Update README.md

README.md

@@ -1,1874 +1,7 @@
 ---
 tags:
 - feature-extraction
-- mteb
 pipeline_tag: feature-extraction
-model-index:
-- name: dragon-plus
-  results:
-  - task:
-      type: Retrieval
-    dataset:
-      type: arguana
-      name: MTEB ArguAna
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 22.973
-    - type: map_at_10
-      value: 38.242
-    - type: map_at_100
-      value: 39.326
-    - type: map_at_1000
-      value: 39.342
-    - type: map_at_3
-      value: 33.144
-    - type: map_at_5
-      value: 35.818
-    - type: mrr_at_1
-      value: 23.115
-    - type: mrr_at_10
-      value: 38.31
-    - type: mrr_at_100
-      value: 39.387
-    - type: mrr_at_1000
-      value: 39.403
-    - type: mrr_at_3
-      value: 33.167
-    - type: mrr_at_5
-      value: 35.856
-    - type: ndcg_at_1
-      value: 22.973
-    - type: ndcg_at_10
-      value: 47.251
-    - type: ndcg_at_100
-      value: 51.937
-    - type: ndcg_at_1000
-      value: 52.288000000000004
-    - type: ndcg_at_3
-      value: 36.569
-    - type: ndcg_at_5
-      value: 41.396
-    - type: precision_at_1
-      value: 22.973
-    - type: precision_at_10
-      value: 7.632
-    - type: precision_at_100
-      value: 0.9690000000000001
-    - type: precision_at_1000
-      value: 0.1
-    - type: precision_at_3
-      value: 15.504999999999999
-    - type: precision_at_5
-      value: 11.65
-    - type: recall_at_1
-      value: 22.973
-    - type: recall_at_10
-      value: 76.31599999999999
-    - type: recall_at_100
-      value: 96.942
-    - type: recall_at_1000
-      value: 99.57300000000001
-    - type: recall_at_3
-      value: 46.515
-    - type: recall_at_5
-      value: 58.25
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackAndroidRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 28.793000000000003
-    - type: map_at_10
-      value: 38.686
-    - type: map_at_100
-      value: 39.848
-    - type: map_at_1000
-      value: 39.989999999999995
-    - type: map_at_3
-      value: 35.437000000000005
-    - type: map_at_5
-      value: 37.067
-    - type: mrr_at_1
-      value: 35.05
-    - type: mrr_at_10
-      value: 43.903999999999996
-    - type: mrr_at_100
-      value: 44.612
-    - type: mrr_at_1000
-      value: 44.669
-    - type: mrr_at_3
-      value: 41.321000000000005
-    - type: mrr_at_5
-      value: 42.573
-    - type: ndcg_at_1
-      value: 35.05
-    - type: ndcg_at_10
-      value: 44.564
-    - type: ndcg_at_100
-      value: 49.252
-    - type: ndcg_at_1000
-      value: 51.791
-    - type: ndcg_at_3
-      value: 39.576
-    - type: ndcg_at_5
-      value: 41.426
-    - type: precision_at_1
-      value: 35.05
-    - type: precision_at_10
-      value: 8.455
-    - type: precision_at_100
-      value: 1.3299999999999998
-    - type: precision_at_1000
-      value: 0.187
-    - type: precision_at_3
-      value: 18.645999999999997
-    - type: precision_at_5
-      value: 13.247
-    - type: recall_at_1
-      value: 28.793000000000003
-    - type: recall_at_10
-      value: 56.351
-    - type: recall_at_100
-      value: 76.542
-    - type: recall_at_1000
-      value: 93.14099999999999
-    - type: recall_at_3
-      value: 41.581
-    - type: recall_at_5
-      value: 47.066
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackEnglishRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 29.828
-    - type: map_at_10
-      value: 39.312999999999995
-    - type: map_at_100
-      value: 40.487
-    - type: map_at_1000
-      value: 40.607
-    - type: map_at_3
-      value: 36.525
-    - type: map_at_5
-      value: 38.121
-    - type: mrr_at_1
-      value: 37.197
-    - type: mrr_at_10
-      value: 45.091
-    - type: mrr_at_100
-      value: 45.726
-    - type: mrr_at_1000
-      value: 45.769999999999996
-    - type: mrr_at_3
-      value: 42.856
-    - type: mrr_at_5
-      value: 44.056
-    - type: ndcg_at_1
-      value: 37.197
-    - type: ndcg_at_10
-      value: 44.737
-    - type: ndcg_at_100
-      value: 49.02
-    - type: ndcg_at_1000
-      value: 51.052
-    - type: ndcg_at_3
-      value: 40.685
-    - type: ndcg_at_5
-      value: 42.519
-    - type: precision_at_1
-      value: 37.197
-    - type: precision_at_10
-      value: 8.363
