ember-v1

1_Pooling/config.json

@@ -0,0 +1,7 @@
+{
+  "word_embedding_dimension": 1024,
+  "pooling_mode_cls_token": true,
+  "pooling_mode_mean_tokens": false,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false
+}

README.md

@@ -1,3 +1,2692 @@
 ---
+tags:
+- mteb
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+language: en
 license: mit
+model-index:
+- name: ember_v1
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 76.05970149253731
+    - type: ap
+      value: 38.76045348512767
+    - type: f1
+      value: 69.8824007294685
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 91.977
+    - type: ap
+      value: 88.63507587170176
+    - type: f1
+      value: 91.9524133311038
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 47.938
+    - type: f1
+      value: 47.58273047536129
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 41.252
+    - type: map_at_10
+      value: 56.567
+    - type: map_at_100
+      value: 57.07600000000001
+    - type: map_at_1000
+      value: 57.08
+    - type: map_at_3
+      value: 52.394
+    - type: map_at_5
+      value: 55.055
+    - type: mrr_at_1
+      value: 42.39
+    - type: mrr_at_10
+      value: 57.001999999999995
+    - type: mrr_at_100
+      value: 57.531
+    - type: mrr_at_1000
+      value: 57.535000000000004
+    - type: mrr_at_3
+      value: 52.845
+    - type: mrr_at_5
+      value: 55.47299999999999
+    - type: ndcg_at_1
+      value: 41.252
+    - type: ndcg_at_10
+      value: 64.563
+    - type: ndcg_at_100
+      value: 66.667
+    - type: ndcg_at_1000
+      value: 66.77
+    - type: ndcg_at_3
+      value: 56.120000000000005
+    - type: ndcg_at_5
+      value: 60.889
+    - type: precision_at_1
+      value: 41.252
+    - type: precision_at_10
+      value: 8.982999999999999
+    - type: precision_at_100
+      value: 0.989
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 22.309
+    - type: precision_at_5
+      value: 15.690000000000001
+    - type: recall_at_1
+      value: 41.252
+    - type: recall_at_10
+      value: 89.82900000000001
+    - type: recall_at_100
+      value: 98.86200000000001
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 66.927
+    - type: recall_at_5
+      value: 78.45
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 48.5799968717232
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 43.142844164856136
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 64.45997990276463
+    - type: mrr
+      value: 77.85560392208592
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.38299310075898
+    - type: cos_sim_spearman
+      value: 85.81038898286454
+    - type: euclidean_pearson
+      value: 84.28002556389774
+    - type: euclidean_spearman
+      value: 85.80315990248238
+    - type: manhattan_pearson
+      value: 83.9755390675032
+    - type: manhattan_spearman
+      value: 85.30435335611396
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 87.89935064935065
+    - type: f1
+      value: 87.87886687103833
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 38.84335510371379
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 36.377963093857005
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.557
+    - type: map_at_10
+      value: 44.501000000000005
+    - type: map_at_100
+      value: 46.11
+    - type: map_at_1000
+      value: 46.232
+    - type: map_at_3
+      value: 40.711000000000006
+    - type: map_at_5
+      value: 42.937
+    - type: mrr_at_1
+      value: 40.916000000000004
+    - type: mrr_at_10
+      value: 51.317
+    - type: mrr_at_100
+      value: 52.003
+    - type: mrr_at_1000
+      value: 52.044999999999995
+    - type: mrr_at_3
+      value: 48.569
+    - type: mrr_at_5
+      value: 50.322
+    - type: ndcg_at_1
+      value: 40.916000000000004
+    - type: ndcg_at_10
+      value: 51.353
+    - type: ndcg_at_100
+      value: 56.762
+    - type: ndcg_at_1000
+      value: 58.555
+    - type: ndcg_at_3
+      value: 46.064
+    - type: ndcg_at_5
+      value: 48.677
+    - type: precision_at_1
+      value: 40.916000000000004
+    - type: precision_at_10
+      value: 9.927999999999999
+    - type: precision_at_100
+      value: 1.592
+    - type: precision_at_1000
+      value: 0.20600000000000002
+    - type: precision_at_3
+      value: 22.078999999999997
+    - type: precision_at_5
+      value: 16.08
+    - type: recall_at_1
+      value: 32.557
+    - type: recall_at_10
+      value: 63.942
+    - type: recall_at_100
+      value: 86.436
+    - type: recall_at_1000
+      value: 97.547
+    - type: recall_at_3
+      value: 48.367
+    - type: recall_at_5
+      value: 55.818
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.106
+    - type: map_at_10
+      value: 42.55
+    - type: map_at_100
+      value: 43.818
+    - type: map_at_1000
+      value: 43.952999999999996
+    - type: map_at_3
+      value: 39.421
+    - type: map_at_5
+      value: 41.276
+    - type: mrr_at_1
+      value: 39.936
+    - type: mrr_at_10
+      value: 48.484
+    - type: mrr_at_100
+      value: 49.123
+    - type: mrr_at_1000
+      value: 49.163000000000004
+    - type: mrr_at_3
+      value: 46.221000000000004
+    - type: mrr_at_5
+      value: 47.603
+    - type: ndcg_at_1
+      value: 39.936
+    - type: ndcg_at_10
+      value: 48.25
+    - type: ndcg_at_100
+      value: 52.674
+    - type: ndcg_at_1000
+      value: 54.638
+    - type: ndcg_at_3
+      value: 44.05
+    - type: ndcg_at_5
+      value: 46.125
+    - type: precision_at_1
+      value: 39.936
+    - type: precision_at_10
+      value: 9.096
+    - type: precision_at_100
+      value: 1.473
+    - type: precision_at_1000
+      value: 0.19499999999999998
+    - type: precision_at_3
+      value: 21.295
+    - type: precision_at_5
+      value: 15.121
+    - type: recall_at_1
+      value: 32.106
+    - type: recall_at_10
+      value: 58.107
+    - type: recall_at_100
+      value: 76.873
+    - type: recall_at_1000
+      value: 89.079
+    - type: recall_at_3
+      value: 45.505
+    - type: recall_at_5
+      value: 51.479
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 41.513
+    - type: map_at_10
+      value: 54.571999999999996
+    - type: map_at_100
+      value: 55.579
+    - type: map_at_1000
+      value: 55.626
+    - type: map_at_3
+      value: 51.127
+    - type: map_at_5
+      value: 53.151
+    - type: mrr_at_1
+      value: 47.398
+    - type: mrr_at_10
+      value: 57.82000000000001
+    - type: mrr_at_100
+      value: 58.457
+    - type: mrr_at_1000
+      value: 58.479000000000006
+    - type: mrr_at_3
+      value: 55.32899999999999
+    - type: mrr_at_5
+      value: 56.89999999999999
+    - type: ndcg_at_1
+      value: 47.398
+    - type: ndcg_at_10
+      value: 60.599000000000004
+    - type: ndcg_at_100
+      value: 64.366
+    - type: ndcg_at_1000
+      value: 65.333
+    - type: ndcg_at_3
+      value: 54.98
+    - type: ndcg_at_5
+      value: 57.874
+    - type: precision_at_1
+      value: 47.398
+    - type: precision_at_10
+      value: 9.806
