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1_Pooling/config.json

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+{
+  "word_embedding_dimension": 384,
+  "pooling_mode_cls_token": false,
+  "pooling_mode_mean_tokens": true,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false
+}

README.md

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+---
+model-index:
+- name: gte_tiny
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 71.76119402985076
+    - type: ap
+      value: 34.63659287952359
+    - type: f1
+      value: 65.88939512571113
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 86.61324999999998
+    - type: ap
+      value: 81.7476302802319
+    - type: f1
+      value: 86.5863470912001
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 42.61000000000001
+    - type: f1
+      value: 42.2217180000715
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.377999999999997
+    - type: map_at_10
+      value: 44.565
+    - type: map_at_100
+      value: 45.48
+    - type: map_at_1000
+      value: 45.487
+    - type: map_at_3
+      value: 39.841
+    - type: map_at_5
+      value: 42.284
+    - type: mrr_at_1
+      value: 29.445
+    - type: mrr_at_10
+      value: 44.956
+    - type: mrr_at_100
+      value: 45.877
+    - type: mrr_at_1000
+      value: 45.884
+    - type: mrr_at_3
+      value: 40.209
+    - type: mrr_at_5
+      value: 42.719
+    - type: ndcg_at_1
+      value: 28.377999999999997
+    - type: ndcg_at_10
+      value: 53.638
+    - type: ndcg_at_100
+      value: 57.354000000000006
+    - type: ndcg_at_1000
+      value: 57.513000000000005
+    - type: ndcg_at_3
+      value: 43.701
+    - type: ndcg_at_5
+      value: 48.114000000000004
+    - type: precision_at_1
+      value: 28.377999999999997
+    - type: precision_at_10
+      value: 8.272
+    - type: precision_at_100
+      value: 0.984
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 18.303
+    - type: precision_at_5
+      value: 13.129
+    - type: recall_at_1
+      value: 28.377999999999997
+    - type: recall_at_10
+      value: 82.717
+    - type: recall_at_100
+      value: 98.43499999999999
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 54.908
+    - type: recall_at_5
+      value: 65.647
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 46.637318326729876
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 36.01134479855804
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 59.82917555338909
+    - type: mrr
+      value: 74.7888361254012
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.1657730995964
+    - type: cos_sim_spearman
+      value: 86.62787748941281
+    - type: euclidean_pearson
+      value: 85.48127914481798
+    - type: euclidean_spearman
+      value: 86.48148861167424
+    - type: manhattan_pearson
+      value: 85.07496934780823
+    - type: manhattan_spearman
+      value: 86.39473964708843
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 81.73051948051948
+    - type: f1
+      value: 81.66368364988331
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 39.18623707448217
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 32.12697757150375
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 29.160000000000004
+    - type: map_at_10
+      value: 40.474
+    - type: map_at_100
+      value: 41.905
+    - type: map_at_1000
+      value: 42.041000000000004
+    - type: map_at_3
+      value: 37.147000000000006
+    - type: map_at_5
+      value: 38.873999999999995
+    - type: mrr_at_1
+      value: 36.91
+    - type: mrr_at_10
+      value: 46.495999999999995
+    - type: mrr_at_100
+      value: 47.288000000000004
+    - type: mrr_at_1000
+      value: 47.339999999999996
+    - type: mrr_at_3
+      value: 43.777
+    - type: mrr_at_5
+      value: 45.257999999999996
+    - type: ndcg_at_1
+      value: 36.91
+    - type: ndcg_at_10
+      value: 46.722
+    - type: ndcg_at_100
+      value: 51.969
+    - type: ndcg_at_1000
+      value: 54.232
+    - type: ndcg_at_3
+      value: 41.783
+    - type: ndcg_at_5
+      value: 43.797000000000004
+    - type: precision_at_1
+      value: 36.91
+    - type: precision_at_10
+      value: 9.013
+    - type: precision_at_100
+      value: 1.455
+    - type: precision_at_1000
+      value: 0.193
+    - type: precision_at_3
+      value: 20.124
+    - type: precision_at_5
+      value: 14.363000000000001
+    - type: recall_at_1
+      value: 29.160000000000004
+    - type: recall_at_10
+      value: 58.521
+    - type: recall_at_100
+      value: 80.323
+    - type: recall_at_1000
+      value: 95.13000000000001
+    - type: recall_at_3
+      value: 44.205
+    - type: recall_at_5
+      value: 49.97
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.750000000000004
+    - type: map_at_10
+      value: 36.39
+    - type: map_at_100
+      value: 37.5
+    - type: map_at_1000
+      value: 37.625
+    - type: map_at_3
+      value: 33.853
+    - type: map_at_5
+      value: 35.397
+    - type: mrr_at_1
+      value: 34.14
+    - type: mrr_at_10
+      value: 41.841
+    - type: mrr_at_100
+      value: 42.469
+    - type: mrr_at_1000
+      value: 42.521
+    - type: mrr_at_3
+      value: 39.724
+    - type: mrr_at_5
+      value: 40.955999999999996
+    - type: ndcg_at_1
+      value: 34.14
+    - type: ndcg_at_10
+      value: 41.409
+    - type: ndcg_at_100
+      value: 45.668
+    - type: ndcg_at_1000
+      value: 47.916
+    - type: ndcg_at_3
+      value: 37.836
+    - type: ndcg_at_5
+      value: 39.650999999999996
+    - type: precision_at_1
+      value: 34.14
+    - type: precision_at_10
+      value: 7.739
+    - type: precision_at_100
+      value: 1.2630000000000001
+    - type: precision_at_1000
+      value: 0.173
+    - type: precision_at_3
+      value: 18.217
+    - type: precision_at_5
+      value: 12.854
+    - type: recall_at_1
+      value: 27.750000000000004
+    - type: recall_at_10
+      value: 49.882
+    - type: recall_at_100
+      value: 68.556
+    - type: recall_at_1000
+      value: 83.186
+    - type: recall_at_3
+      value: 39.047
+    - type: recall_at_5
+      value: 44.458
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 36.879
+    - type: map_at_10
+      value: 48.878
+    - type: map_at_100
+      value: 49.918
+    - type: map_at_1000
+      value: 49.978
+    - type: map_at_3
+      value: 45.867999999999995
+    - type: map_at_5
+      value: 47.637
+    - type: mrr_at_1
+      value: 42.696
+    - type: mrr_at_10
+      value: 52.342
+    - type: mrr_at_100
+      value: 53.044000000000004
+    - type: mrr_at_1000
+      value: 53.077
+    - type: mrr_at_3
+      value: 50.01
+    - type: mrr_at_5
+      value: 51.437
+    - type: ndcg_at_1
+      value: 42.696
