - type: map_at_1000
+      value: 36.579
+    - type: map_at_3
+      value: 31.840000000000003
+    - type: map_at_5
+      value: 33.647
+    - type: mrr_at_1
+      value: 30.936000000000003
+    - type: mrr_at_10
+      value: 40.637
+    - type: mrr_at_100
+      value: 41.471000000000004
+    - type: mrr_at_1000
+      value: 41.525
+    - type: mrr_at_3
+      value: 38.013999999999996
+    - type: mrr_at_5
+      value: 39.469
+    - type: ndcg_at_1
+      value: 30.936000000000003
+    - type: ndcg_at_10
+      value: 41.295
+    - type: ndcg_at_100
+      value: 46.92
+    - type: ndcg_at_1000
+      value: 49.183
+    - type: ndcg_at_3
+      value: 35.811
+    - type: ndcg_at_5
+      value: 38.306000000000004
+    - type: precision_at_1
+      value: 30.936000000000003
+    - type: precision_at_10
+      value: 7.728
+    - type: precision_at_100
+      value: 1.226
+    - type: precision_at_1000
+      value: 0.158
+    - type: precision_at_3
+      value: 17.237
+    - type: precision_at_5
+      value: 12.42
+    - type: recall_at_1
+      value: 24.94
+    - type: recall_at_10
+      value: 54.235
+    - type: recall_at_100
+      value: 78.314
+    - type: recall_at_1000
+      value: 93.973
+    - type: recall_at_3
+      value: 38.925
+    - type: recall_at_5
+      value: 45.505
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.250833333333333
+    - type: map_at_10
+      value: 35.46875
+    - type: map_at_100
+      value: 36.667
+    - type: map_at_1000
+      value: 36.78025
+    - type: map_at_3
+      value: 32.56733333333334
+    - type: map_at_5
+      value: 34.20333333333333
+    - type: mrr_at_1
+      value: 30.8945
+    - type: mrr_at_10
+      value: 39.636833333333335
+    - type: mrr_at_100
+      value: 40.46508333333333
+    - type: mrr_at_1000
+      value: 40.521249999999995
+    - type: mrr_at_3
+      value: 37.140166666666666
+    - type: mrr_at_5
+      value: 38.60999999999999
+    - type: ndcg_at_1
+      value: 30.8945
+    - type: ndcg_at_10
+      value: 40.93441666666667
+    - type: ndcg_at_100
+      value: 46.062416666666664
+    - type: ndcg_at_1000
+      value: 48.28341666666667
+    - type: ndcg_at_3
+      value: 35.97575
+    - type: ndcg_at_5
+      value: 38.3785
+    - type: precision_at_1
+      value: 30.8945
+    - type: precision_at_10
+      value: 7.180250000000001
+    - type: precision_at_100
+      value: 1.1468333333333334
+    - type: precision_at_1000
+      value: 0.15283333333333332
+    - type: precision_at_3
+      value: 16.525583333333334
+    - type: precision_at_5
+      value: 11.798333333333332
+    - type: recall_at_1
+      value: 26.250833333333333
+    - type: recall_at_10
+      value: 52.96108333333333
+    - type: recall_at_100
+      value: 75.45908333333334
+    - type: recall_at_1000
+      value: 90.73924999999998
+    - type: recall_at_3
+      value: 39.25483333333333
+    - type: recall_at_5
+      value: 45.37950000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.595
+    - type: map_at_10
+      value: 31.747999999999998
+    - type: map_at_100
+      value: 32.62
+    - type: map_at_1000
+      value: 32.713
+    - type: map_at_3
+      value: 29.48
+    - type: map_at_5
+      value: 30.635
+    - type: mrr_at_1
+      value: 27.607
+    - type: mrr_at_10
+      value: 34.449000000000005
+    - type: mrr_at_100
+      value: 35.182
+    - type: mrr_at_1000
+      value: 35.254000000000005
+    - type: mrr_at_3
+      value: 32.413
+    - type: mrr_at_5
+      value: 33.372
+    - type: ndcg_at_1
+      value: 27.607
+    - type: ndcg_at_10
+      value: 36.041000000000004
+    - type: ndcg_at_100
+      value: 40.514
+    - type: ndcg_at_1000
+      value: 42.851
+    - type: ndcg_at_3
+      value: 31.689
+    - type: ndcg_at_5
+      value: 33.479
+    - type: precision_at_1
+      value: 27.607
+    - type: precision_at_10
+      value: 5.66
+    - type: precision_at_100
+      value: 0.868
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 13.446
+    - type: precision_at_5
+      value: 9.264
+    - type: recall_at_1
+      value: 24.595
+    - type: recall_at_10
+      value: 46.79
+    - type: recall_at_100
+      value: 67.413
+    - type: recall_at_1000
+      value: 84.753
+    - type: recall_at_3
+      value: 34.644999999999996
+    - type: recall_at_5
+      value: 39.09
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.333000000000002
+    - type: map_at_10
+      value: 24.427
+    - type: map_at_100
+      value: 25.576
+    - type: map_at_1000
+      value: 25.692999999999998
+    - type: map_at_3
+      value: 22.002
+    - type: map_at_5
+      value: 23.249
+    - type: mrr_at_1
+      value: 20.716
+    - type: mrr_at_10
+      value: 28.072000000000003
+    - type: mrr_at_100
+      value: 29.067
+    - type: mrr_at_1000
+      value: 29.137
+    - type: mrr_at_3
+      value: 25.832
+    - type: mrr_at_5
+      value: 27.045
+    - type: ndcg_at_1
+      value: 20.716
+    - type: ndcg_at_10
+      value: 29.109
+    - type: ndcg_at_100
+      value: 34.797
+    - type: ndcg_at_1000
+      value: 37.503
+    - type: ndcg_at_3