+    - type: precision_at_100
+      value: 1.2590000000000001
+    - type: precision_at_1000
+      value: 0.13799999999999998
+    - type: precision_at_3
+      value: 24.619
+    - type: precision_at_5
+      value: 16.878
+    - type: recall_at_1
+      value: 41.513
+    - type: recall_at_10
+      value: 74.91799999999999
+    - type: recall_at_100
+      value: 90.96
+    - type: recall_at_1000
+      value: 97.923
+    - type: recall_at_3
+      value: 60.013000000000005
+    - type: recall_at_5
+      value: 67.245
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.319
+    - type: map_at_10
+      value: 35.766999999999996
+    - type: map_at_100
+      value: 36.765
+    - type: map_at_1000
+      value: 36.829
+    - type: map_at_3
+      value: 32.888
+    - type: map_at_5
+      value: 34.538999999999994
+    - type: mrr_at_1
+      value: 28.249000000000002
+    - type: mrr_at_10
+      value: 37.766
+    - type: mrr_at_100
+      value: 38.62
+    - type: mrr_at_1000
+      value: 38.667
+    - type: mrr_at_3
+      value: 35.009
+    - type: mrr_at_5
+      value: 36.608000000000004
+    - type: ndcg_at_1
+      value: 28.249000000000002
+    - type: ndcg_at_10
+      value: 41.215
+    - type: ndcg_at_100
+      value: 46.274
+    - type: ndcg_at_1000
+      value: 48.007
+    - type: ndcg_at_3
+      value: 35.557
+    - type: ndcg_at_5
+      value: 38.344
+    - type: precision_at_1
+      value: 28.249000000000002
+    - type: precision_at_10
+      value: 6.429
+    - type: precision_at_100
+      value: 0.9480000000000001
+    - type: precision_at_1000
+      value: 0.11399999999999999
+    - type: precision_at_3
+      value: 15.179
+    - type: precision_at_5
+      value: 10.734
+    - type: recall_at_1
+      value: 26.319
+    - type: recall_at_10
+      value: 56.157999999999994
+    - type: recall_at_100
+      value: 79.65
+    - type: recall_at_1000
+      value: 92.73
+    - type: recall_at_3
+      value: 40.738
+    - type: recall_at_5
+      value: 47.418
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 18.485
+    - type: map_at_10
+      value: 27.400999999999996
+    - type: map_at_100
+      value: 28.665000000000003
+    - type: map_at_1000
+      value: 28.79
+    - type: map_at_3
+      value: 24.634
+    - type: map_at_5
+      value: 26.313
+    - type: mrr_at_1
+      value: 23.134
+    - type: mrr_at_10
+      value: 32.332
+    - type: mrr_at_100
+      value: 33.318
+    - type: mrr_at_1000
+      value: 33.384
+    - type: mrr_at_3
+      value: 29.664
+    - type: mrr_at_5
+      value: 31.262
+    - type: ndcg_at_1
+      value: 23.134
+    - type: ndcg_at_10
+      value: 33.016
+    - type: ndcg_at_100
+      value: 38.763
+    - type: ndcg_at_1000
+      value: 41.619
+    - type: ndcg_at_3
+      value: 28.017999999999997
+    - type: ndcg_at_5
+      value: 30.576999999999998
+    - type: precision_at_1
+      value: 23.134
+    - type: precision_at_10
+      value: 6.069999999999999
+    - type: precision_at_100
+      value: 1.027
+    - type: precision_at_1000
+      value: 0.14200000000000002
+    - type: precision_at_3
+      value: 13.599
+    - type: precision_at_5
+      value: 9.975000000000001
+    - type: recall_at_1
+      value: 18.485
+    - type: recall_at_10
+      value: 45.39
+    - type: recall_at_100
+      value: 69.876
+    - type: recall_at_1000
+      value: 90.023
+    - type: recall_at_3
+      value: 31.587
+    - type: recall_at_5
+      value: 38.164
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 30.676
+    - type: map_at_10
+      value: 41.785
+    - type: map_at_100
+      value: 43.169000000000004
+    - type: map_at_1000
+      value: 43.272
+    - type: map_at_3
+      value: 38.462
+    - type: map_at_5
+      value: 40.32
+    - type: mrr_at_1
+      value: 37.729
+    - type: mrr_at_10
+      value: 47.433
+    - type: mrr_at_100
+      value: 48.303000000000004
+    - type: mrr_at_1000
+      value: 48.337
+    - type: mrr_at_3
+      value: 45.011
+    - type: mrr_at_5
+      value: 46.455
+    - type: ndcg_at_1
+      value: 37.729
+    - type: ndcg_at_10
+      value: 47.921
+    - type: ndcg_at_100
+      value: 53.477
+    - type: ndcg_at_1000
+      value: 55.300000000000004
+    - type: ndcg_at_3
+      value: 42.695
+    - type: ndcg_at_5
+      value: 45.175
+    - type: precision_at_1
+      value: 37.729
+    - type: precision_at_10
+      value: 8.652999999999999
+    - type: precision_at_100
+      value: 1.336
+    - type: precision_at_1000
+      value: 0.168
+    - type: precision_at_3
+      value: 20.18
+    - type: precision_at_5
+      value: 14.302000000000001
+    - type: recall_at_1
+      value: 30.676
+    - type: recall_at_10
+      value: 60.441
+    - type: recall_at_100
+      value: 83.37
+    - type: recall_at_1000
+      value: 95.092
+    - type: recall_at_3
+      value: 45.964
+    - type: recall_at_5
+      value: 52.319
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.978
+    - type: map_at_10
+      value: 35.926
+    - type: map_at_100
+      value: 37.341
+    - type: map_at_1000
+      value: 37.445
+    - type: map_at_3
+      value: 32.748
+    - type: map_at_5
+      value: 34.207
+    - type: mrr_at_1
+      value: 31.163999999999998
+    - type: mrr_at_10
+      value: 41.394
+    - type: mrr_at_100
+      value: 42.321
+    - type: mrr_at_1000
+      value: 42.368
+    - type: mrr_at_3
+      value: 38.964999999999996
+    - type: mrr_at_5
+      value: 40.135
+    - type: ndcg_at_1
+      value: 31.163999999999998
+    - type: ndcg_at_10
+      value: 42.191
+    - type: ndcg_at_100
+      value: 48.083999999999996
+    - type: ndcg_at_1000
+      value: 50.21
+    - type: ndcg_at_3
+      value: 36.979
+    - type: ndcg_at_5
+      value: 38.823
+    - type: precision_at_1
+      value: 31.163999999999998
+    - type: precision_at_10
+      value: 7.968
+    - type: precision_at_100
+      value: 1.2550000000000001
+    - type: precision_at_1000
+      value: 0.16199999999999998
+    - type: precision_at_3
+      value: 18.075
+    - type: precision_at_5
+      value: 12.626000000000001
+    - type: recall_at_1
+      value: 24.978
+    - type: recall_at_10
+      value: 55.410000000000004
+    - type: recall_at_100
+      value: 80.562
+    - type: recall_at_1000
+      value: 94.77600000000001
+    - type: recall_at_3
+      value: 40.359
+    - type: recall_at_5
+      value: 45.577
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.812166666666666
+    - type: map_at_10
+      value: 36.706916666666665
+    - type: map_at_100
+      value: 37.94016666666666
+    - type: map_at_1000
+      value: 38.05358333333333
+    - type: map_at_3
+      value: 33.72408333333334
+    - type: map_at_5
+      value: 35.36508333333333
+    - type: mrr_at_1
+      value: 31.91516666666667
+    - type: mrr_at_10
+      value: 41.09716666666666
+    - type: mrr_at_100
+      value: 41.931916666666666
+    - type: mrr_at_1000
+      value: 41.98458333333333
+    - type: mrr_at_3
+      value: 38.60183333333333