-    - type: precision_at_100
-      value: 1.329
-    - type: precision_at_1000
-      value: 0.179
-    - type: precision_at_3
-      value: 19.533
-    - type: precision_at_5
-      value: 13.732
-    - type: recall_at_1
-      value: 29.828
-    - type: recall_at_10
-      value: 54.339000000000006
-    - type: recall_at_100
-      value: 72.217
-    - type: recall_at_1000
-      value: 85.185
-    - type: recall_at_3
-      value: 42.331
-    - type: recall_at_5
-      value: 47.612
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGamingRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 37.919000000000004
-    - type: map_at_10
-      value: 49.225
-    - type: map_at_100
-      value: 50.306
-    - type: map_at_1000
-      value: 50.364
-    - type: map_at_3
-      value: 46.459
-    - type: map_at_5
-      value: 48.173
-    - type: mrr_at_1
-      value: 43.072
-    - type: mrr_at_10
-      value: 52.437
-    - type: mrr_at_100
-      value: 53.2
-    - type: mrr_at_1000
-      value: 53.233
-    - type: mrr_at_3
-      value: 50.219
-    - type: mrr_at_5
-      value: 51.629999999999995
-    - type: ndcg_at_1
-      value: 43.072
-    - type: ndcg_at_10
-      value: 54.468
-    - type: ndcg_at_100
-      value: 58.912
-    - type: ndcg_at_1000
-      value: 60.179
-    - type: ndcg_at_3
-      value: 49.836999999999996
-    - type: ndcg_at_5
-      value: 52.371
-    - type: precision_at_1
-      value: 43.072
-    - type: precision_at_10
-      value: 8.52
-    - type: precision_at_100
-      value: 1.168
-    - type: precision_at_1000
-      value: 0.133
-    - type: precision_at_3
-      value: 21.923000000000002
-    - type: precision_at_5
-      value: 14.997
-    - type: recall_at_1
-      value: 37.919000000000004
-    - type: recall_at_10
-      value: 66.682
-    - type: recall_at_100
-      value: 85.81
-    - type: recall_at_1000
-      value: 94.812
-    - type: recall_at_3
-      value: 54.515
-    - type: recall_at_5
-      value: 60.684000000000005
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGisRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.04
-    - type: map_at_10
-      value: 27.665
-    - type: map_at_100
-      value: 28.716
-    - type: map_at_1000
-      value: 28.794999999999998
-    - type: map_at_3
-      value: 25.338
-    - type: map_at_5
-      value: 26.815
-    - type: mrr_at_1
-      value: 22.712
-    - type: mrr_at_10
-      value: 29.447000000000003
-    - type: mrr_at_100
-      value: 30.457
-    - type: mrr_at_1000
-      value: 30.522
-    - type: mrr_at_3
-      value: 27.119
-    - type: mrr_at_5
-      value: 28.582
-    - type: ndcg_at_1
-      value: 22.712
-    - type: ndcg_at_10
-      value: 31.77
-    - type: ndcg_at_100
-      value: 37.104
-    - type: ndcg_at_1000
-      value: 39.371
-    - type: ndcg_at_3
-      value: 27.171
-    - type: ndcg_at_5
-      value: 29.698999999999998
-    - type: precision_at_1
-      value: 22.712
-    - type: precision_at_10
-      value: 4.859
-    - type: precision_at_100
-      value: 0.7929999999999999
-    - type: precision_at_1000
-      value: 0.10300000000000001
-    - type: precision_at_3
-      value: 11.299
-    - type: precision_at_5
-      value: 8.203000000000001
-    - type: recall_at_1
-      value: 21.04
-    - type: recall_at_10
-      value: 42.848000000000006
-    - type: recall_at_100
-      value: 67.694
-    - type: recall_at_1000
-      value: 85.179
-    - type: recall_at_3
-      value: 30.54
-    - type: recall_at_5
-      value: 36.555
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackMathematicaRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 13.403
-    - type: map_at_10
-      value: 19.663
-    - type: map_at_100
-      value: 20.799
-    - type: map_at_1000
-      value: 20.915
-    - type: map_at_3
-      value: 17.465
-    - type: map_at_5
-      value: 18.665000000000003
-    - type: mrr_at_1
-      value: 16.418
-    - type: mrr_at_10
-      value: 23.394000000000002
-    - type: mrr_at_100
-      value: 24.363
-    - type: mrr_at_1000
-      value: 24.44
-    - type: mrr_at_3
-      value: 20.916
-    - type: mrr_at_5
-      value: 22.241
-    - type: ndcg_at_1
-      value: 16.418
-    - type: ndcg_at_10
-      value: 24.013
-    - type: ndcg_at_100