+      value: 24.668
+    - type: ndcg_at_5
+      value: 26.552999999999997
+    - type: precision_at_1
+      value: 20.716
+    - type: precision_at_10
+      value: 5.351
+    - type: precision_at_100
+      value: 0.955
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 11.584999999999999
+    - type: precision_at_5
+      value: 8.362
+    - type: recall_at_1
+      value: 17.333000000000002
+    - type: recall_at_10
+      value: 39.604
+    - type: recall_at_100
+      value: 65.525
+    - type: recall_at_1000
+      value: 84.651
+    - type: recall_at_3
+      value: 27.199
+    - type: recall_at_5
+      value: 32.019
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.342
+    - type: map_at_10
+      value: 35.349000000000004
+    - type: map_at_100
+      value: 36.443
+    - type: map_at_1000
+      value: 36.548
+    - type: map_at_3
+      value: 32.307
+    - type: map_at_5
+      value: 34.164
+    - type: mrr_at_1
+      value: 31.063000000000002
+    - type: mrr_at_10
+      value: 39.703
+    - type: mrr_at_100
+      value: 40.555
+    - type: mrr_at_1000
+      value: 40.614
+    - type: mrr_at_3
+      value: 37.141999999999996
+    - type: mrr_at_5
+      value: 38.812000000000005
+    - type: ndcg_at_1
+      value: 31.063000000000002
+    - type: ndcg_at_10
+      value: 40.873
+    - type: ndcg_at_100
+      value: 45.896
+    - type: ndcg_at_1000
+      value: 48.205999999999996
+    - type: ndcg_at_3
+      value: 35.522
+    - type: ndcg_at_5
+      value: 38.419
+    - type: precision_at_1
+      value: 31.063000000000002
+    - type: precision_at_10
+      value: 6.866
+    - type: precision_at_100
+      value: 1.053
+    - type: precision_at_1000
+      value: 0.13699999999999998
+    - type: precision_at_3
+      value: 16.014
+    - type: precision_at_5
+      value: 11.604000000000001
+    - type: recall_at_1
+      value: 26.342
+    - type: recall_at_10
+      value: 53.40200000000001
+    - type: recall_at_100
+      value: 75.251
+    - type: recall_at_1000
+      value: 91.13799999999999
+    - type: recall_at_3
+      value: 39.103
+    - type: recall_at_5
+      value: 46.357
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.71
+    - type: map_at_10
+      value: 32.153999999999996
+    - type: map_at_100
+      value: 33.821
+    - type: map_at_1000
+      value: 34.034
+    - type: map_at_3
+      value: 29.376
+    - type: map_at_5
+      value: 30.878
+    - type: mrr_at_1
+      value: 28.458
+    - type: mrr_at_10
+      value: 36.775999999999996
+    - type: mrr_at_100
+      value: 37.804
+    - type: mrr_at_1000
+      value: 37.858999999999995
+    - type: mrr_at_3
+      value: 34.123999999999995
+    - type: mrr_at_5
+      value: 35.596
+    - type: ndcg_at_1
+      value: 28.458
+    - type: ndcg_at_10
+      value: 37.858999999999995
+    - type: ndcg_at_100
+      value: 44.194
+    - type: ndcg_at_1000
+      value: 46.744
+    - type: ndcg_at_3
+      value: 33.348
+    - type: ndcg_at_5
+      value: 35.448
+    - type: precision_at_1
+      value: 28.458
+    - type: precision_at_10
+      value: 7.4510000000000005
+    - type: precision_at_100
+      value: 1.5
+    - type: precision_at_1000
+      value: 0.23700000000000002
+    - type: precision_at_3
+      value: 15.809999999999999
+    - type: precision_at_5
+      value: 11.462
+    - type: recall_at_1
+      value: 23.71
+    - type: recall_at_10
+      value: 48.272999999999996
+    - type: recall_at_100
+      value: 77.134
+    - type: recall_at_1000
+      value: 93.001
+    - type: recall_at_3
+      value: 35.480000000000004
+    - type: recall_at_5
+      value: 41.19
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.331
+    - type: map_at_10
+      value: 28.926000000000002
+    - type: map_at_100
+      value: 29.855999999999998
+    - type: map_at_1000
+      value: 29.957
+    - type: map_at_3
+      value: 26.395999999999997
+    - type: map_at_5
+      value: 27.933000000000003
+    - type: mrr_at_1
+      value: 23.105
+    - type: mrr_at_10
+      value: 31.008000000000003
+    - type: mrr_at_100
+      value: 31.819999999999997
+    - type: mrr_at_1000
+      value: 31.887999999999998
+    - type: mrr_at_3
+      value: 28.466
+    - type: mrr_at_5
+      value: 30.203000000000003
+    - type: ndcg_at_1
+      value: 23.105
+    - type: ndcg_at_10
+      value: 33.635999999999996
+    - type: ndcg_at_100
+      value: 38.277
+    - type: ndcg_at_1000
+      value: 40.907
+    - type: ndcg_at_3
+      value: 28.791
+    - type: ndcg_at_5
+      value: 31.528
+    - type: precision_at_1
+      value: 23.105
+    - type: precision_at_10
+      value: 5.323
+    - type: precision_at_100
+      value: 0.815
+    - type: precision_at_1000
+      value: 0.117
+    - type: precision_at_3
+      value: 12.384
+    - type: precision_at_5
+      value: 9.02
+    - type: recall_at_1
+      value: 21.331
+    - type: recall_at_10
+      value: 46.018
+    - type: recall_at_100
+      value: 67.364
+    - type: recall_at_1000
+      value: 86.97
+    - type: recall_at_3
+      value: 33.395
+    - type: recall_at_5
+      value: 39.931