+    - type: mrr_at_5
+      value: 40.031916666666675
+    - type: ndcg_at_1
+      value: 31.91516666666667
+    - type: ndcg_at_10
+      value: 42.38725
+    - type: ndcg_at_100
+      value: 47.56291666666667
+    - type: ndcg_at_1000
+      value: 49.716499999999996
+    - type: ndcg_at_3
+      value: 37.36491666666667
+    - type: ndcg_at_5
+      value: 39.692166666666665
+    - type: precision_at_1
+      value: 31.91516666666667
+    - type: precision_at_10
+      value: 7.476749999999999
+    - type: precision_at_100
+      value: 1.1869166666666668
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 17.275249999999996
+    - type: precision_at_5
+      value: 12.25825
+    - type: recall_at_1
+      value: 26.812166666666666
+    - type: recall_at_10
+      value: 54.82933333333333
+    - type: recall_at_100
+      value: 77.36508333333333
+    - type: recall_at_1000
+      value: 92.13366666666667
+    - type: recall_at_3
+      value: 40.83508333333334
+    - type: recall_at_5
+      value: 46.85083333333334
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.352999999999998
+    - type: map_at_10
+      value: 33.025999999999996
+    - type: map_at_100
+      value: 33.882
+    - type: map_at_1000
+      value: 33.983999999999995
+    - type: map_at_3
+      value: 30.995
+    - type: map_at_5
+      value: 32.113
+    - type: mrr_at_1
+      value: 28.834
+    - type: mrr_at_10
+      value: 36.14
+    - type: mrr_at_100
+      value: 36.815
+    - type: mrr_at_1000
+      value: 36.893
+    - type: mrr_at_3
+      value: 34.305
+    - type: mrr_at_5
+      value: 35.263
+    - type: ndcg_at_1
+      value: 28.834
+    - type: ndcg_at_10
+      value: 37.26
+    - type: ndcg_at_100
+      value: 41.723
+    - type: ndcg_at_1000
+      value: 44.314
+    - type: ndcg_at_3
+      value: 33.584
+    - type: ndcg_at_5
+      value: 35.302
+    - type: precision_at_1
+      value: 28.834
+    - type: precision_at_10
+      value: 5.736
+    - type: precision_at_100
+      value: 0.876
+    - type: precision_at_1000
+      value: 0.117
+    - type: precision_at_3
+      value: 14.468
+    - type: precision_at_5
+      value: 9.847
+    - type: recall_at_1
+      value: 25.352999999999998
+    - type: recall_at_10
+      value: 47.155
+    - type: recall_at_100
+      value: 68.024
+    - type: recall_at_1000
+      value: 87.26899999999999
+    - type: recall_at_3
+      value: 37.074
+    - type: recall_at_5
+      value: 41.352
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.845
+    - type: map_at_10
+      value: 25.556
+    - type: map_at_100
+      value: 26.787
+    - type: map_at_1000
+      value: 26.913999999999998
+    - type: map_at_3
+      value: 23.075000000000003
+    - type: map_at_5
+      value: 24.308
+    - type: mrr_at_1
+      value: 21.714
+    - type: mrr_at_10
+      value: 29.543999999999997
+    - type: mrr_at_100
+      value: 30.543
+    - type: mrr_at_1000
+      value: 30.618000000000002
+    - type: mrr_at_3
+      value: 27.174
+    - type: mrr_at_5
+      value: 28.409000000000002
+    - type: ndcg_at_1
+      value: 21.714
+    - type: ndcg_at_10
+      value: 30.562
+    - type: ndcg_at_100
+      value: 36.27
+    - type: ndcg_at_1000
+      value: 39.033
+    - type: ndcg_at_3
+      value: 26.006
+    - type: ndcg_at_5
+      value: 27.843
+    - type: precision_at_1
+      value: 21.714
+    - type: precision_at_10
+      value: 5.657
+    - type: precision_at_100
+      value: 1.0
+    - type: precision_at_1000
+      value: 0.14100000000000001
+    - type: precision_at_3
+      value: 12.4
+    - type: precision_at_5
+      value: 8.863999999999999
+    - type: recall_at_1
+      value: 17.845
+    - type: recall_at_10
+      value: 41.72
+    - type: recall_at_100
+      value: 67.06400000000001
+    - type: recall_at_1000
+      value: 86.515
+    - type: recall_at_3
+      value: 28.78
+    - type: recall_at_5
+      value: 33.629999999999995
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.695
+    - type: map_at_10
+      value: 36.205999999999996
+    - type: map_at_100
+      value: 37.346000000000004
+    - type: map_at_1000
+      value: 37.447
+    - type: map_at_3
+      value: 32.84
+    - type: map_at_5
+      value: 34.733000000000004
+    - type: mrr_at_1
+      value: 31.343
+    - type: mrr_at_10
+      value: 40.335
+    - type: mrr_at_100
+      value: 41.162
+    - type: mrr_at_1000
+      value: 41.221000000000004
+    - type: mrr_at_3
+      value: 37.329
+    - type: mrr_at_5
+      value: 39.068999999999996
+    - type: ndcg_at_1
+      value: 31.343
+    - type: ndcg_at_10
+      value: 41.996
+    - type: ndcg_at_100
+      value: 47.096
+    - type: ndcg_at_1000
+      value: 49.4
+    - type: ndcg_at_3
+      value: 35.902
+    - type: ndcg_at_5
+      value: 38.848
+    - type: precision_at_1
+      value: 31.343
+    - type: precision_at_10
+      value: 7.146
+    - type: precision_at_100
+      value: 1.098
+    - type: precision_at_1000
+      value: 0.14100000000000001
+    - type: precision_at_3
+      value: 16.014
+    - type: precision_at_5
+      value: 11.735
+    - type: recall_at_1
+      value: 26.695
+    - type: recall_at_10
+      value: 55.525000000000006
+    - type: recall_at_100
+      value: 77.376
+    - type: recall_at_1000
+      value: 93.476
+    - type: recall_at_3
+      value: 39.439
+    - type: recall_at_5
+      value: 46.501
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.196
+    - type: map_at_10
+      value: 33.516
+    - type: map_at_100
+      value: 35.202
+    - type: map_at_1000
+      value: 35.426
+    - type: map_at_3
+      value: 30.561
+    - type: map_at_5
+      value: 31.961000000000002
+    - type: mrr_at_1
+      value: 29.644
+    - type: mrr_at_10
+      value: 38.769
+    - type: mrr_at_100
+      value: 39.843
+    - type: mrr_at_1000
+      value: 39.888
+    - type: mrr_at_3
+      value: 36.132999999999996
+    - type: mrr_at_5
+      value: 37.467
+    - type: ndcg_at_1
+      value: 29.644
+    - type: ndcg_at_10
+      value: 39.584
+    - type: ndcg_at_100
+      value: 45.964
+    - type: ndcg_at_1000
+      value: 48.27
+    - type: ndcg_at_3
+      value: 34.577999999999996
+    - type: ndcg_at_5
+      value: 36.498000000000005
+    - type: precision_at_1
+      value: 29.644
+    - type: precision_at_10
+      value: 7.668
+    - type: precision_at_100
+      value: 1.545
+    - type: precision_at_1000
+      value: 0.242
+    - type: precision_at_3
+      value: 16.271
+    - type: precision_at_5
+      value: 11.620999999999999
+    - type: recall_at_1
+      value: 24.196
+    - type: recall_at_10
+      value: 51.171
+    - type: recall_at_100
+      value: 79.212
+    - type: recall_at_1000
+      value: 92.976
+    - type: recall_at_3
+      value: 36.797999999999995
+    - type: recall_at_5
+      value: 42.006
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.023
+    - type: map_at_10
+      value: 29.677
+    - type: map_at_100
+      value: 30.618000000000002
+    - type: map_at_1000