-      value: 29.62
-    - type: ndcg_at_1000
-      value: 32.518
-    - type: ndcg_at_3
-      value: 19.747
-    - type: ndcg_at_5
-      value: 21.689
-    - type: precision_at_1
-      value: 16.418
-    - type: precision_at_10
-      value: 4.515000000000001
-    - type: precision_at_100
-      value: 0.8410000000000001
-    - type: precision_at_1000
-      value: 0.123
-    - type: precision_at_3
-      value: 9.411
-    - type: precision_at_5
-      value: 6.965000000000001
-    - type: recall_at_1
-      value: 13.403
-    - type: recall_at_10
-      value: 33.731
-    - type: recall_at_100
-      value: 58.743
-    - type: recall_at_1000
-      value: 79.343
-    - type: recall_at_3
-      value: 22.148
-    - type: recall_at_5
-      value: 26.998
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackPhysicsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 25.782
-    - type: map_at_10
-      value: 34.891
-    - type: map_at_100
-      value: 36.186
-    - type: map_at_1000
-      value: 36.303999999999995
-    - type: map_at_3
-      value: 32.099
-    - type: map_at_5
-      value: 33.777
-    - type: mrr_at_1
-      value: 30.895
-    - type: mrr_at_10
-      value: 40.049
-    - type: mrr_at_100
-      value: 40.953
-    - type: mrr_at_1000
-      value: 41.0
-    - type: mrr_at_3
-      value: 37.424
-    - type: mrr_at_5
-      value: 39.07
-    - type: ndcg_at_1
-      value: 30.895
-    - type: ndcg_at_10
-      value: 40.436
-    - type: ndcg_at_100
-      value: 46.046
-    - type: ndcg_at_1000
-      value: 48.324
-    - type: ndcg_at_3
-      value: 35.66
-    - type: ndcg_at_5
-      value: 38.167
-    - type: precision_at_1
-      value: 30.895
-    - type: precision_at_10
-      value: 7.151000000000001
-    - type: precision_at_100
-      value: 1.171
-    - type: precision_at_1000
-      value: 0.155
-    - type: precision_at_3
-      value: 16.619
-    - type: precision_at_5
-      value: 11.935
-    - type: recall_at_1
-      value: 25.782
-    - type: recall_at_10
-      value: 52.013
-    - type: recall_at_100
-      value: 75.736
-    - type: recall_at_1000
-      value: 90.823
-    - type: recall_at_3
-      value: 38.763
-    - type: recall_at_5
-      value: 45.023
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackProgrammersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 22.491
-    - type: map_at_10
-      value: 30.434
-    - type: map_at_100
-      value: 31.611
-    - type: map_at_1000
-      value: 31.732
-    - type: map_at_3
-      value: 27.776
-    - type: map_at_5
-      value: 29.271
-    - type: mrr_at_1
-      value: 27.74
-    - type: mrr_at_10
-      value: 34.964
-    - type: mrr_at_100
-      value: 35.943000000000005
-    - type: mrr_at_1000
-      value: 36.012
-    - type: mrr_at_3
-      value: 32.667
-    - type: mrr_at_5
-      value: 33.975
-    - type: ndcg_at_1
-      value: 27.74
-    - type: ndcg_at_10
-      value: 35.32
-    - type: ndcg_at_100
-      value: 40.812
-    - type: ndcg_at_1000
-      value: 43.49
-    - type: ndcg_at_3
-      value: 30.843999999999998
-    - type: ndcg_at_5
-      value: 32.838
-    - type: precision_at_1
-      value: 27.74
-    - type: precision_at_10
-      value: 6.358
-    - type: precision_at_100
-      value: 1.078
-    - type: precision_at_1000
-      value: 0.147
-    - type: precision_at_3
-      value: 14.421999999999999
-    - type: precision_at_5
-      value: 10.32
-    - type: recall_at_1
-      value: 22.491
-    - type: recall_at_10
-      value: 45.659
-    - type: recall_at_100
-      value: 69.303
-    - type: recall_at_1000
-      value: 87.849
-    - type: recall_at_3
-      value: 33.155
-    - type: recall_at_5
-      value: 38.369
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 22.955500000000008
-    - type: map_at_10
-      value: 30.754000000000005
-    - type: map_at_100
-      value: 31.85208333333333
-    - type: map_at_1000
-      value: 31.968416666666666
-    - type: map_at_3
-      value: 28.35166666666667
-    - type: map_at_5
-      value: 29.717333333333336
-    - type: mrr_at_1
-      value: 27.0815
-    - type: mrr_at_10
-      value: 34.50116666666666
-    - type: mrr_at_100
-      value: 35.361583333333336
-    - type: mrr_at_1000