+    - type: ndcg_at_10
+      value: 54.469
+    - type: ndcg_at_100
+      value: 58.664
+    - type: ndcg_at_1000
+      value: 59.951
+    - type: ndcg_at_3
+      value: 49.419999999999995
+    - type: ndcg_at_5
+      value: 52.007000000000005
+    - type: precision_at_1
+      value: 42.696
+    - type: precision_at_10
+      value: 8.734
+    - type: precision_at_100
+      value: 1.1769999999999998
+    - type: precision_at_1000
+      value: 0.133
+    - type: precision_at_3
+      value: 22.027
+    - type: precision_at_5
+      value: 15.135000000000002
+    - type: recall_at_1
+      value: 36.879
+    - type: recall_at_10
+      value: 67.669
+    - type: recall_at_100
+      value: 85.822
+    - type: recall_at_1000
+      value: 95.092
+    - type: recall_at_3
+      value: 54.157999999999994
+    - type: recall_at_5
+      value: 60.436
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.942
+    - type: map_at_10
+      value: 31.741999999999997
+    - type: map_at_100
+      value: 32.721000000000004
+    - type: map_at_1000
+      value: 32.809
+    - type: map_at_3
+      value: 29.17
+    - type: map_at_5
+      value: 30.714000000000002
+    - type: mrr_at_1
+      value: 24.746000000000002
+    - type: mrr_at_10
+      value: 33.517
+    - type: mrr_at_100
+      value: 34.451
+    - type: mrr_at_1000
+      value: 34.522000000000006
+    - type: mrr_at_3
+      value: 31.148999999999997
+    - type: mrr_at_5
+      value: 32.606
+    - type: ndcg_at_1
+      value: 24.746000000000002
+    - type: ndcg_at_10
+      value: 36.553000000000004
+    - type: ndcg_at_100
+      value: 41.53
+    - type: ndcg_at_1000
+      value: 43.811
+    - type: ndcg_at_3
+      value: 31.674000000000003
+    - type: ndcg_at_5
+      value: 34.241
+    - type: precision_at_1
+      value: 24.746000000000002
+    - type: precision_at_10
+      value: 5.684
+    - type: precision_at_100
+      value: 0.859
+    - type: precision_at_1000
+      value: 0.109
+    - type: precision_at_3
+      value: 13.597000000000001
+    - type: precision_at_5
+      value: 9.672
+    - type: recall_at_1
+      value: 22.942
+    - type: recall_at_10
+      value: 49.58
+    - type: recall_at_100
+      value: 72.614
+    - type: recall_at_1000
+      value: 89.89200000000001
+    - type: recall_at_3
+      value: 36.552
+    - type: recall_at_5
+      value: 42.702
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 15.345
+    - type: map_at_10
+      value: 22.428
+    - type: map_at_100
+      value: 23.756
+    - type: map_at_1000
+      value: 23.872
+    - type: map_at_3
+      value: 20.212
+    - type: map_at_5
+      value: 21.291
+    - type: mrr_at_1
+      value: 19.279
+    - type: mrr_at_10
+      value: 27.1
+    - type: mrr_at_100
+      value: 28.211000000000002
+    - type: mrr_at_1000
+      value: 28.279
+    - type: mrr_at_3
+      value: 24.813
+    - type: mrr_at_5
+      value: 25.889
+    - type: ndcg_at_1
+      value: 19.279
+    - type: ndcg_at_10
+      value: 27.36
+    - type: ndcg_at_100
+      value: 33.499
+    - type: ndcg_at_1000
+      value: 36.452
+    - type: ndcg_at_3
+      value: 23.233999999999998
+    - type: ndcg_at_5
+      value: 24.806
+    - type: precision_at_1
+      value: 19.279
+    - type: precision_at_10
+      value: 5.149
+    - type: precision_at_100
+      value: 0.938
+    - type: precision_at_1000
+      value: 0.133
+    - type: precision_at_3
+      value: 11.360000000000001
+    - type: precision_at_5
+      value: 8.035
+    - type: recall_at_1
+      value: 15.345
+    - type: recall_at_10
+      value: 37.974999999999994
+    - type: recall_at_100
+      value: 64.472
+    - type: recall_at_1000
+      value: 85.97200000000001
+    - type: recall_at_3
+      value: 26.203
+    - type: recall_at_5
+      value: 30.485
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.362000000000002
+    - type: map_at_10
+      value: 36.406
+    - type: map_at_100
+      value: 37.726
+    - type: map_at_1000
+      value: 37.84
+    - type: map_at_3
+      value: 33.425
+    - type: map_at_5
+      value: 35.043
+    - type: mrr_at_1
+      value: 32.146
+    - type: mrr_at_10
+      value: 41.674
+    - type: mrr_at_100
+      value: 42.478
+    - type: mrr_at_1000
+      value: 42.524
+    - type: mrr_at_3
+      value: 38.948
+    - type: mrr_at_5
+      value: 40.415
+    - type: ndcg_at_1
+      value: 32.146
+    - type: ndcg_at_10
+      value: 42.374
+    - type: ndcg_at_100
+      value: 47.919
+    - type: ndcg_at_1000
+      value: 50.013
+    - type: ndcg_at_3
+      value: 37.29
+    - type: ndcg_at_5
+      value: 39.531
+    - type: precision_at_1
+      value: 32.146
+    - type: precision_at_10
+      value: 7.767
+    - type: precision_at_100
+      value: 1.236
+    - type: precision_at_1000
+      value: 0.16
+    - type: precision_at_3
+      value: 17.965999999999998
+    - type: precision_at_5
+      value: 12.742999999999999
+    - type: recall_at_1
+      value: 26.362000000000002
+    - type: recall_at_10
+      value: 54.98800000000001
+    - type: recall_at_100
+      value: 78.50200000000001
+    - type: recall_at_1000
+      value: 92.146
+    - type: recall_at_3
+      value: 40.486
+    - type: recall_at_5
+      value: 46.236
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.417
+    - type: map_at_10
+      value: 33.161
+    - type: map_at_100
+      value: 34.357
+    - type: map_at_1000
+      value: 34.473
+    - type: map_at_3
+      value: 30.245
+    - type: map_at_5
+      value: 31.541999999999998
+    - type: mrr_at_1
+      value: 29.909000000000002
+    - type: mrr_at_10
+      value: 38.211
+    - type: mrr_at_100
+      value: 39.056999999999995
+    - type: mrr_at_1000
+      value: 39.114
+    - type: mrr_at_3
+      value: 35.769
+    - type: mrr_at_5
+      value: 36.922
+    - type: ndcg_at_1
+      value: 29.909000000000002
+    - type: ndcg_at_10
+      value: 38.694
+    - type: ndcg_at_100
+      value: 44.057
+    - type: ndcg_at_1000
+      value: 46.6
+    - type: ndcg_at_3
+      value: 33.822
+    - type: ndcg_at_5
+      value: 35.454
+    - type: precision_at_1
+      value: 29.909000000000002
+    - type: precision_at_10
+      value: 7.180000000000001
+    - type: precision_at_100
+      value: 1.153
+    - type: precision_at_1000
+      value: 0.155
+    - type: precision_at_3
+      value: 16.134
+    - type: precision_at_5
+      value: 11.256
+    - type: recall_at_1
+      value: 24.417
+    - type: recall_at_10
+      value: 50.260000000000005
+    - type: recall_at_100
+      value: 73.55699999999999
+    - type: recall_at_1000
+      value: 91.216
+    - type: recall_at_3
+      value: 35.971
+    - type: recall_at_5