+      value: 30.725
+    - type: map_at_3
+      value: 27.227
+    - type: map_at_5
+      value: 28.523
+    - type: mrr_at_1
+      value: 22.921
+    - type: mrr_at_10
+      value: 31.832
+    - type: mrr_at_100
+      value: 32.675
+    - type: mrr_at_1000
+      value: 32.751999999999995
+    - type: mrr_at_3
+      value: 29.513
+    - type: mrr_at_5
+      value: 30.89
+    - type: ndcg_at_1
+      value: 22.921
+    - type: ndcg_at_10
+      value: 34.699999999999996
+    - type: ndcg_at_100
+      value: 39.302
+    - type: ndcg_at_1000
+      value: 41.919000000000004
+    - type: ndcg_at_3
+      value: 29.965999999999998
+    - type: ndcg_at_5
+      value: 32.22
+    - type: precision_at_1
+      value: 22.921
+    - type: precision_at_10
+      value: 5.564
+    - type: precision_at_100
+      value: 0.8340000000000001
+    - type: precision_at_1000
+      value: 0.11800000000000001
+    - type: precision_at_3
+      value: 13.123999999999999
+    - type: precision_at_5
+      value: 9.316
+    - type: recall_at_1
+      value: 21.023
+    - type: recall_at_10
+      value: 48.015
+    - type: recall_at_100
+      value: 68.978
+    - type: recall_at_1000
+      value: 88.198
+    - type: recall_at_3
+      value: 35.397
+    - type: recall_at_5
+      value: 40.701
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 11.198
+    - type: map_at_10
+      value: 19.336000000000002
+    - type: map_at_100
+      value: 21.382
+    - type: map_at_1000
+      value: 21.581
+    - type: map_at_3
+      value: 15.992
+    - type: map_at_5
+      value: 17.613
+    - type: mrr_at_1
+      value: 25.080999999999996
+    - type: mrr_at_10
+      value: 36.032
+    - type: mrr_at_100
+      value: 37.1
+    - type: mrr_at_1000
+      value: 37.145
+    - type: mrr_at_3
+      value: 32.595
+    - type: mrr_at_5
+      value: 34.553
+    - type: ndcg_at_1
+      value: 25.080999999999996
+    - type: ndcg_at_10
+      value: 27.290999999999997
+    - type: ndcg_at_100
+      value: 35.31
+    - type: ndcg_at_1000
+      value: 38.885
+    - type: ndcg_at_3
+      value: 21.895999999999997
+    - type: ndcg_at_5
+      value: 23.669999999999998
+    - type: precision_at_1
+      value: 25.080999999999996
+    - type: precision_at_10
+      value: 8.645
+    - type: precision_at_100
+      value: 1.7209999999999999
+    - type: precision_at_1000
+      value: 0.23900000000000002
+    - type: precision_at_3
+      value: 16.287
+    - type: precision_at_5
+      value: 12.625
+    - type: recall_at_1
+      value: 11.198
+    - type: recall_at_10
+      value: 33.355000000000004
+    - type: recall_at_100
+      value: 60.912
+    - type: recall_at_1000
+      value: 80.89
+    - type: recall_at_3
+      value: 20.055
+    - type: recall_at_5
+      value: 25.14
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 9.228
+    - type: map_at_10
+      value: 20.018
+    - type: map_at_100
+      value: 28.388999999999996
+    - type: map_at_1000
+      value: 30.073
+    - type: map_at_3
+      value: 14.366999999999999
+    - type: map_at_5
+      value: 16.705000000000002
+    - type: mrr_at_1
+      value: 69.0
+    - type: mrr_at_10
+      value: 77.058
+    - type: mrr_at_100
+      value: 77.374
+    - type: mrr_at_1000
+      value: 77.384
+    - type: mrr_at_3
+      value: 75.708
+    - type: mrr_at_5
+      value: 76.608
+    - type: ndcg_at_1
+      value: 57.49999999999999
+    - type: ndcg_at_10
+      value: 41.792
+    - type: ndcg_at_100
+      value: 47.374
+    - type: ndcg_at_1000
+      value: 55.13
+    - type: ndcg_at_3
+      value: 46.353
+    - type: ndcg_at_5
+      value: 43.702000000000005
+    - type: precision_at_1
+      value: 69.0
+    - type: precision_at_10
+      value: 32.85
+    - type: precision_at_100
+      value: 10.708
+    - type: precision_at_1000
+      value: 2.024
+    - type: precision_at_3
+      value: 49.5
+    - type: precision_at_5
+      value: 42.05
+    - type: recall_at_1
+      value: 9.228
+    - type: recall_at_10
+      value: 25.635
+    - type: recall_at_100
+      value: 54.894
+    - type: recall_at_1000
+      value: 79.38
+    - type: recall_at_3
+      value: 15.68
+    - type: recall_at_5
+      value: 19.142
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 52.035
+    - type: f1
+      value: 46.85325505614071
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 70.132
+    - type: map_at_10
+      value: 79.527
+    - type: map_at_100
+      value: 79.81200000000001
+    - type: map_at_1000
+      value: 79.828
+    - type: map_at_3
+      value: 78.191
+    - type: map_at_5
+      value: 79.092
+    - type: mrr_at_1
+      value: 75.563
+    - type: mrr_at_10
+      value: 83.80199999999999
+    - type: mrr_at_100
+      value: 83.93
+    - type: mrr_at_1000
+      value: 83.933
+    - type: mrr_at_3
+      value: 82.818
+    - type: mrr_at_5
+      value: 83.505
+    - type: ndcg_at_1
+      value: 75.563
+    - type: ndcg_at_10
+      value: 83.692
+    - type: ndcg_at_100
+      value: 84.706
+    - type: ndcg_at_1000
+      value: 85.001
+    - type: ndcg_at_3
+      value: 81.51
+    - type: ndcg_at_5
+      value: 82.832
+    - type: precision_at_1
+      value: 75.563
+    - type: precision_at_10
+      value: 10.245
+    - type: precision_at_100
+      value: 1.0959999999999999
+    - type: precision_at_1000
+      value: 0.11399999999999999
+    - type: precision_at_3
+      value: 31.518
+    - type: precision_at_5
+      value: 19.772000000000002
+    - type: recall_at_1
+      value: 70.132
+    - type: recall_at_10
+      value: 92.204
+    - type: recall_at_100
+      value: 96.261
+    - type: recall_at_1000
+      value: 98.17399999999999
+    - type: recall_at_3
+      value: 86.288
+    - type: recall_at_5
+      value: 89.63799999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.269
+    - type: map_at_10
+      value: 36.042
+    - type: map_at_100
+      value: 37.988
+    - type: map_at_1000
+      value: 38.162
+    - type: map_at_3
+      value: 31.691000000000003
+    - type: map_at_5
+      value: 33.988
+    - type: mrr_at_1
+      value: 44.907000000000004
+    - type: mrr_at_10
+      value: 53.348
+    - type: mrr_at_100
+      value: 54.033
+    - type: mrr_at_1000
+      value: 54.064
+    - type: mrr_at_3
+      value: 50.977
+    - type: mrr_at_5
+      value: 52.112
+    - type: ndcg_at_1
+      value: 44.907000000000004
+    - type: ndcg_at_10
+      value: 44.302
+    - type: ndcg_at_100
+      value: 51.054
+    - type: ndcg_at_1000
+      value: 53.822
+    - type: ndcg_at_3
+      value: 40.615
+    - type: ndcg_at_5
+      value: 41.455999999999996
+    - type: precision_at_1
+      value: 44.907000000000004
+    - type: precision_at_10
+      value: 12.176
+    - type: precision_at_100
+      value: 1.931
+    - type: precision_at_1000
+      value: 0.243
+    - type: precision_at_3
+      value: 27.16
+    - type: precision_at_5
+      value: 19.567999999999998
+    - type: recall_at_1
+      value: 22.269