-      value: 35.42583333333334
-    - type: mrr_at_3
-      value: 32.30499999999999
-    - type: mrr_at_5
-      value: 33.56175
-    - type: ndcg_at_1
-      value: 27.0815
-    - type: ndcg_at_10
-      value: 35.40033333333333
-    - type: ndcg_at_100
-      value: 40.3485
-    - type: ndcg_at_1000
-      value: 42.86816666666667
-    - type: ndcg_at_3
-      value: 31.24325
-    - type: ndcg_at_5
-      value: 33.21525
-    - type: precision_at_1
-      value: 27.0815
-    - type: precision_at_10
-      value: 6.118666666666667
-    - type: precision_at_100
-      value: 1.0085833333333334
-    - type: precision_at_1000
-      value: 0.14150000000000001
-    - type: precision_at_3
-      value: 14.19175
-    - type: precision_at_5
-      value: 10.064583333333331
-    - type: recall_at_1
-      value: 22.955500000000008
-    - type: recall_at_10
-      value: 45.51058333333333
-    - type: recall_at_100
-      value: 67.49925
-    - type: recall_at_1000
-      value: 85.24766666666666
-    - type: recall_at_3
-      value: 33.885
-    - type: recall_at_5
-      value: 38.99608333333334
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackStatsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 21.371000000000002
-    - type: map_at_10
-      value: 27.532
-    - type: map_at_100
-      value: 28.443
-    - type: map_at_1000
-      value: 28.525
-    - type: map_at_3
-      value: 25.689
-    - type: map_at_5
-      value: 26.677
-    - type: mrr_at_1
-      value: 24.08
-    - type: mrr_at_10
-      value: 30.128
-    - type: mrr_at_100
-      value: 30.953999999999997
-    - type: mrr_at_1000
-      value: 31.022
-    - type: mrr_at_3
-      value: 28.298000000000002
-    - type: mrr_at_5
-      value: 29.317
-    - type: ndcg_at_1
-      value: 24.08
-    - type: ndcg_at_10
-      value: 31.212
-    - type: ndcg_at_100
-      value: 35.72
-    - type: ndcg_at_1000
-      value: 38.061
-    - type: ndcg_at_3
-      value: 27.705000000000002
-    - type: ndcg_at_5
-      value: 29.26
-    - type: precision_at_1
-      value: 24.08
-    - type: precision_at_10
-      value: 4.8469999999999995
-    - type: precision_at_100
-      value: 0.753
-    - type: precision_at_1000
-      value: 0.104
-    - type: precision_at_3
-      value: 11.759
-    - type: precision_at_5
-      value: 8.097999999999999
-    - type: recall_at_1
-      value: 21.371000000000002
-    - type: recall_at_10
-      value: 40.089000000000006
-    - type: recall_at_100
-      value: 60.879000000000005
-    - type: recall_at_1000
-      value: 78.325
-    - type: recall_at_3
-      value: 30.175
-    - type: recall_at_5
-      value: 34.168
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackTexRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 15.043999999999999
-    - type: map_at_10
-      value: 20.794
-    - type: map_at_100
-      value: 21.636
-    - type: map_at_1000
-      value: 21.753
-    - type: map_at_3
-      value: 19.006
-    - type: map_at_5
-      value: 19.994999999999997
-    - type: mrr_at_1
-      value: 18.066
-    - type: mrr_at_10
-      value: 24.157999999999998
-    - type: mrr_at_100
-      value: 24.936
-    - type: mrr_at_1000
-      value: 25.018
-    - type: mrr_at_3
-      value: 22.345000000000002
-    - type: mrr_at_5
-      value: 23.396
-    - type: ndcg_at_1
-      value: 18.066
-    - type: ndcg_at_10
-      value: 24.584
-    - type: ndcg_at_100
-      value: 28.869
-    - type: ndcg_at_1000
-      value: 31.94
-    - type: ndcg_at_3
-      value: 21.295
-    - type: ndcg_at_5
-      value: 22.820999999999998
-    - type: precision_at_1
-      value: 18.066
-    - type: precision_at_10
-      value: 4.381
-    - type: precision_at_100
-      value: 0.754
-    - type: precision_at_1000
-      value: 0.117
-    - type: precision_at_3
-      value: 9.956
-    - type: precision_at_5
-      value: 7.123
-    - type: recall_at_1
-      value: 15.043999999999999
-    - type: recall_at_10
-      value: 32.665
-    - type: recall_at_100
-      value: 52.342
-    - type: recall_at_1000
-      value: 74.896
-    - type: recall_at_3
-      value: 23.402
-    - type: recall_at_5
-      value: 27.397
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackUnixRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 22.712