+      value: 40.793
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.266916666666663
+    - type: map_at_10
+      value: 32.75025
+    - type: map_at_100
+      value: 33.91341666666667
+    - type: map_at_1000
+      value: 34.031749999999995
+    - type: map_at_3
+      value: 30.166416666666674
+    - type: map_at_5
+      value: 31.577000000000005
+    - type: mrr_at_1
+      value: 28.828166666666664
+    - type: mrr_at_10
+      value: 36.80991666666667
+    - type: mrr_at_100
+      value: 37.67075
+    - type: mrr_at_1000
+      value: 37.733
+    - type: mrr_at_3
+      value: 34.513416666666664
+    - type: mrr_at_5
+      value: 35.788
+    - type: ndcg_at_1
+      value: 28.828166666666664
+    - type: ndcg_at_10
+      value: 37.796
+    - type: ndcg_at_100
+      value: 42.94783333333333
+    - type: ndcg_at_1000
+      value: 45.38908333333333
+    - type: ndcg_at_3
+      value: 33.374750000000006
+    - type: ndcg_at_5
+      value: 35.379666666666665
+    - type: precision_at_1
+      value: 28.828166666666664
+    - type: precision_at_10
+      value: 6.615749999999999
+    - type: precision_at_100
+      value: 1.0848333333333333
+    - type: precision_at_1000
+      value: 0.1484166666666667
+    - type: precision_at_3
+      value: 15.347833333333332
+    - type: precision_at_5
+      value: 10.848916666666666
+    - type: recall_at_1
+      value: 24.266916666666663
+    - type: recall_at_10
+      value: 48.73458333333333
+    - type: recall_at_100
+      value: 71.56341666666667
+    - type: recall_at_1000
+      value: 88.63091666666668
+    - type: recall_at_3
+      value: 36.31208333333333
+    - type: recall_at_5
+      value: 41.55633333333333
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.497
+    - type: map_at_10
+      value: 30.249
+    - type: map_at_100
+      value: 30.947000000000003
+    - type: map_at_1000
+      value: 31.049
+    - type: map_at_3
+      value: 28.188000000000002
+    - type: map_at_5
+      value: 29.332
+    - type: mrr_at_1
+      value: 26.687
+    - type: mrr_at_10
+      value: 33.182
+    - type: mrr_at_100
+      value: 33.794999999999995
+    - type: mrr_at_1000
+      value: 33.873
+    - type: mrr_at_3
+      value: 31.263
+    - type: mrr_at_5
+      value: 32.428000000000004
+    - type: ndcg_at_1
+      value: 26.687
+    - type: ndcg_at_10
+      value: 34.252
+    - type: ndcg_at_100
+      value: 38.083
+    - type: ndcg_at_1000
+      value: 40.682
+    - type: ndcg_at_3
+      value: 30.464999999999996
+    - type: ndcg_at_5
+      value: 32.282
+    - type: precision_at_1
+      value: 26.687
+    - type: precision_at_10
+      value: 5.2909999999999995
+    - type: precision_at_100
+      value: 0.788
+    - type: precision_at_1000
+      value: 0.109
+    - type: precision_at_3
+      value: 13.037
+    - type: precision_at_5
+      value: 9.049
+    - type: recall_at_1
+      value: 23.497
+    - type: recall_at_10
+      value: 43.813
+    - type: recall_at_100
+      value: 61.88399999999999
+    - type: recall_at_1000
+      value: 80.926
+    - type: recall_at_3
+      value: 33.332
+    - type: recall_at_5
+      value: 37.862
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.073
+    - type: map_at_10
+      value: 22.705000000000002
+    - type: map_at_100
+      value: 23.703
+    - type: map_at_1000
+      value: 23.833
+    - type: map_at_3
+      value: 20.593
+    - type: map_at_5
+      value: 21.7
+    - type: mrr_at_1
+      value: 19.683
+    - type: mrr_at_10
+      value: 26.39
+    - type: mrr_at_100
+      value: 27.264
+    - type: mrr_at_1000
+      value: 27.349
+    - type: mrr_at_3
+      value: 24.409
+    - type: mrr_at_5
+      value: 25.474000000000004
+    - type: ndcg_at_1
+      value: 19.683
+    - type: ndcg_at_10
+      value: 27.014
+    - type: ndcg_at_100
+      value: 31.948
+    - type: ndcg_at_1000
+      value: 35.125
+    - type: ndcg_at_3
+      value: 23.225
+    - type: ndcg_at_5
+      value: 24.866
+    - type: precision_at_1
+      value: 19.683
+    - type: precision_at_10
+      value: 4.948
+    - type: precision_at_100
+      value: 0.876
+    - type: precision_at_1000
+      value: 0.133
+    - type: precision_at_3
+      value: 10.943
+    - type: precision_at_5
+      value: 7.86
+    - type: recall_at_1
+      value: 16.073
+    - type: recall_at_10
+      value: 36.283
+    - type: recall_at_100
+      value: 58.745999999999995
+    - type: recall_at_1000
+      value: 81.711
+    - type: recall_at_3
+      value: 25.637
+    - type: recall_at_5
+      value: 29.919
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.776
+    - type: map_at_10
+      value: 33.317
+    - type: map_at_100
+      value: 34.437
+    - type: map_at_1000
+      value: 34.54
+    - type: map_at_3
+      value: 30.706
+    - type: map_at_5
+      value: 32.202999999999996
+    - type: mrr_at_1
+      value: 30.224
+    - type: mrr_at_10
+      value: 37.34
+    - type: mrr_at_100
+      value: 38.268
+    - type: mrr_at_1000
+      value: 38.335
+    - type: mrr_at_3
+      value: 35.075
+    - type: mrr_at_5
+      value: 36.348
+    - type: ndcg_at_1
+      value: 30.224
+    - type: ndcg_at_10
+      value: 38.083
+    - type: ndcg_at_100
+      value: 43.413000000000004
+    - type: ndcg_at_1000
+      value: 45.856
+    - type: ndcg_at_3
+      value: 33.437
+    - type: ndcg_at_5
+      value: 35.661
+    - type: precision_at_1
+      value: 30.224
+    - type: precision_at_10
+      value: 6.1850000000000005
+    - type: precision_at_100
+      value: 1.0030000000000001
+    - type: precision_at_1000
+      value: 0.132
+    - type: precision_at_3
+      value: 14.646
+    - type: precision_at_5
+      value: 10.428999999999998
+    - type: recall_at_1
+      value: 25.776
+    - type: recall_at_10
+      value: 48.787000000000006
+    - type: recall_at_100
+      value: 72.04899999999999
+    - type: recall_at_1000
+      value: 89.339
+    - type: recall_at_3
+      value: 36.192
+    - type: recall_at_5
+      value: 41.665
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.156
+    - type: map_at_10
+      value: 30.886000000000003
+    - type: map_at_100
+      value: 32.551
+    - type: map_at_1000
+      value: 32.769
+    - type: map_at_3
+      value: 28.584
+    - type: map_at_5
+      value: 29.959999999999997
+    - type: mrr_at_1
+      value: 28.260999999999996
+    - type: mrr_at_10
+      value: 35.555
+    - type: mrr_at_100
+      value: 36.687
+    - type: mrr_at_1000
+      value: 36.742999999999995
+    - type: mrr_at_3
+      value: 33.531
+    - type: mrr_at_5
+      value: 34.717
+    - type: ndcg_at_1
+      value: 28.260999999999996
+    - type: ndcg_at_10
+      value: 36.036