+    - type: recall_at_10
+      value: 51.188
+    - type: recall_at_100
+      value: 75.924
+    - type: recall_at_1000
+      value: 92.525
+    - type: recall_at_3
+      value: 36.643
+    - type: recall_at_5
+      value: 42.27
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 40.412
+    - type: map_at_10
+      value: 66.376
+    - type: map_at_100
+      value: 67.217
+    - type: map_at_1000
+      value: 67.271
+    - type: map_at_3
+      value: 62.741
+    - type: map_at_5
+      value: 65.069
+    - type: mrr_at_1
+      value: 80.824
+    - type: mrr_at_10
+      value: 86.53
+    - type: mrr_at_100
+      value: 86.67399999999999
+    - type: mrr_at_1000
+      value: 86.678
+    - type: mrr_at_3
+      value: 85.676
+    - type: mrr_at_5
+      value: 86.256
+    - type: ndcg_at_1
+      value: 80.824
+    - type: ndcg_at_10
+      value: 74.332
+    - type: ndcg_at_100
+      value: 77.154
+    - type: ndcg_at_1000
+      value: 78.12400000000001
+    - type: ndcg_at_3
+      value: 69.353
+    - type: ndcg_at_5
+      value: 72.234
+    - type: precision_at_1
+      value: 80.824
+    - type: precision_at_10
+      value: 15.652
+    - type: precision_at_100
+      value: 1.7840000000000003
+    - type: precision_at_1000
+      value: 0.191
+    - type: precision_at_3
+      value: 44.911
+    - type: precision_at_5
+      value: 29.221000000000004
+    - type: recall_at_1
+      value: 40.412
+    - type: recall_at_10
+      value: 78.25800000000001
+    - type: recall_at_100
+      value: 89.196
+    - type: recall_at_1000
+      value: 95.544
+    - type: recall_at_3
+      value: 67.367
+    - type: recall_at_5
+      value: 73.05199999999999
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 92.78880000000001
+    - type: ap
+      value: 89.39251741048801
+    - type: f1
+      value: 92.78019950076781
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.888
+    - type: map_at_10
+      value: 35.146
+    - type: map_at_100
+      value: 36.325
+    - type: map_at_1000
+      value: 36.372
+    - type: map_at_3
+      value: 31.3
+    - type: map_at_5
+      value: 33.533
+    - type: mrr_at_1
+      value: 23.480999999999998
+    - type: mrr_at_10
+      value: 35.777
+    - type: mrr_at_100
+      value: 36.887
+    - type: mrr_at_1000
+      value: 36.928
+    - type: mrr_at_3
+      value: 31.989
+    - type: mrr_at_5
+      value: 34.202
+    - type: ndcg_at_1
+      value: 23.496
+    - type: ndcg_at_10
+      value: 42.028999999999996
+    - type: ndcg_at_100
+      value: 47.629
+    - type: ndcg_at_1000
+      value: 48.785000000000004
+    - type: ndcg_at_3
+      value: 34.227000000000004
+    - type: ndcg_at_5
+      value: 38.207
+    - type: precision_at_1
+      value: 23.496
+    - type: precision_at_10
+      value: 6.596
+    - type: precision_at_100
+      value: 0.9400000000000001
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 14.513000000000002
+    - type: precision_at_5
+      value: 10.711
+    - type: recall_at_1
+      value: 22.888
+    - type: recall_at_10
+      value: 63.129999999999995
+    - type: recall_at_100
+      value: 88.90299999999999
+    - type: recall_at_1000
+      value: 97.69
+    - type: recall_at_3
+      value: 42.014
+    - type: recall_at_5
+      value: 51.554
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 94.59188326493388
+    - type: f1
+      value: 94.36568950290486
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 79.25672594619242
+    - type: f1
+      value: 59.52405059722216
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 77.4142568930733
+    - type: f1
+      value: 75.23044196543388
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 80.44720914593141
+    - type: f1
+      value: 80.41049641537015
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 31.960921474993775
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 30.88042240204361
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 32.27071371606404
+    - type: mrr
+      value: 33.541450459533856
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 6.551
+    - type: map_at_10
+      value: 14.359
+    - type: map_at_100
+      value: 18.157
+    - type: map_at_1000
+      value: 19.659
+    - type: map_at_3
+      value: 10.613999999999999
+    - type: map_at_5
+      value: 12.296
+    - type: mrr_at_1
+      value: 47.368
+    - type: mrr_at_10
+      value: 56.689
+    - type: mrr_at_100
+      value: 57.24399999999999
+    - type: mrr_at_1000
+      value: 57.284
+    - type: mrr_at_3
+      value: 54.489
+    - type: mrr_at_5
+      value: 55.928999999999995
+    - type: ndcg_at_1
+      value: 45.511
+    - type: ndcg_at_10
+      value: 36.911
+    - type: ndcg_at_100
+      value: 34.241
+    - type: ndcg_at_1000
+      value: 43.064
+    - type: ndcg_at_3
+      value: 42.348
+    - type: ndcg_at_5
+      value: 39.884
+    - type: precision_at_1
+      value: 46.749
+    - type: precision_at_10
+      value: 27.028000000000002
+    - type: precision_at_100
+      value: 8.52
+    - type: precision_at_1000
+      value: 2.154
+    - type: precision_at_3
+      value: 39.525
+    - type: precision_at_5
+      value: 34.18
+    - type: recall_at_1
+      value: 6.551
+    - type: recall_at_10
+      value: 18.602
+    - type: recall_at_100
+      value: 34.882999999999996
+    - type: recall_at_1000
+      value: 66.049
+    - type: recall_at_3
+      value: 11.872
+    - type: recall_at_5
+      value: 14.74
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.828999999999997
+    - type: map_at_10
+      value: 43.606
+    - type: map_at_100
+      value: 44.656
+    - type: map_at_1000
+      value: 44.690000000000005
+    - type: map_at_3
+      value: 39.015
+    - type: map_at_5
+      value: 41.625
+    - type: mrr_at_1
+      value: 31.518
+    - type: mrr_at_10
+      value: 46.047
+    - type: mrr_at_100
+      value: 46.846
+    - type: mrr_at_1000
+      value: 46.867999999999995
+    - type: mrr_at_3
+      value: 42.154
+    - type: mrr_at_5
+      value: 44.468999999999994
+    - type: ndcg_at_1
+      value: 31.518
+    - type: ndcg_at_10
+      value: 51.768
+    - type: ndcg_at_100
+      value: 56.184999999999995
+    - type: ndcg_at_1000
+      value: 56.92
+    - type: ndcg_at_3
+      value: 43.059999999999995
+    - type: ndcg_at_5
+      value: 47.481
+    - type: precision_at_1
+      value: 31.518
+    - type: precision_at_10
+      value: 8.824
+    - type: precision_at_100
+      value: 1.131
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_3
+      value: 19.969
+    - type: precision_at_5
+      value: 14.502
+    - type: recall_at_1
+      value: 27.828999999999997
+    - type: recall_at_10
+      value: 74.244
+    - type: recall_at_100
+      value: 93.325
+    - type: recall_at_1000
+      value: 98.71799999999999
+    - type: recall_at_3
+      value: 51.601
+    - type: recall_at_5
+      value: 61.841
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 71.54
+    - type: map_at_10
+      value: 85.509
+    - type: map_at_100