-    - type: map_at_10
-      value: 28.963
-    - type: map_at_100
-      value: 29.934
-    - type: map_at_1000
-      value: 30.049
-    - type: map_at_3
-      value: 27.086
-    - type: map_at_5
-      value: 28.163
-    - type: mrr_at_1
-      value: 26.586
-    - type: mrr_at_10
-      value: 32.792
-    - type: mrr_at_100
-      value: 33.692
-    - type: mrr_at_1000
-      value: 33.767
-    - type: mrr_at_3
-      value: 30.939
-    - type: mrr_at_5
-      value: 32.012
-    - type: ndcg_at_1
-      value: 26.586
-    - type: ndcg_at_10
-      value: 32.92
-    - type: ndcg_at_100
-      value: 37.891000000000005
-    - type: ndcg_at_1000
-      value: 40.647
-    - type: ndcg_at_3
-      value: 29.465000000000003
-    - type: ndcg_at_5
-      value: 31.106
-    - type: precision_at_1
-      value: 26.586
-    - type: precision_at_10
-      value: 5.177
-    - type: precision_at_100
-      value: 0.8540000000000001
-    - type: precision_at_1000
-      value: 0.121
-    - type: precision_at_3
-      value: 12.903999999999998
-    - type: precision_at_5
-      value: 8.881
-    - type: recall_at_1
-      value: 22.712
-    - type: recall_at_10
-      value: 41.382000000000005
-    - type: recall_at_100
-      value: 63.866
-    - type: recall_at_1000
-      value: 83.29299999999999
-    - type: recall_at_3
-      value: 31.739
-    - type: recall_at_5
-      value: 35.988
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWebmastersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 19.64
-    - type: map_at_10
-      value: 28.432000000000002
-    - type: map_at_100
-      value: 29.848999999999997
-    - type: map_at_1000
-      value: 30.072
-    - type: map_at_3
-      value: 25.862000000000002
-    - type: map_at_5
-      value: 27.339000000000002
-    - type: mrr_at_1
-      value: 24.308
-    - type: mrr_at_10
-      value: 32.475
-    - type: mrr_at_100
-      value: 33.404
-    - type: mrr_at_1000
-      value: 33.477000000000004
-    - type: mrr_at_3
-      value: 30.203999999999997
-    - type: mrr_at_5
-      value: 31.558000000000003
-    - type: ndcg_at_1
-      value: 24.308
-    - type: ndcg_at_10
-      value: 33.79
-    - type: ndcg_at_100
-      value: 39.113
-    - type: ndcg_at_1000
-      value: 42.388
-    - type: ndcg_at_3
-      value: 29.738999999999997
-    - type: ndcg_at_5
-      value: 31.734
-    - type: precision_at_1
-      value: 24.308
-    - type: precision_at_10
-      value: 6.621
-    - type: precision_at_100
-      value: 1.322
-    - type: precision_at_1000
-      value: 0.22499999999999998
-    - type: precision_at_3
-      value: 14.032
-    - type: precision_at_5
-      value: 10.435
-    - type: recall_at_1
-      value: 19.64
-    - type: recall_at_10
-      value: 44.147999999999996
-    - type: recall_at_100
-      value: 68.31099999999999
-    - type: recall_at_1000
-      value: 90.022
-    - type: recall_at_3
-      value: 32.275999999999996
-    - type: recall_at_5
-      value: 37.717
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWordpressRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 17.443
-    - type: map_at_10
-      value: 23.45
-    - type: map_at_100
-      value: 24.41
-    - type: map_at_1000
-      value: 24.515
-    - type: map_at_3
-      value: 21.478
-    - type: map_at_5
-      value: 22.545
-    - type: mrr_at_1
-      value: 18.854000000000003
-    - type: mrr_at_10
-      value: 25.174999999999997
-    - type: mrr_at_100
-      value: 26.099
-    - type: mrr_at_1000
-      value: 26.179999999999996
-    - type: mrr_at_3
-      value: 23.352
-    - type: mrr_at_5
-      value: 24.331
-    - type: ndcg_at_1
-      value: 18.854000000000003
-    - type: ndcg_at_10
-      value: 26.99
-    - type: ndcg_at_100
-      value: 31.823
-    - type: ndcg_at_1000
-      value: 34.657
-    - type: ndcg_at_3
-      value: 23.195
-    - type: ndcg_at_5
-      value: 24.953
-    - type: precision_at_1
-      value: 18.854000000000003
-    - type: precision_at_10
-      value: 4.1770000000000005
-    - type: precision_at_100
-      value: 0.7100000000000001
-    - type: precision_at_1000
-      value: 0.104
-    - type: precision_at_3
-      value: 9.797
-    - type: precision_at_5
-      value: 6.839
-    - type: recall_at_1