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.011000000000003
+    - type: map_at_10
+      value: 28.816999999999997
+    - type: map_at_100
+      value: 30.761
+    - type: map_at_1000
+      value: 30.958000000000002
+    - type: map_at_3
+      value: 24.044999999999998
+    - type: map_at_5
+      value: 26.557
+    - type: mrr_at_1
+      value: 38.696999999999996
+    - type: mrr_at_10
+      value: 50.464
+    - type: mrr_at_100
+      value: 51.193999999999996
+    - type: mrr_at_1000
+      value: 51.219
+    - type: mrr_at_3
+      value: 47.339999999999996
+    - type: mrr_at_5
+      value: 49.346000000000004
+    - type: ndcg_at_1
+      value: 38.696999999999996
+    - type: ndcg_at_10
+      value: 38.53
+    - type: ndcg_at_100
+      value: 45.525
+    - type: ndcg_at_1000
+      value: 48.685
+    - type: ndcg_at_3
+      value: 32.282
+    - type: ndcg_at_5
+      value: 34.482
+    - type: precision_at_1
+      value: 38.696999999999996
+    - type: precision_at_10
+      value: 11.895999999999999
+    - type: precision_at_100
+      value: 1.95
+    - type: precision_at_1000
+      value: 0.254
+    - type: precision_at_3
+      value: 24.038999999999998
+    - type: precision_at_5
+      value: 18.332
+    - type: recall_at_1
+      value: 17.011000000000003
+    - type: recall_at_10
+      value: 44.452999999999996
+    - type: recall_at_100
+      value: 68.223
+    - type: recall_at_1000
+      value: 85.653
+    - type: recall_at_3
+      value: 28.784
+    - type: recall_at_5
+      value: 35.66
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 9.516
+    - type: map_at_10
+      value: 21.439
+    - type: map_at_100
+      value: 31.517
+    - type: map_at_1000
+      value: 33.267
+    - type: map_at_3
+      value: 15.004999999999999
+    - type: map_at_5
+      value: 17.793999999999997
+    - type: mrr_at_1
+      value: 71.25
+    - type: mrr_at_10
+      value: 79.071
+    - type: mrr_at_100
+      value: 79.325
+    - type: mrr_at_1000
+      value: 79.33
+    - type: mrr_at_3
+      value: 77.708
+    - type: mrr_at_5
+      value: 78.546
+    - type: ndcg_at_1
+      value: 58.62500000000001
+    - type: ndcg_at_10
+      value: 44.889
+    - type: ndcg_at_100
+      value: 50.536
+    - type: ndcg_at_1000
+      value: 57.724
+    - type: ndcg_at_3
+      value: 49.32
+    - type: ndcg_at_5
+      value: 46.775
+    - type: precision_at_1
+      value: 71.25
+    - type: precision_at_10
+      value: 36.175000000000004
+    - type: precision_at_100
+      value: 11.940000000000001
+    - type: precision_at_1000
+      value: 2.178
+    - type: precision_at_3
+      value: 53.583000000000006
+    - type: precision_at_5
+      value: 45.550000000000004
+    - type: recall_at_1
+      value: 9.516
+    - type: recall_at_10
+      value: 27.028000000000002
+    - type: recall_at_100
+      value: 57.581
+    - type: recall_at_1000
+      value: 80.623
+    - type: recall_at_3
+      value: 16.313
+    - type: recall_at_5
+      value: 20.674
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 51.74999999999999
+    - type: f1
+      value: 46.46706502669774
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 77.266
+    - type: map_at_10
+      value: 84.89999999999999
+    - type: map_at_100
+      value: 85.109
+    - type: map_at_1000
+      value: 85.123
+    - type: map_at_3
+      value: 83.898
+    - type: map_at_5
+      value: 84.541
+    - type: mrr_at_1
+      value: 83.138
+    - type: mrr_at_10
+      value: 89.37
+    - type: mrr_at_100
+      value: 89.432
+    - type: mrr_at_1000
+      value: 89.43299999999999
+    - type: mrr_at_3
+      value: 88.836
+    - type: mrr_at_5
+      value: 89.21
+    - type: ndcg_at_1
+      value: 83.138
+    - type: ndcg_at_10
+      value: 88.244
+    - type: ndcg_at_100
+      value: 88.98700000000001
+    - type: ndcg_at_1000
+      value: 89.21900000000001
+    - type: ndcg_at_3
+      value: 86.825
+    - type: ndcg_at_5
+      value: 87.636
+    - type: precision_at_1
+      value: 83.138
+    - type: precision_at_10
+      value: 10.47
+    - type: precision_at_100
+      value: 1.1079999999999999
+    - type: precision_at_1000
+      value: 0.11499999999999999
+    - type: precision_at_3
+      value: 32.933
+    - type: precision_at_5
+      value: 20.36
+    - type: recall_at_1
+      value: 77.266
+    - type: recall_at_10
+      value: 94.063
+    - type: recall_at_100
+      value: 96.993
+    - type: recall_at_1000
+      value: 98.414
+    - type: recall_at_3
+      value: 90.228
+    - type: recall_at_5
+      value: 92.328
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.319
+    - type: map_at_10
+      value: 36.943
+    - type: map_at_100
+      value: 38.951
+    - type: map_at_1000
+      value: 39.114
+    - type: map_at_3
+      value: 32.82
+    - type: map_at_5
+      value: 34.945
+    - type: mrr_at_1
+      value: 44.135999999999996
+    - type: mrr_at_10
+      value: 53.071999999999996
+    - type: mrr_at_100
+      value: 53.87
+    - type: mrr_at_1000
+      value: 53.90200000000001
+    - type: mrr_at_3
+      value: 50.77199999999999
+    - type: mrr_at_5