+      value: 86.137
+    - type: map_at_1000
+      value: 86.151
+    - type: map_at_3
+      value: 82.624
+    - type: map_at_5
+      value: 84.425
+    - type: mrr_at_1
+      value: 82.45
+    - type: mrr_at_10
+      value: 88.344
+    - type: mrr_at_100
+      value: 88.437
+    - type: mrr_at_1000
+      value: 88.437
+    - type: mrr_at_3
+      value: 87.417
+    - type: mrr_at_5
+      value: 88.066
+    - type: ndcg_at_1
+      value: 82.45
+    - type: ndcg_at_10
+      value: 89.092
+    - type: ndcg_at_100
+      value: 90.252
+    - type: ndcg_at_1000
+      value: 90.321
+    - type: ndcg_at_3
+      value: 86.404
+    - type: ndcg_at_5
+      value: 87.883
+    - type: precision_at_1
+      value: 82.45
+    - type: precision_at_10
+      value: 13.496
+    - type: precision_at_100
+      value: 1.536
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 37.833
+    - type: precision_at_5
+      value: 24.79
+    - type: recall_at_1
+      value: 71.54
+    - type: recall_at_10
+      value: 95.846
+    - type: recall_at_100
+      value: 99.715
+    - type: recall_at_1000
+      value: 99.979
+    - type: recall_at_3
+      value: 88.01299999999999
+    - type: recall_at_5
+      value: 92.32000000000001
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 57.60557586253866
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 64.0287172242051
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 3.9849999999999994
+    - type: map_at_10
+      value: 11.397
+    - type: map_at_100
+      value: 13.985
+    - type: map_at_1000
+      value: 14.391000000000002
+    - type: map_at_3
+      value: 7.66
+    - type: map_at_5
+      value: 9.46
+    - type: mrr_at_1
+      value: 19.8
+    - type: mrr_at_10
+      value: 31.958
+    - type: mrr_at_100
+      value: 33.373999999999995
+    - type: mrr_at_1000
+      value: 33.411
+    - type: mrr_at_3
+      value: 28.316999999999997
+    - type: mrr_at_5
+      value: 30.297
+    - type: ndcg_at_1
+      value: 19.8
+    - type: ndcg_at_10
+      value: 19.580000000000002
+    - type: ndcg_at_100
+      value: 29.555999999999997
+    - type: ndcg_at_1000
+      value: 35.882
+    - type: ndcg_at_3
+      value: 17.544
+    - type: ndcg_at_5
+      value: 15.815999999999999
+    - type: precision_at_1
+      value: 19.8
+    - type: precision_at_10
+      value: 10.61
+    - type: precision_at_100
+      value: 2.501
+    - type: precision_at_1000
+      value: 0.40099999999999997
+    - type: precision_at_3
+      value: 16.900000000000002
+    - type: precision_at_5
+      value: 14.44
+    - type: recall_at_1
+      value: 3.9849999999999994
+    - type: recall_at_10
+      value: 21.497
+    - type: recall_at_100
+      value: 50.727999999999994
+    - type: recall_at_1000
+      value: 81.27499999999999
+    - type: recall_at_3
+      value: 10.263
+    - type: recall_at_5
+      value: 14.643
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.0087509585503
+    - type: cos_sim_spearman
+      value: 81.74697270664319
+    - type: euclidean_pearson
+      value: 81.80424382731947
+    - type: euclidean_spearman
+      value: 81.29794251968431
+    - type: manhattan_pearson
+      value: 81.81524666226125
+    - type: manhattan_spearman
+      value: 81.29475370198963
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.44442736429552
+    - type: cos_sim_spearman
+      value: 78.51011398910948
+    - type: euclidean_pearson
+      value: 83.36181801196723
+    - type: euclidean_spearman
+      value: 79.47272621331535
+    - type: manhattan_pearson
+      value: 83.3660113483837
+    - type: manhattan_spearman
+      value: 79.47695922566032
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.82923943323635
+    - type: cos_sim_spearman
+      value: 86.62037823380983
+    - type: euclidean_pearson
+      value: 83.56369548403958
+    - type: euclidean_spearman
+      value: 84.2176755481191
+    - type: manhattan_pearson
+      value: 83.55460702084464
+    - type: manhattan_spearman
+      value: 84.18617930921467
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.09071068110103
+    - type: cos_sim_spearman
+      value: 83.05697553913335
+    - type: euclidean_pearson
+      value: 81.1377457216497
+    - type: euclidean_spearman
+      value: 81.74714169016676
+    - type: manhattan_pearson
+      value: 81.0893424142723
+    - type: manhattan_spearman
+      value: 81.7058918219677
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.61132157220429
+    - type: cos_sim_spearman
+      value: 88.38581627185445
+    - type: euclidean_pearson
+      value: 86.14904510913374
+    - type: euclidean_spearman
+      value: 86.5452758925542
+    - type: manhattan_pearson
+      value: 86.1484025377679
+    - type: manhattan_spearman
+      value: 86.55483841566252
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.46195145161064
+    - type: cos_sim_spearman
+      value: 86.82409112251158
+    - type: euclidean_pearson
+      value: 84.75479672288957
+    - type: euclidean_spearman
+      value: 85.41144307151548
+    - type: manhattan_pearson
+      value: 84.70914329694165
+    - type: manhattan_spearman
+      value: 85.38477943384089
+  - 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: 88.06351289930238
+    - type: cos_sim_spearman
+      value: 87.90311138579116
+    - type: euclidean_pearson
+      value: 86.17651467063077
+    - type: euclidean_spearman
+      value: 84.89447802019073
+    - type: manhattan_pearson
+      value: 86.3267677479595
+    - type: manhattan_spearman
+      value: 85.00472295103874
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 67.78311975978767
+    - type: cos_sim_spearman
+      value: 66.76465685245887
+    - type: euclidean_pearson
+      value: 67.21687806595443
+    - type: euclidean_spearman
+      value: 65.05776733534435
+    - type: manhattan_pearson
+      value: 67.14008143635883
+    - type: manhattan_spearman
+      value: 65.25247076149701
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.7403488889418
+    - type: cos_sim_spearman
+      value: 87.76870289783061
+    - type: euclidean_pearson
+      value: 84.83171077794671
+    - type: euclidean_spearman
+      value: 85.50579695091902
+    - type: manhattan_pearson
+      value: 84.83074260180555
+    - type: manhattan_spearman
+      value: 85.47589026938667
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 87.56234016237356
+    - type: mrr
+      value: 96.26124238869338
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 59.660999999999994
+    - type: map_at_10
+      value: 69.105
+    - type: map_at_100
+      value: 69.78
+    - type: map_at_1000
+      value: 69.80199999999999
+    - type: map_at_3
+      value: 65.991
+    - type: map_at_5
+      value: 68.02
+    - type: mrr_at_1
+      value: 62.666999999999994
+    - type: mrr_at_10
+      value: 70.259
+    - type: mrr_at_100
+      value: 70.776
+    - type: mrr_at_1000
+      value: 70.796
+    - type: mrr_at_3
+      value: 67.889
+    - type: mrr_at_5
+      value: 69.52199999999999