-      value: 17.443
-    - type: recall_at_10
-      value: 36.22
-    - type: recall_at_100
-      value: 58.548
-    - type: recall_at_1000
-      value: 80.104
-    - type: recall_at_3
-      value: 25.995
-    - type: recall_at_5
-      value: 30.375999999999998
-  - task:
-      type: Retrieval
-    dataset:
-      type: climate-fever
-      name: MTEB ClimateFEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 10.283000000000001
-    - type: map_at_10
-      value: 16.121
-    - type: map_at_100
-      value: 17.818
-    - type: map_at_1000
-      value: 18.015
-    - type: map_at_3
-      value: 13.655000000000001
-    - type: map_at_5
-      value: 14.854999999999999
-    - type: mrr_at_1
-      value: 22.15
-    - type: mrr_at_10
-      value: 31.139
-    - type: mrr_at_100
-      value: 32.336999999999996
-    - type: mrr_at_1000
-      value: 32.39
-    - type: mrr_at_3
-      value: 27.861000000000004
-    - type: mrr_at_5
-      value: 29.754
-    - type: ndcg_at_1
-      value: 22.15
-    - type: ndcg_at_10
-      value: 22.852
-    - type: ndcg_at_100
-      value: 30.233999999999998
-    - type: ndcg_at_1000
-      value: 34.02
-    - type: ndcg_at_3
-      value: 18.394
-    - type: ndcg_at_5
-      value: 19.973
-    - type: precision_at_1
-      value: 22.15
-    - type: precision_at_10
-      value: 6.912
-    - type: precision_at_100
-      value: 1.4829999999999999
-    - type: precision_at_1000
-      value: 0.218
-    - type: precision_at_3
-      value: 12.899
-    - type: precision_at_5
-      value: 10.111
-    - type: recall_at_1
-      value: 10.283000000000001
-    - type: recall_at_10
-      value: 27.587
-    - type: recall_at_100
-      value: 53.273
-    - type: recall_at_1000
-      value: 74.74499999999999
-    - type: recall_at_3
-      value: 16.897000000000002
-    - type: recall_at_5
-      value: 21.084
-  - task:
-      type: Retrieval
-    dataset:
-      type: dbpedia-entity
-      name: MTEB DBPedia
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 9.038
-    - type: map_at_10
-      value: 20.153
-    - type: map_at_100
-      value: 28.610999999999997
-    - type: map_at_1000
-      value: 30.285
-    - type: map_at_3
-      value: 14.249
-    - type: map_at_5
-      value: 16.715
-    - type: mrr_at_1
-      value: 66.75
-    - type: mrr_at_10
-      value: 74.477
-    - type: mrr_at_100
-      value: 74.678
-    - type: mrr_at_1000
-      value: 74.695
-    - type: mrr_at_3
-      value: 72.625
-    - type: mrr_at_5
-      value: 73.8
-    - type: ndcg_at_1
-      value: 55.125
-    - type: ndcg_at_10
-      value: 41.837999999999994
-    - type: ndcg_at_100
-      value: 46.182
-    - type: ndcg_at_1000
-      value: 53.144000000000005
-    - type: ndcg_at_3
-      value: 46.084
-    - type: ndcg_at_5
-      value: 43.751
-    - type: precision_at_1
-      value: 66.75
-    - type: precision_at_10
-      value: 33.775
-    - type: precision_at_100
-      value: 10.803
-    - type: precision_at_1000
-      value: 2.191
-    - type: precision_at_3
-      value: 49.5
-    - type: precision_at_5
-      value: 42.4
-    - type: recall_at_1
-      value: 9.038
-    - type: recall_at_10
-      value: 25.988
-    - type: recall_at_100
-      value: 52.158
-    - type: recall_at_1000
-      value: 74.617
-    - type: recall_at_3
-      value: 15.675
-    - type: recall_at_5
-      value: 19.570999999999998
-  - task:
-      type: Retrieval
-    dataset:
-      type: fever
-      name: MTEB FEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 62.551
-    - type: map_at_10
-      value: 73.124
-    - type: map_at_100
-      value: 73.432
-    - type: map_at_1000
-      value: 73.447
-    - type: map_at_3
-      value: 71.297
-    - type: map_at_5
-      value: 72.489
-    - type: mrr_at_1
-      value: 67.23700000000001
-    - type: mrr_at_10
-      value: 77.438
-    - type: mrr_at_100
-      value: 77.645
-    - type: mrr_at_1000
-      value: 77.64999999999999
-    - type: mrr_at_3
-      value: 75.788
-    - type: mrr_at_5
-      value: 76.886
-    - type: ndcg_at_1
-      value: 67.23700000000001
-    - type: ndcg_at_10
-      value: 78.306
-    - type: ndcg_at_100
-      value: 79.526
-    - type: ndcg_at_1000
-      value: 79.825
-    - type: ndcg_at_3