+      value: 52.129999999999995
+    - type: ndcg_at_1
+      value: 44.135999999999996
+    - type: ndcg_at_10
+      value: 44.836
+    - type: ndcg_at_100
+      value: 51.754
+    - type: ndcg_at_1000
+      value: 54.36
+    - type: ndcg_at_3
+      value: 41.658
+    - type: ndcg_at_5
+      value: 42.354
+    - type: precision_at_1
+      value: 44.135999999999996
+    - type: precision_at_10
+      value: 12.284
+    - type: precision_at_100
+      value: 1.952
+    - type: precision_at_1000
+      value: 0.242
+    - type: precision_at_3
+      value: 27.828999999999997
+    - type: precision_at_5
+      value: 20.093
+    - type: recall_at_1
+      value: 22.319
+    - type: recall_at_10
+      value: 51.528
+    - type: recall_at_100
+      value: 76.70700000000001
+    - type: recall_at_1000
+      value: 92.143
+    - type: recall_at_3
+      value: 38.641
+    - type: recall_at_5
+      value: 43.653999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 40.182
+    - type: map_at_10
+      value: 65.146
+    - type: map_at_100
+      value: 66.023
+    - type: map_at_1000
+      value: 66.078
+    - type: map_at_3
+      value: 61.617999999999995
+    - type: map_at_5
+      value: 63.82299999999999
+    - type: mrr_at_1
+      value: 80.365
+    - type: mrr_at_10
+      value: 85.79
+    - type: mrr_at_100
+      value: 85.963
+    - type: mrr_at_1000
+      value: 85.968
+    - type: mrr_at_3
+      value: 84.952
+    - type: mrr_at_5
+      value: 85.503
+    - type: ndcg_at_1
+      value: 80.365
+    - type: ndcg_at_10
+      value: 73.13499999999999
+    - type: ndcg_at_100
+      value: 76.133
+    - type: ndcg_at_1000
+      value: 77.151
+    - type: ndcg_at_3
+      value: 68.255
+    - type: ndcg_at_5
+      value: 70.978
+    - type: precision_at_1
+      value: 80.365
+    - type: precision_at_10
+      value: 15.359
+    - type: precision_at_100
+      value: 1.7690000000000001
+    - type: precision_at_1000
+      value: 0.19
+    - type: precision_at_3
+      value: 44.024
+    - type: precision_at_5
+      value: 28.555999999999997
+    - type: recall_at_1
+      value: 40.182
+    - type: recall_at_10
+      value: 76.793
+    - type: recall_at_100
+      value: 88.474
+    - type: recall_at_1000
+      value: 95.159
+    - type: recall_at_3
+      value: 66.036
+    - type: recall_at_5
+      value: 71.391
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 92.7796
+    - type: ap
+      value: 89.24883716810874
+    - type: f1
+      value: 92.7706903433313
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.016
+    - type: map_at_10
+      value: 34.408
+    - type: map_at_100
+      value: 35.592
+    - type: map_at_1000
+      value: 35.64
+    - type: map_at_3
+      value: 30.459999999999997
+    - type: map_at_5
+      value: 32.721000000000004
+    - type: mrr_at_1
+      value: 22.593
+    - type: mrr_at_10
+      value: 34.993
+    - type: mrr_at_100
+      value: 36.113
+    - type: mrr_at_1000
+      value: 36.156
+    - type: mrr_at_3
+      value: 31.101
+    - type: mrr_at_5
+      value: 33.364
+    - type: ndcg_at_1
+      value: 22.579
+    - type: ndcg_at_10
+      value: 41.404999999999994
+    - type: ndcg_at_100
+      value: 47.018
+    - type: ndcg_at_1000
+      value: 48.211999999999996
+    - type: ndcg_at_3
+      value: 33.389
+    - type: ndcg_at_5
+      value: 37.425000000000004
+    - type: precision_at_1
+      value: 22.579
+    - type: precision_at_10
+      value: 6.59
+    - type: precision_at_100
+      value: 0.938
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 14.241000000000001
+    - type: precision_at_5
+      value: 10.59
+    - type: recall_at_1
+      value: 22.016
+    - type: recall_at_10
+      value: 62.927
+    - type: recall_at_100
+      value: 88.72
+    - type: recall_at_1000
+      value: 97.80799999999999
+    - type: recall_at_3
+      value: 41.229
+    - type: recall_at_5
+      value: 50.88
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 94.01732786137711
+    - type: f1
+      value: 93.76353126402202
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 76.91746466028272
+    - type: f1
+      value: 57.715651682646765
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 76.5030262273033
+    - type: f1
+      value: 74.6693629986121
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 79.74781439139207
+    - type: f1
+      value: 79.96684171018774
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 33.2156206892017
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 31.180539484816137
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 32.51125957874274
+    - type: mrr
+      value: 33.777037359249995
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 7.248
+    - type: map_at_10
+      value: 15.340000000000002
+    - type: map_at_100
+      value: 19.591
+    - type: map_at_1000
+      value: 21.187
+    - type: map_at_3
+      value: 11.329
+    - type: map_at_5
+      value: 13.209999999999999
+    - type: mrr_at_1
+      value: 47.678
+    - type: mrr_at_10
+      value: 57.493
+    - type: mrr_at_100
+      value: 58.038999999999994