+    - type: ndcg_at_1
+      value: 62.666999999999994
+    - type: ndcg_at_10
+      value: 73.425
+    - type: ndcg_at_100
+      value: 75.955
+    - type: ndcg_at_1000
+      value: 76.459
+    - type: ndcg_at_3
+      value: 68.345
+    - type: ndcg_at_5
+      value: 71.319
+    - type: precision_at_1
+      value: 62.666999999999994
+    - type: precision_at_10
+      value: 9.667
+    - type: precision_at_100
+      value: 1.09
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 26.333000000000002
+    - type: precision_at_5
+      value: 17.732999999999997
+    - type: recall_at_1
+      value: 59.660999999999994
+    - type: recall_at_10
+      value: 85.422
+    - type: recall_at_100
+      value: 96.167
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 72.044
+    - type: recall_at_5
+      value: 79.428
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.86435643564356
+    - type: cos_sim_ap
+      value: 96.83057412333741
+    - type: cos_sim_f1
+      value: 93.04215337734891
+    - type: cos_sim_precision
+      value: 94.53044375644994
+    - type: cos_sim_recall
+      value: 91.60000000000001
+    - type: dot_accuracy
+      value: 99.7910891089109
+    - type: dot_ap
+      value: 94.10681982106397
+    - type: dot_f1
+      value: 89.34881373043918
+    - type: dot_precision
+      value: 90.21406727828746
+    - type: dot_recall
+      value: 88.5
+    - type: euclidean_accuracy
+      value: 99.85544554455446
+    - type: euclidean_ap
+      value: 96.78545104478602
+    - type: euclidean_f1
+      value: 92.65143992055613
+    - type: euclidean_precision
+      value: 92.01183431952663
+    - type: euclidean_recall
+      value: 93.30000000000001
+    - type: manhattan_accuracy
+      value: 99.85841584158416
+    - type: manhattan_ap
+      value: 96.80748903307823
+    - type: manhattan_f1
+      value: 92.78247884519662
+    - type: manhattan_precision
+      value: 92.36868186323092
+    - type: manhattan_recall
+      value: 93.2
+    - type: max_accuracy
+      value: 99.86435643564356
+    - type: max_ap
+      value: 96.83057412333741
+    - type: max_f1
+      value: 93.04215337734891
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 65.53971025855282
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 33.97791591490788
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 55.852215301355066
+    - type: mrr
+      value: 56.85527809608691
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.21442519856758
+    - type: cos_sim_spearman
+      value: 30.822536216936825
+    - type: dot_pearson
+      value: 28.661325528121807
+    - type: dot_spearman
+      value: 28.1435226478879
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.183
+    - type: map_at_10
+      value: 1.526
+    - type: map_at_100
+      value: 7.915
+    - type: map_at_1000
+      value: 19.009
+    - type: map_at_3
+      value: 0.541
+    - type: map_at_5
+      value: 0.8659999999999999
+    - type: mrr_at_1
+      value: 68.0
+    - type: mrr_at_10
+      value: 81.186
+    - type: mrr_at_100
+      value: 81.186
+    - type: mrr_at_1000
+      value: 81.186
+    - type: mrr_at_3
+      value: 80.0
+    - type: mrr_at_5
+      value: 80.9
+    - type: ndcg_at_1
+      value: 64.0
+    - type: ndcg_at_10
+      value: 64.13799999999999
+    - type: ndcg_at_100
+      value: 47.632000000000005
+    - type: ndcg_at_1000
+      value: 43.037
+    - type: ndcg_at_3
+      value: 67.542
+    - type: ndcg_at_5
+      value: 67.496
+    - type: precision_at_1
+      value: 68.0
+    - type: precision_at_10
+      value: 67.80000000000001
+    - type: precision_at_100
+      value: 48.980000000000004
+    - type: precision_at_1000
+      value: 19.036
+    - type: precision_at_3
+      value: 72.0
+    - type: precision_at_5
+      value: 71.2
+    - type: recall_at_1
+      value: 0.183
+    - type: recall_at_10
+      value: 1.799
+    - type: recall_at_100
+      value: 11.652999999999999
+    - type: recall_at_1000
+      value: 40.086
+    - type: recall_at_3
+      value: 0.5930000000000001
+    - type: recall_at_5
+      value: 0.983
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 2.29
+    - type: map_at_10
+      value: 9.489
+    - type: map_at_100
+      value: 15.051
+    - type: map_at_1000
+      value: 16.561999999999998
+    - type: map_at_3
+      value: 5.137
+    - type: map_at_5
+      value: 6.7989999999999995
+    - type: mrr_at_1
+      value: 28.571
+    - type: mrr_at_10
+      value: 45.699
+    - type: mrr_at_100
+      value: 46.461000000000006
+    - type: mrr_at_1000
+      value: 46.461000000000006
+    - type: mrr_at_3
+      value: 41.837
+    - type: mrr_at_5
+      value: 43.163000000000004
+    - type: ndcg_at_1
+      value: 23.469
+    - type: ndcg_at_10
+      value: 23.544999999999998
+    - type: ndcg_at_100
+      value: 34.572
+    - type: ndcg_at_1000
+      value: 46.035
+    - type: ndcg_at_3
+      value: 27.200000000000003
+    - type: ndcg_at_5
+      value: 25.266
+    - type: precision_at_1
+      value: 28.571
+    - type: precision_at_10
+      value: 22.041
+    - type: precision_at_100
+      value: 7.3469999999999995
+    - type: precision_at_1000
+      value: 1.484
+    - type: precision_at_3
+      value: 29.932
+    - type: precision_at_5
+      value: 26.531
+    - type: recall_at_1
+      value: 2.29
+    - type: recall_at_10
+      value: 15.895999999999999
+    - type: recall_at_100
+      value: 45.518
+    - type: recall_at_1000
+      value: 80.731
+    - type: recall_at_3
+      value: 6.433
+    - type: recall_at_5
+      value: 9.484
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 71.4178
+    - type: ap
+      value: 14.575240629602373
+    - type: f1
+      value: 55.02449563229096
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 60.00282965478212
+    - type: f1
+      value: 60.34413028768773
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 50.409448342549936
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 87.62591643321214
+    - type: cos_sim_ap
+      value: 79.28766491329633
+    - type: cos_sim_f1
+      value: 71.98772064466617
+    - type: cos_sim_precision
+      value: 69.8609731876862
+    - type: cos_sim_recall
+      value: 74.24802110817942
+    - type: dot_accuracy
+      value: 84.75293556654945
+    - type: dot_ap
+      value: 69.72705761174353
+    - type: dot_f1
+      value: 65.08692852543464
+    - type: dot_precision
+      value: 63.57232704402516
+    - type: dot_recall
+      value: 66.6754617414248
+    - type: euclidean_accuracy
+      value: 87.44710019669786
+    - type: euclidean_ap
+      value: 79.11021477292638
+    - type: euclidean_f1
+      value: 71.5052389470994
+    - type: euclidean_precision
+      value: 69.32606541129832
+    - type: euclidean_recall
+      value: 73.82585751978891
+    - type: manhattan_accuracy
+      value: 87.42325803182929
+    - type: manhattan_ap
+      value: 79.05094494327616
+    - type: manhattan_f1
+      value: 71.36333985649055
+    - type: manhattan_precision