+    - type: ndcg_at_100
+      value: 42.675000000000004
+    - type: ndcg_at_1000
+      value: 45.303
+    - type: ndcg_at_3
+      value: 32.449
+    - type: ndcg_at_5
+      value: 34.293
+    - type: precision_at_1
+      value: 28.260999999999996
+    - type: precision_at_10
+      value: 6.837999999999999
+    - type: precision_at_100
+      value: 1.4569999999999999
+    - type: precision_at_1000
+      value: 0.23500000000000001
+    - type: precision_at_3
+      value: 15.217
+    - type: precision_at_5
+      value: 11.028
+    - type: recall_at_1
+      value: 23.156
+    - type: recall_at_10
+      value: 45.251999999999995
+    - type: recall_at_100
+      value: 75.339
+    - type: recall_at_1000
+      value: 91.56
+    - type: recall_at_3
+      value: 34.701
+    - type: recall_at_5
+      value: 39.922999999999995
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 19.846
+    - type: map_at_10
+      value: 26.367
+    - type: map_at_100
+      value: 27.439999999999998
+    - type: map_at_1000
+      value: 27.552
+    - type: map_at_3
+      value: 24.006
+    - type: map_at_5
+      value: 25.230999999999998
+    - type: mrr_at_1
+      value: 21.257
+    - type: mrr_at_10
+      value: 28.071
+    - type: mrr_at_100
+      value: 29.037000000000003
+    - type: mrr_at_1000
+      value: 29.119
+    - type: mrr_at_3
+      value: 25.692999999999998
+    - type: mrr_at_5
+      value: 27.006000000000004
+    - type: ndcg_at_1
+      value: 21.257
+    - type: ndcg_at_10
+      value: 30.586000000000002
+    - type: ndcg_at_100
+      value: 35.949
+    - type: ndcg_at_1000
+      value: 38.728
+    - type: ndcg_at_3
+      value: 25.862000000000002
+    - type: ndcg_at_5
+      value: 27.967
+    - type: precision_at_1
+      value: 21.257
+    - type: precision_at_10
+      value: 4.861
+    - type: precision_at_100
+      value: 0.8130000000000001
+    - type: precision_at_1000
+      value: 0.116
+    - type: precision_at_3
+      value: 10.906
+    - type: precision_at_5
+      value: 7.763000000000001
+    - type: recall_at_1
+      value: 19.846
+    - type: recall_at_10
+      value: 41.805
+    - type: recall_at_100
+      value: 66.89699999999999
+    - type: recall_at_1000
+      value: 87.401
+    - type: recall_at_3
+      value: 29.261
+    - type: recall_at_5
+      value: 34.227000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 10.333
+    - type: map_at_10
+      value: 17.14
+    - type: map_at_100
+      value: 18.878
+    - type: map_at_1000
+      value: 19.067
+    - type: map_at_3
+      value: 14.123
+    - type: map_at_5
+      value: 15.699
+    - type: mrr_at_1
+      value: 23.192
+    - type: mrr_at_10
+      value: 33.553
+    - type: mrr_at_100
+      value: 34.553
+    - type: mrr_at_1000
+      value: 34.603
+    - type: mrr_at_3
+      value: 29.848000000000003
+    - type: mrr_at_5
+      value: 32.18
+    - type: ndcg_at_1
+      value: 23.192
+    - type: ndcg_at_10
+      value: 24.707
+    - type: ndcg_at_100
+      value: 31.701
+    - type: ndcg_at_1000
+      value: 35.260999999999996
+    - type: ndcg_at_3
+      value: 19.492
+    - type: ndcg_at_5
+      value: 21.543
+    - type: precision_at_1
+      value: 23.192
+    - type: precision_at_10
+      value: 7.824000000000001
+    - type: precision_at_100
+      value: 1.52
+    - type: precision_at_1000
+      value: 0.218
+    - type: precision_at_3
+      value: 14.180000000000001
+    - type: precision_at_5
+      value: 11.530999999999999
+    - type: recall_at_1
+      value: 10.333
+    - type: recall_at_10
+      value: 30.142999999999997
+    - type: recall_at_100
+      value: 54.298
+    - type: recall_at_1000
+      value: 74.337
+    - type: recall_at_3
+      value: 17.602999999999998
+    - type: recall_at_5
+      value: 22.938
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 8.03
+    - type: map_at_10
+      value: 17.345
+    - type: map_at_100
+      value: 23.462
+    - type: map_at_1000
+      value: 24.77
+    - type: map_at_3
+      value: 12.714
+    - type: map_at_5
+      value: 14.722
+    - type: mrr_at_1
+      value: 61.0
+    - type: mrr_at_10
+      value: 69.245
+    - type: mrr_at_100
+      value: 69.715
+    - type: mrr_at_1000
+      value: 69.719
+    - type: mrr_at_3
+      value: 67.583
+    - type: mrr_at_5
+      value: 68.521
+    - type: ndcg_at_1
+      value: 47.625
+    - type: ndcg_at_10
+      value: 35.973
+    - type: ndcg_at_100
+      value: 39.875
+    - type: ndcg_at_1000
+      value: 46.922000000000004
+    - type: ndcg_at_3
+      value: 40.574
+    - type: ndcg_at_5
+      value: 38.18
+    - type: precision_at_1
+      value: 61.0
+    - type: precision_at_10
+      value: 29.049999999999997
+    - type: precision_at_100
+      value: 8.828
+    - type: precision_at_1000
+      value: 1.8290000000000002
+    - type: precision_at_3
+      value: 45.333
+    - type: precision_at_5
+      value: 37.9
+    - type: recall_at_1
+      value: 8.03
+    - type: recall_at_10
+      value: 22.334
+    - type: recall_at_100
+      value: 45.919
+    - type: recall_at_1000
+      value: 68.822
+    - type: recall_at_3
+      value: 14.038999999999998
+    - type: recall_at_5
+      value: 17.118
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 44.714999999999996
+    - type: f1
+      value: 39.83929362259356
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 52.242999999999995
+    - type: map_at_10
+      value: 64.087
+    - type: map_at_100
+      value: 64.549
+    - type: map_at_1000
+      value: 64.567
+    - type: map_at_3
+      value: 61.667
+    - type: map_at_5
+      value: 63.266
+    - type: mrr_at_1
+      value: 56.271
+    - type: mrr_at_10
+      value: 68.146
+    - type: mrr_at_100
+      value: 68.524
+    - type: mrr_at_1000
+      value: 68.53200000000001
+    - type: mrr_at_3
+      value: 65.869
+    - type: mrr_at_5
+      value: 67.37100000000001
+    - type: ndcg_at_1
+      value: 56.271
+    - type: ndcg_at_10
+      value: 70.109
+    - type: ndcg_at_100
+      value: 72.09
+    - type: ndcg_at_1000
+      value: 72.479
+    - type: ndcg_at_3
+      value: 65.559
+    - type: ndcg_at_5
+      value: 68.242
+    - type: precision_at_1
+      value: 56.271
+    - type: precision_at_10
+      value: 9.286999999999999
+    - type: precision_at_100
+      value: 1.039
+    - type: precision_at_1000
+      value: 0.109
+    - type: precision_at_3
+      value: 26.308
+    - type: precision_at_5
+      value: 17.291
+    - type: recall_at_1
+      value: 52.242999999999995
+    - type: recall_at_10
+      value: 84.71
+    - type: recall_at_100
+      value: 93.309
+    - type: recall_at_1000
+      value: 96.013
+    - type: recall_at_3