-      value: 74.961
-    - type: ndcg_at_5
-      value: 76.91900000000001
-    - type: precision_at_1
-      value: 67.23700000000001
-    - type: precision_at_10
-      value: 9.875
-    - type: precision_at_100
-      value: 1.065
-    - type: precision_at_1000
-      value: 0.11
-    - type: precision_at_3
-      value: 29.353
-    - type: precision_at_5
-      value: 18.749
-    - type: recall_at_1
-      value: 62.551
-    - type: recall_at_10
-      value: 90.011
-    - type: recall_at_100
-      value: 95.06
-    - type: recall_at_1000
-      value: 97.033
-    - type: recall_at_3
-      value: 81.081
-    - type: recall_at_5
-      value: 85.87599999999999
-  - task:
-      type: Retrieval
-    dataset:
-      type: fiqa
-      name: MTEB FiQA2018
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 17.636
-    - type: map_at_10
-      value: 28.627000000000002
-    - type: map_at_100
-      value: 30.262
-    - type: map_at_1000
-      value: 30.442000000000004
-    - type: map_at_3
-      value: 25.091
-    - type: map_at_5
-      value: 27.12
-    - type: mrr_at_1
-      value: 34.259
-    - type: mrr_at_10
-      value: 42.733
-    - type: mrr_at_100
-      value: 43.613
-    - type: mrr_at_1000
-      value: 43.663000000000004
-    - type: mrr_at_3
-      value: 40.406
-    - type: mrr_at_5
-      value: 41.687000000000005
-    - type: ndcg_at_1
-      value: 34.259
-    - type: ndcg_at_10
-      value: 35.613
-    - type: ndcg_at_100
-      value: 42.027
-    - type: ndcg_at_1000
-      value: 45.336999999999996
-    - type: ndcg_at_3
-      value: 32.435
-    - type: ndcg_at_5
-      value: 33.482
-    - type: precision_at_1
-      value: 34.259
-    - type: precision_at_10
-      value: 9.66
-    - type: precision_at_100
-      value: 1.6219999999999999
-    - type: precision_at_1000
-      value: 0.22300000000000003
-    - type: precision_at_3
-      value: 21.399
-    - type: precision_at_5
-      value: 15.741
-    - type: recall_at_1
-      value: 17.636
-    - type: recall_at_10
-      value: 41.955999999999996
-    - type: recall_at_100
-      value: 66.17
-    - type: recall_at_1000
-      value: 85.79599999999999
-    - type: recall_at_3
-      value: 29.853
-    - type: recall_at_5
-      value: 35.18
-  - task:
-      type: Retrieval
-    dataset:
-      type: hotpotqa
-      name: MTEB HotpotQA
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 39.487
-    - type: map_at_10
-      value: 56.765
-    - type: map_at_100
-      value: 57.616
-    - type: map_at_1000
-      value: 57.679
-    - type: map_at_3
-      value: 53.616
-    - type: map_at_5
-      value: 55.623999999999995
-    - type: mrr_at_1
-      value: 78.974
-    - type: mrr_at_10
-      value: 84.622
-    - type: mrr_at_100
-      value: 84.776
-    - type: mrr_at_1000
-      value: 84.783
-    - type: mrr_at_3
-      value: 83.747
-    - type: mrr_at_5
-      value: 84.27900000000001
-    - type: ndcg_at_1
-      value: 78.974
-    - type: ndcg_at_10
-      value: 66.164
-    - type: ndcg_at_100
-      value: 69.03099999999999
-    - type: ndcg_at_1000
-      value: 70.261
-    - type: ndcg_at_3
-      value: 61.712
-    - type: ndcg_at_5
-      value: 64.22
-    - type: precision_at_1
-      value: 78.974
-    - type: precision_at_10
-      value: 13.520999999999999
-    - type: precision_at_100
-      value: 1.575
-    - type: precision_at_1000
-      value: 0.174
-    - type: precision_at_3
-      value: 38.501000000000005
-    - type: precision_at_5
-      value: 25.083
-    - type: recall_at_1
-      value: 39.487
-    - type: recall_at_10
-      value: 67.60300000000001
-    - type: recall_at_100
-      value: 78.744
-    - type: recall_at_1000
-      value: 86.914
-    - type: recall_at_3
-      value: 57.752
-    - type: recall_at_5
-      value: 62.708
-  - task:
-      type: Retrieval
-    dataset:
-      type: msmarco
-      name: MTEB MSMARCO
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 24.224999999999998
-    - type: map_at_10
-      value: 37.791000000000004
-    - type: map_at_100
-      value: 38.899
-    - type: map_at_1000
-      value: 38.937
-    - type: map_at_3
-      value: 33.584
-    - type: map_at_5
-      value: 36.142
-    - type: mrr_at_1
-      value: 24.871