+      value: 70.58064516129032
+    - type: manhattan_recall
+      value: 72.16358839050132
+    - type: max_accuracy
+      value: 87.62591643321214
+    - type: max_ap
+      value: 79.28766491329633
+    - type: max_f1
+      value: 71.98772064466617
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.85202002561415
+    - type: cos_sim_ap
+      value: 85.9835303311168
+    - type: cos_sim_f1
+      value: 78.25741142443962
+    - type: cos_sim_precision
+      value: 73.76635768811342
+    - type: cos_sim_recall
+      value: 83.3307668617185
+    - type: dot_accuracy
+      value: 88.20584468506229
+    - type: dot_ap
+      value: 83.591632302697
+    - type: dot_f1
+      value: 76.81739705396173
+    - type: dot_precision
+      value: 73.45275728837373
+    - type: dot_recall
+      value: 80.50508161379734
+    - type: euclidean_accuracy
+      value: 88.64633057787093
+    - type: euclidean_ap
+      value: 85.25705123182283
+    - type: euclidean_f1
+      value: 77.18535726329199
+    - type: euclidean_precision
+      value: 75.17699437997226
+    - type: euclidean_recall
+      value: 79.30397289805975
+    - type: manhattan_accuracy
+      value: 88.63274731245392
+    - type: manhattan_ap
+      value: 85.2376825633018
+    - type: manhattan_f1
+      value: 77.15810785937788
+    - type: manhattan_precision
+      value: 73.92255061014319
+    - type: manhattan_recall
+      value: 80.68986757006468
+    - type: max_accuracy
+      value: 88.85202002561415
+    - type: max_ap
+      value: 85.9835303311168
+    - type: max_f1
+      value: 78.25741142443962
 ---
+
+# ember-v1
+
+<p align="center">
+<img src="https://console.llmrails.com/assets/img/logo-black.svg" width="150px">
+</p>
+
+This model has been trained on an extensive corpus of text pairs that encompass a broad spectrum of domains, including finance, science, medicine, law, and various others. During the training process, we incorporated techniques derived from the [RetroMAE](https://arxiv.org/abs/2205.12035) and [SetFit](https://arxiv.org/abs/2209.11055) research papers.
+
+We are pleased to offer this model as an API service through our platform, [LLMRails](https://llmrails.com/?ref=ember-v1). If you are interested, please don't hesitate to sign up.
+
+### Plans
+- The research paper will be published soon.
+-  The v2 of the model is currently in development and will feature an extended maximum sequence length of 4,000 tokens.
+
+## Usage
+Use with API request:
+```bash
+curl --location 'https://api.llmrails.com/v1/embeddings' \
+--header 'X-API-KEY: {token}' \
+--header 'Content-Type: application/json' \
+--data '{
+   "input": ["This is an example sentence"],
+   "model":"embedding-english-v1" # equals to ember-v1
+}'
+```
+API docs: https://docs.llmrails.com/embedding/embed-text<br>
+Langchain plugin: https://python.langchain.com/docs/integrations/text_embedding/llm_rails
+
+Use with transformers:
+```python
+import torch.nn.functional as F
+from torch import Tensor
+from transformers import AutoTokenizer, AutoModel
+
+def average_pool(last_hidden_states: Tensor,
+                 attention_mask: Tensor) -> Tensor:
+    last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0)
+    return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None]
+
+input_texts = [
+    "This is an example sentence",
+    "Each sentence is converted"
+]
+
+tokenizer = AutoTokenizer.from_pretrained("llmrails/ember-v1")
+model = AutoModel.from_pretrained("llmrails/ember-v1")
+
+# Tokenize the input texts
+batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')
+
+outputs = model(**batch_dict)
+embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask'])
+
+# (Optionally) normalize embeddings
+embeddings = F.normalize(embeddings, p=2, dim=1)
+scores = (embeddings[:1] @ embeddings[1:].T) * 100
+print(scores.tolist())
+```
+
+Use with sentence-transformers:
+```python
+from sentence_transformers import SentenceTransformer
+from sentence_transformers.util import cos_sim
+
+sentences = [
+	"This is an example sentence",
+    "Each sentence is converted"
+]
+
+model = SentenceTransformer('llmrails/ember-v1')
+embeddings = model.encode(sentences)
+print(cos_sim(embeddings[0], embeddings[1]))
+```
+
+## Massive Text Embedding Benchmark (MTEB) Evaluation
+Our model achieve state-of-the-art performance on [MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard)
+
+|                               Model Name                                | Dimension | Sequence Length | Average (56) | 
+|:-----------------------------------------------------------------------:|:---------:|:---:|:------------:|
+| [bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) |   1024    |       512       |    64.23     |  
+| [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) |   768    |       512       |    63.55     |
+| [ember-v1](https://huggingface.co/llmrails/emmbedding-en-v1) |   1024    | 512 |    **63.54**     |  
+| [text-embedding-ada-002](https://platform.openai.com/docs/guides/embeddings/types-of-embedding-models) |   1536    |      8191       |    60.99     |
+
+### Limitation
+
+This model exclusively caters to English texts, and any lengthy texts will be truncated to a maximum of 512 tokens.

config.json

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+{
+  "_name_or_path": "/root/.cache/torch/sentence_transformers/llmrails_luna-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": "4.33.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

config_sentence_transformers.json

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+{
+  "__version__": {
+    "sentence_transformers": "2.2.2",
+    "transformers": "4.28.1",
+    "pytorch": "1.13.0+cu117"
+  }
+}

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modules.json

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+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

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onnx/model_quantized.onnx

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quantize_config.json

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+{
+    "per_channel": true,
+    "reduce_range": true,
+    "per_model_config": {
+        "model": {
+            "op_types": [
+                "Mul",
+                "Div",
+                "Gather",
+                "Constant",
+                "Reshape",
+                "Cast",
+                "Slice",
+                "Sub",
+                "Sqrt",
+                "Unsqueeze",
+                "Add",
+                "Transpose",
+                "Softmax",
+                "ReduceMean",
+                "Shape",
+                "Concat",
+                "Erf",
+                "MatMul",
+                "Pow"
+            ],
+            "weight_type": "QInt8"
+        }
+    }
+}

sentence_bert_config.json

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+{
+  "max_seq_length": 512,
+  "do_lower_case": true
+}

special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "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]"
+}