+      value: 72.554
+    - type: recall_at_5
+      value: 79.069
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 14.346
+    - type: map_at_10
+      value: 24.552
+    - type: map_at_100
+      value: 26.161
+    - type: map_at_1000
+      value: 26.345000000000002
+    - type: map_at_3
+      value: 21.208
+    - type: map_at_5
+      value: 22.959
+    - type: mrr_at_1
+      value: 29.166999999999998
+    - type: mrr_at_10
+      value: 38.182
+    - type: mrr_at_100
+      value: 39.22
+    - type: mrr_at_1000
+      value: 39.263
+    - type: mrr_at_3
+      value: 35.983
+    - type: mrr_at_5
+      value: 37.14
+    - type: ndcg_at_1
+      value: 29.166999999999998
+    - type: ndcg_at_10
+      value: 31.421
+    - type: ndcg_at_100
+      value: 38.129999999999995
+    - type: ndcg_at_1000
+      value: 41.569
+    - type: ndcg_at_3
+      value: 28.172000000000004
+    - type: ndcg_at_5
+      value: 29.029
+    - type: precision_at_1
+      value: 29.166999999999998
+    - type: precision_at_10
+      value: 8.997
+    - type: precision_at_100
+      value: 1.5709999999999997
+    - type: precision_at_1000
+      value: 0.22
+    - type: precision_at_3
+      value: 19.187
+    - type: precision_at_5
+      value: 13.980999999999998
+    - type: recall_at_1
+      value: 14.346
+    - type: recall_at_10
+      value: 37.963
+    - type: recall_at_100
+      value: 63.43299999999999
+    - type: recall_at_1000
+      value: 84.057
+    - type: recall_at_3
+      value: 26.119999999999997
+    - type: recall_at_5
+      value: 30.988
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 33.059
+    - type: map_at_10
+      value: 46.421
+    - type: map_at_100
+      value: 47.323
+    - type: map_at_1000
+      value: 47.403
+    - type: map_at_3
+      value: 43.553999999999995
+    - type: map_at_5
+      value: 45.283
+    - type: mrr_at_1
+      value: 66.117
+    - type: mrr_at_10
+      value: 73.10900000000001
+    - type: mrr_at_100
+      value: 73.444
+    - type: mrr_at_1000
+      value: 73.46000000000001
+    - type: mrr_at_3
+      value: 71.70400000000001
+    - type: mrr_at_5
+      value: 72.58099999999999
+    - type: ndcg_at_1
+      value: 66.117
+    - type: ndcg_at_10
+      value: 55.696999999999996
+    - type: ndcg_at_100
+      value: 59.167
+    - type: ndcg_at_1000
+      value: 60.809000000000005
+    - type: ndcg_at_3
+      value: 51.243
+    - type: ndcg_at_5
+      value: 53.627
+    - type: precision_at_1
+      value: 66.117
+    - type: precision_at_10
+      value: 11.538
+    - type: precision_at_100
+      value: 1.429
+    - type: precision_at_1000
+      value: 0.165
+    - type: precision_at_3
+      value: 31.861
+    - type: precision_at_5
+      value: 20.997
+    - type: recall_at_1
+      value: 33.059
+    - type: recall_at_10
+      value: 57.691
+    - type: recall_at_100
+      value: 71.458
+    - type: recall_at_1000
+      value: 82.35
+    - type: recall_at_3
+      value: 47.792
+    - type: recall_at_5
+      value: 52.492000000000004
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 80.544
+    - type: ap
+      value: 74.69592367984956
+    - type: f1
+      value: 80.51138138449883
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.095
+    - type: map_at_10
+      value: 28.038999999999998
+    - type: map_at_100
+      value: 29.246
+    - type: map_at_1000
+      value: 29.311
+    - type: map_at_3
+      value: 24.253
+    - type: map_at_5
+      value: 26.442
+    - type: mrr_at_1
+      value: 17.535999999999998
+    - type: mrr_at_10
+      value: 28.53
+    - type: mrr_at_100
+      value: 29.697000000000003
+    - type: mrr_at_1000
+      value: 29.755
+    - type: mrr_at_3
+      value: 24.779999999999998
+    - type: mrr_at_5
+      value: 26.942
+    - type: ndcg_at_1
+      value: 17.549999999999997
+    - type: ndcg_at_10
+      value: 34.514
+    - type: ndcg_at_100
+      value: 40.497
+    - type: ndcg_at_1000
+      value: 42.17
+    - type: ndcg_at_3
+      value: 26.764
+    - type: ndcg_at_5
+      value: 30.678
+    - type: precision_at_1
+      value: 17.549999999999997
+    - type: precision_at_10
+      value: 5.692
+    - type: precision_at_100
+      value: 0.8699999999999999
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 11.562
+    - type: precision_at_5
+      value: 8.917
+    - type: recall_at_1
+      value: 17.095
+    - type: recall_at_10
+      value: 54.642
+    - type: recall_at_100
+      value: 82.652
+    - type: recall_at_1000
+      value: 95.555
+    - type: recall_at_3
+      value: 33.504
+    - type: recall_at_5
+      value: 42.925000000000004
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 91.75558595531236
+    - type: f1
+      value: 91.25979279648296
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 69.90424076607387
+    - type: f1
+      value: 52.067408707562244
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 70.13449899125757
+    - type: f1
+      value: 67.62456762910598
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 74.862138533961
+    - type: f1
+      value: 74.66457222091381
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 34.10761942610792
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 31.673172170578408
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 32.058704977250315
+    - type: mrr
+      value: 33.24327760839221
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.163
+    - type: map_at_10
+      value: 11.652999999999999
+    - type: map_at_100
+      value: 14.849
+    - type: map_at_1000
+      value: 16.253999999999998
+    - type: map_at_3
+      value: 8.616999999999999
+    - type: map_at_5
+      value: 10.100000000000001
+    - type: mrr_at_1
+      value: 44.272
+    - type: mrr_at_10
+      value: 52.25
+    - type: mrr_at_100
+      value: 52.761
+    - type: mrr_at_1000
+      value: 52.811
+    - type: mrr_at_3
+      value: 50.31
+    - type: mrr_at_5
+      value: 51.347
+    - type: ndcg_at_1
+      value: 42.105
+    - type: ndcg_at_10
+      value: 32.044
+    - type: ndcg_at_100
+      value: 29.763
+    - type: ndcg_at_1000
+      value: 38.585
+    - type: ndcg_at_3
+      value: 36.868
+    - type: ndcg_at_5
+      value: 35.154999999999994
+    - type: precision_at_1
+      value: 43.653
+    - type: precision_at_10
+      value: 23.622
+    - type: precision_at_100
+      value: 7.7490000000000006
+    - type: precision_at_1000
+      value: 2.054
+    - type: precision_at_3
+      value: 34.262
+    - type: precision_at_5
+      value: 30.154999999999998
+    - type: recall_at_1
+      value: 5.163
+    - type: recall_at_10
+      value: 15.478
+    - type: recall_at_100
+      value: 30.424
+    - type: recall_at_1000