+    - type: mrr_at_1000
+      value: 58.07
+    - type: mrr_at_3
+      value: 55.36600000000001
+    - type: mrr_at_5
+      value: 56.635999999999996
+    - type: ndcg_at_1
+      value: 46.129999999999995
+    - type: ndcg_at_10
+      value: 38.653999999999996
+    - type: ndcg_at_100
+      value: 36.288
+    - type: ndcg_at_1000
+      value: 44.765
+    - type: ndcg_at_3
+      value: 43.553
+    - type: ndcg_at_5
+      value: 41.317
+    - type: precision_at_1
+      value: 47.368
+    - type: precision_at_10
+      value: 28.669
+    - type: precision_at_100
+      value: 9.158
+    - type: precision_at_1000
+      value: 2.207
+    - type: precision_at_3
+      value: 40.97
+    - type: precision_at_5
+      value: 35.604
+    - type: recall_at_1
+      value: 7.248
+    - type: recall_at_10
+      value: 19.46
+    - type: recall_at_100
+      value: 37.214000000000006
+    - type: recall_at_1000
+      value: 67.64099999999999
+    - type: recall_at_3
+      value: 12.025
+    - type: recall_at_5
+      value: 15.443999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 31.595000000000002
+    - type: map_at_10
+      value: 47.815999999999995
+    - type: map_at_100
+      value: 48.811
+    - type: map_at_1000
+      value: 48.835
+    - type: map_at_3
+      value: 43.225
+    - type: map_at_5
+      value: 46.017
+    - type: mrr_at_1
+      value: 35.689
+    - type: mrr_at_10
+      value: 50.341
+    - type: mrr_at_100
+      value: 51.044999999999995
+    - type: mrr_at_1000
+      value: 51.062
+    - type: mrr_at_3
+      value: 46.553
+    - type: mrr_at_5
+      value: 48.918
+    - type: ndcg_at_1
+      value: 35.66
+    - type: ndcg_at_10
+      value: 55.859
+    - type: ndcg_at_100
+      value: 59.864
+    - type: ndcg_at_1000
+      value: 60.419999999999995
+    - type: ndcg_at_3
+      value: 47.371
+    - type: ndcg_at_5
+      value: 51.995000000000005
+    - type: precision_at_1
+      value: 35.66
+    - type: precision_at_10
+      value: 9.27
+    - type: precision_at_100
+      value: 1.1520000000000001
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_3
+      value: 21.63
+    - type: precision_at_5
+      value: 15.655
+    - type: recall_at_1
+      value: 31.595000000000002
+    - type: recall_at_10
+      value: 77.704
+    - type: recall_at_100
+      value: 94.774
+    - type: recall_at_1000
+      value: 98.919
+    - type: recall_at_3
+      value: 56.052
+    - type: recall_at_5
+      value: 66.623
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 71.489
+    - type: map_at_10
+      value: 85.411
+    - type: map_at_100
+      value: 86.048
+    - type: map_at_1000
+      value: 86.064
+    - type: map_at_3
+      value: 82.587
+    - type: map_at_5
+      value: 84.339
+    - type: mrr_at_1
+      value: 82.28
+    - type: mrr_at_10
+      value: 88.27199999999999
+    - type: mrr_at_100
+      value: 88.362
+    - type: mrr_at_1000
+      value: 88.362
+    - type: mrr_at_3
+      value: 87.372
+    - type: mrr_at_5
+      value: 87.995
+    - type: ndcg_at_1
+      value: 82.27
+    - type: ndcg_at_10
+      value: 89.023
+    - type: ndcg_at_100
+      value: 90.191
+    - type: ndcg_at_1000
+      value: 90.266
+    - type: ndcg_at_3
+      value: 86.37
+    - type: ndcg_at_5
+      value: 87.804
+    - type: precision_at_1
+      value: 82.27
+    - type: precision_at_10
+      value: 13.469000000000001
+    - type: precision_at_100
+      value: 1.533
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 37.797
+    - type: precision_at_5
+      value: 24.734
+    - type: recall_at_1
+      value: 71.489
+    - type: recall_at_10
+      value: 95.824
+    - type: recall_at_100
+      value: 99.70599999999999
+    - type: recall_at_1000
+      value: 99.979
+    - type: recall_at_3
+      value: 88.099
+    - type: recall_at_5
+      value: 92.285
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 60.52398807444541
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 65.34855891507871
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.188000000000001
+    - type: map_at_10
+      value: 13.987
+    - type: map_at_100
+      value: 16.438
+    - type: map_at_1000
+      value: 16.829
+    - type: map_at_3
+      value: 9.767000000000001
+    - type: map_at_5
+      value: 11.912
+    - type: mrr_at_1
+      value: 25.6
+    - type: mrr_at_10
+      value: 37.744
+    - type: mrr_at_100
+      value: 38.847
+    - type: mrr_at_1000
+      value: 38.894
+    - type: mrr_at_3
+      value: 34.166999999999994
+    - type: mrr_at_5
+      value: 36.207
+    - type: ndcg_at_1
+      value: 25.6
+    - type: ndcg_at_10
+      value: 22.980999999999998
+    - type: ndcg_at_100
+      value: 32.039
+    - type: ndcg_at_1000
+      value: 38.157000000000004
+    - type: ndcg_at_3
+      value: 21.567
+    - type: ndcg_at_5
+      value: 19.070999999999998
+    - type: precision_at_1
+      value: 25.6
+    - type: precision_at_10
+      value: 12.02
+    - type: precision_at_100
+      value: 2.5100000000000002
+    - type: precision_at_1000
+      value: 0.396
+    - type: precision_at_3
+      value: 20.333000000000002
+    - type: precision_at_5
+      value: 16.98
+    - type: recall_at_1
+      value: 5.188000000000001
+    - type: recall_at_10
+      value: 24.372
+    - type: recall_at_100
+      value: 50.934999999999995
+    - type: recall_at_1000
+      value: 80.477
+    - type: recall_at_3
+      value: 12.363
+    - type: recall_at_5
+      value: 17.203
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.24286275535398
+    - type: cos_sim_spearman
+      value: 82.62333770991818
+    - type: euclidean_pearson
+      value: 84.60353717637284
+    - type: euclidean_spearman
+      value: 82.32990108810047
+    - type: manhattan_pearson
+      value: 84.6089049738196
+    - type: manhattan_spearman
+      value: 82.33361785438936
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.87428858503165
+    - type: cos_sim_spearman
+      value: 79.09145886519929
+    - type: euclidean_pearson
+      value: 86.42669231664036
+    - type: euclidean_spearman
+      value: 80.03127375435449
+    - type: manhattan_pearson
+      value: 86.41330338305022
+    - type: manhattan_spearman
+      value: 80.02492538673368
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.67912277322645
+    - type: cos_sim_spearman
+      value: 89.6171319711762
+    - type: euclidean_pearson
+      value: 86.56571917398725
+    - type: euclidean_spearman
+      value: 87.71216907898948
+    - type: manhattan_pearson
+      value: 86.57459050182473
+    - type: manhattan_spearman
+      value: 87.71916648349993
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.71957379085862
+    - type: cos_sim_spearman
+      value: 85.01784075851465
+    - type: euclidean_pearson
+      value: 84.7407848472801
+    - type: euclidean_spearman
+      value: 84.61063091345538
+    - type: manhattan_pearson
+      value: 84.71494352494403
+    - type: manhattan_spearman
+      value: 84.58772077604254
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.40508326325175
+    - type: cos_sim_spearman
+      value: 89.50912897763186
+    - type: euclidean_pearson
+      value: 87.82349070086627
+    - type: euclidean_spearman
+      value: 88.44179162727521
+    - type: manhattan_pearson
+      value: 87.80181927025595
+    - type: manhattan_spearman
+      value: 88.43205129636243
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.35846741715478
+    - type: cos_sim_spearman
+      value: 86.61172476741842
+    - type: euclidean_pearson
+      value: 84.60123125491637
+    - type: euclidean_spearman
+      value: 85.3001948141827
+    - type: manhattan_pearson
+      value: 84.56231142658329
+    - type: manhattan_spearman
+      value: 85.23579900798813
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.94539129818824
+    - type: cos_sim_spearman
+      value: 88.99349064256742
+    - type: euclidean_pearson
+      value: 88.7142444640351
+    - type: euclidean_spearman
+      value: 88.34120813505011
+    - type: manhattan_pearson
+      value: 88.70363008238084
+    - type: manhattan_spearman
+      value: 88.31952816956954
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 68.29910260369893
+    - type: cos_sim_spearman
+      value: 68.79263346213466
+    - type: euclidean_pearson
+      value: 68.41627521422252
+    - type: euclidean_spearman
+      value: 66.61602587398579
+    - type: manhattan_pearson
+      value: 68.49402183447361
+    - type: manhattan_spearman
+      value: 66.80157792354453
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.43703906343708
+    - type: cos_sim_spearman
+      value: 89.06081805093662
+    - type: euclidean_pearson
+      value: 87.48311456299662
+    - type: euclidean_spearman
+      value: 88.07417597580013
+    - type: manhattan_pearson
+      value: 87.48202249768894
+    - type: manhattan_spearman
+      value: 88.04758031111642
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 87.49080620485203
+    - type: mrr
+      value: 96.19145378949301
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 59.317
+    - type: map_at_10
+      value: 69.296
+    - type: map_at_100
+      value: 69.738
+    - type: map_at_1000
+      value: 69.759
+    - type: map_at_3
+      value: 66.12599999999999
+    - type: map_at_5
+      value: 67.532
+    - type: mrr_at_1
+      value: 62
+    - type: mrr_at_10
+      value: 70.176
+    - type: mrr_at_100
+      value: 70.565
+    - type: mrr_at_1000
+      value: 70.583
+    - type: mrr_at_3
+      value: 67.833
+    - type: mrr_at_5
+      value: 68.93299999999999
+    - type: ndcg_at_1
+      value: 62
+    - type: ndcg_at_10
+      value: 74.069
+    - type: ndcg_at_100
+      value: 76.037
+    - type: ndcg_at_1000
+      value: 76.467
+    - type: ndcg_at_3
+      value: 68.628
+    - type: ndcg_at_5
+      value: 70.57600000000001
+    - type: precision_at_1
+      value: 62
+    - type: precision_at_10
+      value: 10
+    - type: precision_at_100
+      value: 1.097
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 26.667
+    - type: precision_at_5
+      value: 17.4
+    - type: recall_at_1
+      value: 59.317
+    - type: recall_at_10
+      value: 87.822
+    - type: recall_at_100
+      value: 96.833