+      value: 62.67
+    - type: recall_at_3
+      value: 9.615
+    - type: recall_at_5
+      value: 12.369
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.618000000000002
+    - type: map_at_10
+      value: 35.465
+    - type: map_at_100
+      value: 36.712
+    - type: map_at_1000
+      value: 36.757
+    - type: map_at_3
+      value: 31.189
+    - type: map_at_5
+      value: 33.537
+    - type: mrr_at_1
+      value: 24.305
+    - type: mrr_at_10
+      value: 37.653
+    - type: mrr_at_100
+      value: 38.662
+    - type: mrr_at_1000
+      value: 38.694
+    - type: mrr_at_3
+      value: 33.889
+    - type: mrr_at_5
+      value: 35.979
+    - type: ndcg_at_1
+      value: 24.305
+    - type: ndcg_at_10
+      value: 43.028
+    - type: ndcg_at_100
+      value: 48.653999999999996
+    - type: ndcg_at_1000
+      value: 49.733
+    - type: ndcg_at_3
+      value: 34.768
+    - type: ndcg_at_5
+      value: 38.753
+    - type: precision_at_1
+      value: 24.305
+    - type: precision_at_10
+      value: 7.59
+    - type: precision_at_100
+      value: 1.076
+    - type: precision_at_1000
+      value: 0.11800000000000001
+    - type: precision_at_3
+      value: 16.271
+    - type: precision_at_5
+      value: 12.068
+    - type: recall_at_1
+      value: 21.618000000000002
+    - type: recall_at_10
+      value: 63.977
+    - type: recall_at_100
+      value: 89.03999999999999
+    - type: recall_at_1000
+      value: 97.10600000000001
+    - type: recall_at_3
+      value: 42.422
+    - type: recall_at_5
+      value: 51.629000000000005
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 69.405
+    - type: map_at_10
+      value: 83.05
+    - type: map_at_100
+      value: 83.684
+    - type: map_at_1000
+      value: 83.70400000000001
+    - type: map_at_3
+      value: 80.08800000000001
+    - type: map_at_5
+      value: 81.937
+    - type: mrr_at_1
+      value: 79.85
+    - type: mrr_at_10
+      value: 86.369
+    - type: mrr_at_100
+      value: 86.48599999999999
+    - type: mrr_at_1000
+      value: 86.48700000000001
+    - type: mrr_at_3
+      value: 85.315
+    - type: mrr_at_5
+      value: 86.044
+    - type: ndcg_at_1
+      value: 79.86999999999999
+    - type: ndcg_at_10
+      value: 87.04499999999999
+    - type: ndcg_at_100
+      value: 88.373
+    - type: ndcg_at_1000
+      value: 88.531
+    - type: ndcg_at_3
+      value: 84.04
+    - type: ndcg_at_5
+      value: 85.684
+    - type: precision_at_1
+      value: 79.86999999999999
+    - type: precision_at_10
+      value: 13.183
+    - type: precision_at_100
+      value: 1.51
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 36.67
+    - type: precision_at_5
+      value: 24.12
+    - type: recall_at_1
+      value: 69.405
+    - type: recall_at_10
+      value: 94.634
+    - type: recall_at_100
+      value: 99.214
+    - type: recall_at_1000
+      value: 99.958
+    - type: recall_at_3
+      value: 85.992
+    - type: recall_at_5
+      value: 90.656
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 50.191676323145465
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 56.4874020363744
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.228
+    - type: map_at_10
+      value: 11.245
+    - type: map_at_100
+      value: 13.353000000000002
+    - type: map_at_1000
+      value: 13.665
+    - type: map_at_3
+      value: 7.779999999999999
+    - type: map_at_5
+      value: 9.405
+    - type: mrr_at_1
+      value: 20.9
+    - type: mrr_at_10
+      value: 31.657999999999998
+    - type: mrr_at_100
+      value: 32.769999999999996
+    - type: mrr_at_1000
+      value: 32.833
+    - type: mrr_at_3
+      value: 28.333000000000002
+    - type: mrr_at_5
+      value: 30.043
+    - type: ndcg_at_1
+      value: 20.9
+    - type: ndcg_at_10
+      value: 19.073
+    - type: ndcg_at_100
+      value: 27.055
+    - type: ndcg_at_1000
+      value: 32.641
+    - type: ndcg_at_3
+      value: 17.483999999999998
+    - type: ndcg_at_5
+      value: 15.42
+    - type: precision_at_1
+      value: 20.9
+    - type: precision_at_10
+      value: 10.17
+    - type: precision_at_100
+      value: 2.162
+    - type: precision_at_1000
+      value: 0.35100000000000003
+    - type: precision_at_3
+      value: 16.467000000000002
+    - type: precision_at_5
+      value: 13.68
+    - type: recall_at_1
+      value: 4.228
+    - type: recall_at_10
+      value: 20.573
+    - type: recall_at_100
+      value: 43.887
+    - type: recall_at_1000
+      value: 71.22
+    - type: recall_at_3
+      value: 10.023
+    - type: recall_at_5
+      value: 13.873
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.77965135067481
+    - type: cos_sim_spearman
+      value: 75.85121335808076
+    - type: euclidean_pearson
+      value: 80.09115175262697
+    - type: euclidean_spearman
+      value: 75.72249155647123
+    - type: manhattan_pearson
+      value: 79.89723577351782
+    - type: manhattan_spearman
+      value: 75.49855259442387
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.46084116030949
+    - type: cos_sim_spearman
+      value: 72.57579204392951
+    - type: euclidean_pearson
+      value: 76.39020830763684
+    - type: euclidean_spearman
+      value: 72.3718627025895
+    - type: manhattan_pearson
+      value: 76.6148833027359
+    - type: manhattan_spearman
+      value: 72.57570008442319
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.43678068337017
+    - type: cos_sim_spearman
+      value: 82.38941154076062
+    - type: euclidean_pearson
+      value: 81.59260573633661
+    - type: euclidean_spearman
+      value: 82.31144262574114
+    - type: manhattan_pearson
+      value: 81.43266909137056
+    - type: manhattan_spearman
+      value: 82.14704293004861
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.73713431763163
+    - type: cos_sim_spearman
+      value: 77.97860512809388
+    - type: euclidean_pearson
+      value: 80.35755041527027
+    - type: euclidean_spearman
+      value: 78.021703511412
+    - type: manhattan_pearson
+      value: 80.24440317109162
+    - type: manhattan_spearman
+      value: 77.93165415697575
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.15111852351204
+    - type: cos_sim_spearman
+      value: 86.54032447238258
+    - type: euclidean_pearson
+      value: 86.14157021537433
+    - type: euclidean_spearman
+      value: 86.67537291929713
+    - type: manhattan_pearson
+      value: 86.081041854808
+    - type: manhattan_spearman
+      value: 86.61561701560558
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.34532445104026
+    - type: cos_sim_spearman
+      value: 83.31325001474116
+    - type: euclidean_pearson
+      value: 82.81892375201032
+    - type: euclidean_spearman