+    - type: recall_at_1000
+      value: 100
+    - type: recall_at_3
+      value: 73.06099999999999
+    - type: recall_at_5
+      value: 77.928
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.88910891089108
+    - type: cos_sim_ap
+      value: 97.236958456951
+    - type: cos_sim_f1
+      value: 94.39999999999999
+    - type: cos_sim_precision
+      value: 94.39999999999999
+    - type: cos_sim_recall
+      value: 94.39999999999999
+    - type: dot_accuracy
+      value: 99.82574257425742
+    - type: dot_ap
+      value: 94.94344759441888
+    - type: dot_f1
+      value: 91.17352056168507
+    - type: dot_precision
+      value: 91.44869215291752
+    - type: dot_recall
+      value: 90.9
+    - type: euclidean_accuracy
+      value: 99.88415841584158
+    - type: euclidean_ap
+      value: 97.2044250782305
+    - type: euclidean_f1
+      value: 94.210786739238
+    - type: euclidean_precision
+      value: 93.24191968658178
+    - type: euclidean_recall
+      value: 95.19999999999999
+    - type: manhattan_accuracy
+      value: 99.88613861386139
+    - type: manhattan_ap
+      value: 97.20683205497689
+    - type: manhattan_f1
+      value: 94.2643391521197
+    - type: manhattan_precision
+      value: 94.02985074626866
+    - type: manhattan_recall
+      value: 94.5
+    - type: max_accuracy
+      value: 99.88910891089108
+    - type: max_ap
+      value: 97.236958456951
+    - type: max_f1
+      value: 94.39999999999999
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 66.53940781726187
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 36.71865011295108
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 55.3218674533331
+    - type: mrr
+      value: 56.28279910449028
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.723915667479673
+    - type: cos_sim_spearman
+      value: 32.029070449745234
+    - type: dot_pearson
+      value: 28.864944212481454
+    - type: dot_spearman
+      value: 27.939266999596725
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.231
+    - type: map_at_10
+      value: 1.949
+    - type: map_at_100
+      value: 10.023
+    - type: map_at_1000
+      value: 23.485
+    - type: map_at_3
+      value: 0.652
+    - type: map_at_5
+      value: 1.054
+    - type: mrr_at_1
+      value: 86
+    - type: mrr_at_10
+      value: 92.067
+    - type: mrr_at_100
+      value: 92.067
+    - type: mrr_at_1000
+      value: 92.067
+    - type: mrr_at_3
+      value: 91.667
+    - type: mrr_at_5
+      value: 92.067
+    - type: ndcg_at_1
+      value: 83
+    - type: ndcg_at_10
+      value: 76.32900000000001
+    - type: ndcg_at_100
+      value: 54.662
+    - type: ndcg_at_1000
+      value: 48.062
+    - type: ndcg_at_3
+      value: 81.827
+    - type: ndcg_at_5
+      value: 80.664
+    - type: precision_at_1
+      value: 86
+    - type: precision_at_10
+      value: 80
+    - type: precision_at_100
+      value: 55.48
+    - type: precision_at_1000
+      value: 20.938000000000002
+    - type: precision_at_3
+      value: 85.333
+    - type: precision_at_5
+      value: 84.39999999999999
+    - type: recall_at_1
+      value: 0.231
+    - type: recall_at_10
+      value: 2.158
+    - type: recall_at_100
+      value: 13.344000000000001
+    - type: recall_at_1000
+      value: 44.31
+    - type: recall_at_3
+      value: 0.6779999999999999
+    - type: recall_at_5
+      value: 1.13
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 2.524
+    - type: map_at_10
+      value: 10.183
+    - type: map_at_100
+      value: 16.625
+    - type: map_at_1000
+      value: 18.017
+    - type: map_at_3
+      value: 5.169
+    - type: map_at_5
+      value: 6.772
+    - type: mrr_at_1
+      value: 32.653
+    - type: mrr_at_10
+      value: 47.128
+    - type: mrr_at_100
+      value: 48.458
+    - type: mrr_at_1000
+      value: 48.473
+    - type: mrr_at_3
+      value: 44.897999999999996
+    - type: mrr_at_5
+      value: 45.306000000000004
+    - type: ndcg_at_1
+      value: 30.612000000000002
+    - type: ndcg_at_10
+      value: 24.928
+    - type: ndcg_at_100
+      value: 37.613
+    - type: ndcg_at_1000
+      value: 48.528
+    - type: ndcg_at_3
+      value: 28.829
+    - type: ndcg_at_5
+      value: 25.237
+    - type: precision_at_1
+      value: 32.653
+    - type: precision_at_10
+      value: 22.448999999999998
+    - type: precision_at_100
+      value: 8.02
+    - type: precision_at_1000
+      value: 1.537
+    - type: precision_at_3
+      value: 30.612000000000002
+    - type: precision_at_5
+      value: 24.490000000000002
+    - type: recall_at_1
+      value: 2.524
+    - type: recall_at_10
+      value: 16.38
+    - type: recall_at_100
+      value: 49.529
+    - type: recall_at_1000
+      value: 83.598
+    - type: recall_at_3
+      value: 6.411
+    - type: recall_at_5
+      value: 8.932
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 71.09020000000001
+    - type: ap
+      value: 14.451710060978993
+    - type: f1
+      value: 54.7874410609049
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 59.745331069609506
+    - type: f1
+      value: 60.08387848592697