+      value: 83.4521695148055
+    - type: manhattan_pearson
+      value: 82.72503790526163
+    - type: manhattan_spearman
+      value: 83.37833652941349
+  - 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: 87.25463453839801
+    - type: cos_sim_spearman
+      value: 88.27655263515948
+    - type: euclidean_pearson
+      value: 88.0248334411439
+    - type: euclidean_spearman
+      value: 88.18141448876868
+    - type: manhattan_pearson
+      value: 87.8080451127279
+    - type: manhattan_spearman
+      value: 88.01028114423058
+  - 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: 63.57551045355218
+    - type: cos_sim_spearman
+      value: 66.67614095126629
+    - type: euclidean_pearson
+      value: 66.0787243112528
+    - type: euclidean_spearman
+      value: 66.83660560636939
+    - type: manhattan_pearson
+      value: 66.74684019662031
+    - type: manhattan_spearman
+      value: 67.11761598074368
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.70881496766829
+    - type: cos_sim_spearman
+      value: 84.37803542941634
+    - type: euclidean_pearson
+      value: 84.84501245857096
+    - type: euclidean_spearman
+      value: 84.47088079741476
+    - type: manhattan_pearson
+      value: 84.77244090794765
+    - type: manhattan_spearman
+      value: 84.43307343706205
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 81.53946254759089
+    - type: mrr
+      value: 94.68259953554072
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 51.817
+    - type: map_at_10
+      value: 62.339999999999996
+    - type: map_at_100
+      value: 62.88
+    - type: map_at_1000
+      value: 62.909000000000006
+    - type: map_at_3
+      value: 59.004
+    - type: map_at_5
+      value: 60.906000000000006
+    - type: mrr_at_1
+      value: 54.333
+    - type: mrr_at_10
+      value: 63.649
+    - type: mrr_at_100
+      value: 64.01
+    - type: mrr_at_1000
+      value: 64.039
+    - type: mrr_at_3
+      value: 61.056
+    - type: mrr_at_5
+      value: 62.639
+    - type: ndcg_at_1
+      value: 54.333
+    - type: ndcg_at_10
+      value: 67.509
+    - type: ndcg_at_100
+      value: 69.69999999999999
+    - type: ndcg_at_1000
+      value: 70.613
+    - type: ndcg_at_3
+      value: 61.729
+    - type: ndcg_at_5
+      value: 64.696
+    - type: precision_at_1
+      value: 54.333
+    - type: precision_at_10
+      value: 9.2
+    - type: precision_at_100
+      value: 1.043
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 24.0
+    - type: precision_at_5
+      value: 16.2
+    - type: recall_at_1
+      value: 51.817
+    - type: recall_at_10
+      value: 82.056
+    - type: recall_at_100
+      value: 91.667
+    - type: recall_at_1000
+      value: 99.0
+    - type: recall_at_3
+      value: 66.717
+    - type: recall_at_5
+      value: 74.17200000000001
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.82475247524752
+    - type: cos_sim_ap
+      value: 95.4781199603258
+    - type: cos_sim_f1
+      value: 91.16186693147964
+    - type: cos_sim_precision
+      value: 90.53254437869822
+    - type: cos_sim_recall
+      value: 91.8
+    - type: dot_accuracy
+      value: 99.75049504950495
+    - type: dot_ap
+      value: 93.05183539809457
+    - type: dot_f1
+      value: 87.31117824773412
+    - type: dot_precision
+      value: 87.93103448275862
+    - type: dot_recall
+      value: 86.7
+    - type: euclidean_accuracy
+      value: 99.82475247524752
+    - type: euclidean_ap
+      value: 95.38547978154382
+    - type: euclidean_f1
+      value: 91.16325511732403
+    - type: euclidean_precision
+      value: 91.02691924227318
+    - type: euclidean_recall
+      value: 91.3
+    - type: manhattan_accuracy
+      value: 99.82574257425742
+    - type: manhattan_ap
+      value: 95.47237521890308
+    - type: manhattan_f1
+      value: 91.27849355797821
+    - type: manhattan_precision
+      value: 90.47151277013754
+    - type: manhattan_recall
+      value: 92.10000000000001
+    - type: max_accuracy
+      value: 99.82574257425742
+    - type: max_ap
+      value: 95.4781199603258
+    - type: max_f1
+      value: 91.27849355797821
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 57.542169376331245
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 35.74399302634387
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 49.65076347632749
+    - type: mrr
+      value: 50.418099057804945
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 29.73997756592847
+    - type: cos_sim_spearman
+      value: 29.465208011593308
+    - type: dot_pearson
+      value: 24.83735342474541
+    - type: dot_spearman
+      value: 26.005180528584855
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.208
+    - type: map_at_10
+      value: 1.434
+    - type: map_at_100
+      value: 7.829
+    - type: map_at_1000
+      value: 19.807
+    - type: map_at_3
+      value: 0.549
+    - type: map_at_5
+      value: 0.8330000000000001
+    - type: mrr_at_1
+      value: 78.0
+    - type: mrr_at_10
+      value: 85.35199999999999
+    - type: mrr_at_100
+      value: 85.673
+    - type: mrr_at_1000
+      value: 85.673
+    - type: mrr_at_3
+      value: 84.667
+    - type: mrr_at_5
+      value: 85.06700000000001
+    - type: ndcg_at_1
+      value: 72.0
+    - type: ndcg_at_10
+      value: 59.214999999999996
+    - type: ndcg_at_100
+      value: 44.681
+    - type: ndcg_at_1000
+      value: 43.035000000000004
+    - type: ndcg_at_3
+      value: 66.53099999999999
+    - type: ndcg_at_5
+      value: 63.23
+    - type: precision_at_1
+      value: 78.0
+    - type: precision_at_10
+      value: 62.4
+    - type: precision_at_100
+      value: 45.76
+    - type: precision_at_1000
+      value: 19.05
+    - type: precision_at_3
+      value: 71.333
+    - type: precision_at_5
+      value: 67.2
+    - type: recall_at_1
+      value: 0.208
+    - type: recall_at_10
+      value: 1.6580000000000001
+    - type: recall_at_100
+      value: 11.324
+    - type: recall_at_1000
+      value: 41.537
+    - type: recall_at_3
+      value: 0.579
+    - type: recall_at_5
+      value: 0.8959999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 2.442
+    - type: map_at_10
+      value: 8.863
+    - type: map_at_100
+      value: 14.606
+    - type: map_at_1000
+      value: 16.258
+    - type: map_at_3
+      value: 4.396
+    - type: map_at_5
+      value: 6.199000000000001
+    - type: mrr_at_1
+      value: 30.612000000000002
+    - type: mrr_at_10
+      value: 43.492
+    - type: mrr_at_100
+      value: 44.557
+    - type: mrr_at_1000
+      value: 44.557
+    - type: mrr_at_3
+      value: 40.816
+    - type: mrr_at_5
+      value: 42.143
+    - type: ndcg_at_1
+      value: 25.509999999999998
+    - type: ndcg_at_10