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 51.71549485462037
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 87.39345532574357
+    - type: cos_sim_ap
+      value: 78.16796549696478
+    - type: cos_sim_f1
+      value: 71.27713276123171
+    - type: cos_sim_precision
+      value: 68.3115626511853
+    - type: cos_sim_recall
+      value: 74.51187335092348
+    - type: dot_accuracy
+      value: 85.12248912201228
+    - type: dot_ap
+      value: 69.26039256107077
+    - type: dot_f1
+      value: 65.04294321240867
+    - type: dot_precision
+      value: 63.251059586138126
+    - type: dot_recall
+      value: 66.93931398416886
+    - type: euclidean_accuracy
+      value: 87.07754664123503
+    - type: euclidean_ap
+      value: 77.7872176038945
+    - type: euclidean_f1
+      value: 70.85587801278899
+    - type: euclidean_precision
+      value: 66.3519115614924
+    - type: euclidean_recall
+      value: 76.01583113456465
+    - type: manhattan_accuracy
+      value: 87.07754664123503
+    - type: manhattan_ap
+      value: 77.7341400185556
+    - type: manhattan_f1
+      value: 70.80310880829015
+    - type: manhattan_precision
+      value: 69.54198473282443
+    - type: manhattan_recall
+      value: 72.1108179419525
+    - type: max_accuracy
+      value: 87.39345532574357
+    - type: max_ap
+      value: 78.16796549696478
+    - type: max_f1
+      value: 71.27713276123171
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.09457833663213
+    - type: cos_sim_ap
+      value: 86.33024314706873
+    - type: cos_sim_f1
+      value: 78.59623733719248
+    - type: cos_sim_precision
+      value: 74.13322413322413
+    - type: cos_sim_recall
+      value: 83.63104404065291
+    - type: dot_accuracy
+      value: 88.3086894089339
+    - type: dot_ap
+      value: 83.92225241805097
+    - type: dot_f1
+      value: 76.8721826377781
+    - type: dot_precision
+      value: 72.8168044077135
+    - type: dot_recall
+      value: 81.40591315060055
+    - type: euclidean_accuracy
+      value: 88.77052043311213
+    - type: euclidean_ap
+      value: 85.7410710218755
+    - type: euclidean_f1
+      value: 77.97705489398781
+    - type: euclidean_precision
+      value: 73.77713657598241
+    - type: euclidean_recall
+      value: 82.68401601478288
+    - type: manhattan_accuracy
+      value: 88.73753250281368
+    - type: manhattan_ap
+      value: 85.72867199072802
+    - type: manhattan_f1
+      value: 77.89774182922812
+    - type: manhattan_precision
+      value: 74.23787931635857
+    - type: manhattan_recall
+      value: 81.93717277486911
+    - type: max_accuracy
+      value: 89.09457833663213
+    - type: max_ap
+      value: 86.33024314706873
+    - type: max_f1
+      value: 78.59623733719248
 license: mit
+language:
+- en
 ---
+
+
+# [Universal AnglE Embedding](https://github.com/SeanLee97/AnglE)
+
+Follow us on:
+
+- GitHub: https://github.com/SeanLee97/AnglE.
+- Arxiv: https://arxiv.org/abs/2309.12871
+
+
+🔥 Our universal English sentence embedding `WhereIsAI/UAE-Large-V1` achieves **SOTA** on the [MTEB Leaderboard](https://huggingface.co/spaces/mteb/leaderboard) with an average score of 64.64!
+
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/635cc29de7aef2358a9b03ee/jY3tr0DCMdyJXOihSqJFr.jpeg)
+
+
+# Usage
+
+
+```bash
+python -m pip install -U angle-emb
+```
+
+1) Non-Retrieval Tasks
+
+```python
+from angle_emb import AnglE
+
+angle = AnglE.from_pretrained('WhereIsAI/UAE-Large-V1', pooling_strategy='cls').cuda()
+vec = angle.encode('hello world', to_numpy=True)
+print(vec)
+vecs = angle.encode(['hello world1', 'hello world2'], to_numpy=True)
+print(vecs)
+```
+
+2) Retrieval Tasks
+
+For retrieval purposes, please use the prompt `Prompts.C`.
+
+```python
+from angle_emb import AnglE, Prompts
+
+angle = AnglE.from_pretrained('WhereIsAI/UAE-Large-V1', pooling_strategy='cls').cuda()
+angle.set_prompt(prompt=Prompts.C)
+vec = angle.encode({'text': 'hello world'}, to_numpy=True)
+print(vec)
+vecs = angle.encode([{'text': 'hello world1'}, {'text': 'hello world2'}], to_numpy=True)
+print(vecs)
+```
+
+# Citation 
+
+If you use our pre-trained models, welcome to support us by citing our work:
+
+```
+@article{li2023angle,
+  title={AnglE-optimized Text Embeddings},
+  author={Li, Xianming and Li, Jing},
+  journal={arXiv preprint arXiv:2309.12871},
+  year={2023}
+}
+```

config.json

@@ -0,0 +1,32 @@
+{
+  "_name_or_path": "UAE-Large-V1",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.2",
+  "type_vocab_size": 2,
+  "use_cache": false,
+  "vocab_size": 30522
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2b55399b31b1dec003f7047bfe2a3508a1c16c7cc1f61e962f09903fbb0add63
+size 135

onnx/model.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4b08d8db5fa21210ea5d193c5bb65ad2a2272a7016a6d544a71a065a52e5a92a
+size 135

onnx/model_quantized.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0dc2e43f3ec239d65f470898ce660b23d5a62340c3c51eb5ee11d1d8ba23ee67
+size 134

special_tokens_map.json

@@ -0,0 +1,7 @@
+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

@@ -0,0 +1,57 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}