+      value: 22.076
+    - type: ndcg_at_100
+      value: 34.098
+    - type: ndcg_at_1000
+      value: 46.265
+    - type: ndcg_at_3
+      value: 24.19
+    - type: ndcg_at_5
+      value: 23.474
+    - type: precision_at_1
+      value: 30.612000000000002
+    - type: precision_at_10
+      value: 19.796
+    - type: precision_at_100
+      value: 7.286
+    - type: precision_at_1000
+      value: 1.5310000000000001
+    - type: precision_at_3
+      value: 25.85
+    - type: precision_at_5
+      value: 24.490000000000002
+    - type: recall_at_1
+      value: 2.442
+    - type: recall_at_10
+      value: 15.012
+    - type: recall_at_100
+      value: 45.865
+    - type: recall_at_1000
+      value: 82.958
+    - type: recall_at_3
+      value: 5.731
+    - type: recall_at_5
+      value: 9.301
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 70.974
+    - type: ap
+      value: 14.534996211286682
+    - type: f1
+      value: 54.785946183399005
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 58.56819468024901
+    - type: f1
+      value: 58.92391487111204
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 43.273202335218194
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 84.37742146986946
+    - type: cos_sim_ap
+      value: 68.1684129575579
+    - type: cos_sim_f1
+      value: 64.93475108748189
+    - type: cos_sim_precision
+      value: 59.89745876058849
+    - type: cos_sim_recall
+      value: 70.89709762532982
+    - type: dot_accuracy
+      value: 80.49710913750968
+    - type: dot_ap
+      value: 54.699790073944186
+    - type: dot_f1
+      value: 54.45130013221684
+    - type: dot_precision
+      value: 46.74612183125236
+    - type: dot_recall
+      value: 65.19788918205805
+    - type: euclidean_accuracy
+      value: 84.5085533766466
+    - type: euclidean_ap
+      value: 68.38835695236224
+    - type: euclidean_f1
+      value: 65.3391121002694
+    - type: euclidean_precision
+      value: 58.75289656625237
+    - type: euclidean_recall
+      value: 73.58839050131925
+    - type: manhattan_accuracy
+      value: 84.40126363473803
+    - type: manhattan_ap
+      value: 68.09539181555348
+    - type: manhattan_f1
+      value: 64.99028182701653
+    - type: manhattan_precision
+      value: 60.22062134173795
+    - type: manhattan_recall
+      value: 70.58047493403694
+    - type: max_accuracy
+      value: 84.5085533766466
+    - type: max_ap
+      value: 68.38835695236224
+    - type: max_f1
+      value: 65.3391121002694
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.34167733923235
+    - type: cos_sim_ap
+      value: 84.84136381147736
+    - type: cos_sim_f1
+      value: 77.01434980904001
+    - type: cos_sim_precision
+      value: 74.27937915742794
+    - type: cos_sim_recall
+      value: 79.95842315983985
+    - type: dot_accuracy
+      value: 85.06422944075756
+    - type: dot_ap
+      value: 76.49446747522325
+    - type: dot_f1
+      value: 71.11606520830432
+    - type: dot_precision
+      value: 64.93638676844785
+    - type: dot_recall
+      value: 78.59562673236834
+    - type: euclidean_accuracy
+      value: 88.45810532852097
+    - type: euclidean_ap
+      value: 84.91526721863501
+    - type: euclidean_f1
+      value: 77.04399001750662
+    - type: euclidean_precision
+      value: 74.62298867162133
+    - type: euclidean_recall
+      value: 79.62734832152756
+    - type: manhattan_accuracy
+      value: 88.46004579500912
+    - type: manhattan_ap
+      value: 84.81590026238194
+    - type: manhattan_f1
+      value: 76.97804626491822
+    - type: manhattan_precision
+      value: 73.79237288135593
+    - type: manhattan_recall
+      value: 80.45118570988605
+    - type: max_accuracy
+      value: 88.46004579500912
+    - type: max_ap
+      value: 84.91526721863501
+    - type: max_f1
+      value: 77.04399001750662
+
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+- transformers
+- mteb
+
+---
+
+# {gte-tiny}
+
+This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. 
+It is distilled from `thenlper/gte-small`, with comparable (slightly worse) performance at around half the size.
+
+<!--- Describe your model here -->
+
+## Usage (Sentence-Transformers)
+
+Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
+
+```
+pip install -U sentence-transformers
+```
+
+Then you can use the model like this:
+
+```python
+from sentence_transformers import SentenceTransformer
+sentences = ["This is an example sentence", "Each sentence is converted"]
+
+model = SentenceTransformer('{MODEL_NAME}')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+
+
+## Usage (HuggingFace Transformers)
+Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.
+
+```python
+from transformers import AutoTokenizer, AutoModel
+import torch
+
+
+#Mean Pooling - Take attention mask into account for correct averaging
+def mean_pooling(model_output, attention_mask):
+    token_embeddings = model_output[0] #First element of model_output contains all token embeddings
+    input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
+    return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
+
+
+# Sentences we want sentence embeddings for
+sentences = ['This is an example sentence', 'Each sentence is converted']
+
+# Load model from HuggingFace Hub
+tokenizer = AutoTokenizer.from_pretrained('{MODEL_NAME}')
+model = AutoModel.from_pretrained('{MODEL_NAME}')
+
+# Tokenize sentences
+encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
+
+# Compute token embeddings
+with torch.no_grad():
+    model_output = model(**encoded_input)
+
+# Perform pooling. In this case, mean pooling.
+sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask'])
+
+print("Sentence embeddings:")
+print(sentence_embeddings)
+```
+
+
+
+## Evaluation Results
+
+<!--- Describe how your model was evaluated -->
+
+For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name={MODEL_NAME})
+
+
+
+## Full Model Architecture
+```
+SentenceTransformer(
+  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
+  (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
+)
+```
+
+## Citing & Authors
+
+<!--- Describe where people can find more information -->

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config.json

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+  "_name_or_path": "/root/.cache/torch/sentence_transformers/andersonbcdefg_gte-tiny",
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+  "transformers_version": "4.34.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

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+    "sentence_transformers": "2.2.2",
+    "transformers": "4.34.0",
+    "pytorch": "2.0.1+cu118"
+  }
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