-    - type: mrr_at_10
-      value: 38.361000000000004
-    - type: mrr_at_100
-      value: 39.394
-    - type: mrr_at_1000
-      value: 39.427
-    - type: mrr_at_3
-      value: 34.224
-    - type: mrr_at_5
-      value: 36.767
-    - type: ndcg_at_1
-      value: 24.871
-    - type: ndcg_at_10
-      value: 45.231
-    - type: ndcg_at_100
-      value: 50.42100000000001
-    - type: ndcg_at_1000
-      value: 51.329
-    - type: ndcg_at_3
-      value: 36.77
-    - type: ndcg_at_5
-      value: 41.33
-    - type: precision_at_1
-      value: 24.871
-    - type: precision_at_10
-      value: 7.124999999999999
-    - type: precision_at_100
-      value: 0.971
-    - type: precision_at_1000
-      value: 0.105
-    - type: precision_at_3
-      value: 15.659
-    - type: precision_at_5
-      value: 11.708
-    - type: recall_at_1
-      value: 24.224999999999998
-    - type: recall_at_10
-      value: 68.081
-    - type: recall_at_100
-      value: 91.818
-    - type: recall_at_1000
-      value: 98.65
-    - type: recall_at_3
-      value: 45.355000000000004
-    - type: recall_at_5
-      value: 56.26
-  - task:
-      type: Retrieval
-    dataset:
-      type: nfcorpus
-      name: MTEB NFCorpus
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 5.904
-    - type: map_at_10
-      value: 12.784
-    - type: map_at_100
-      value: 15.628
-    - type: map_at_1000
-      value: 17.006
-    - type: map_at_3
-      value: 9.695
-    - type: map_at_5
-      value: 10.961
-    - type: mrr_at_1
-      value: 46.44
-    - type: mrr_at_10
-      value: 54.106
-    - type: mrr_at_100
-      value: 54.81700000000001
-    - type: mrr_at_1000
-      value: 54.858
-    - type: mrr_at_3
-      value: 52.837999999999994
-    - type: mrr_at_5
-      value: 53.627
-    - type: ndcg_at_1
-      value: 44.737
-    - type: ndcg_at_10
-      value: 33.967999999999996
-    - type: ndcg_at_100
-      value: 30.451
-    - type: ndcg_at_1000
-      value: 39.151
-    - type: ndcg_at_3
-      value: 39.871
-    - type: ndcg_at_5
-      value: 37.138
-    - type: precision_at_1
-      value: 46.44
-    - type: precision_at_10
-      value: 24.582
-    - type: precision_at_100
-      value: 7.715
-    - type: precision_at_1000
-      value: 2.0500000000000003
-    - type: precision_at_3
-      value: 37.461
-    - type: precision_at_5
-      value: 31.517
-    - type: recall_at_1
-      value: 5.904
-    - type: recall_at_10
-      value: 16.522000000000002
-    - type: recall_at_100
-      value: 29.413
-    - type: recall_at_1000
-      value: 61.611000000000004
-    - type: recall_at_3
-      value: 10.649000000000001
-    - type: recall_at_5
-      value: 12.642999999999999
-  - task:
-      type: Retrieval
-    dataset:
-      type: nq
-      name: MTEB NQ
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 31.561
-    - type: map_at_10
-      value: 46.406
-    - type: map_at_100
-      value: 47.499
-    - type: map_at_1000
-      value: 47.526
-    - type: map_at_3
-      value: 42.26
-    - type: map_at_5
-      value: 44.724000000000004
-    - type: mrr_at_1
-      value: 35.168
-    - type: mrr_at_10
-      value: 48.914
-    - type: mrr_at_100
-      value: 49.727
-    - type: mrr_at_1000
-      value: 49.744
-    - type: mrr_at_3
-      value: 45.418
-    - type: mrr_at_5
-      value: 47.53
-    - type: ndcg_at_1
-      value: 35.138999999999996
-    - type: ndcg_at_10
-      value: 53.943
-    - type: ndcg_at_100
-      value: 58.50300000000001
-    - type: ndcg_at_1000
-      value: 59.144
-    - type: ndcg_at_3
-      value: 46.135999999999996
-    - type: ndcg_at_5
-      value: 50.227999999999994
-    - type: precision_at_1
-      value: 35.138999999999996
-    - type: precision_at_10
-      value: 8.812000000000001
-    - type: precision_at_100
-      value: 1.138
-    - type: precision_at_1000
-      value: 0.12
-    - type: precision_at_3
-      value: 20.867
-    - type: precision_at_5
-      value: 14.878
-    - type: recall_at_1
-      value: 31.561
-    - type: recall_at_10
-      value: 74.343
-    - type: recall_at_100
-      value: 93.975
-    - type: recall_at_1000
-      value: 98.75699999999999
-    - type: recall_at_3
-      value: 54.169
-    - type: recall_at_5
-      value: 63.56
-  - task:
-      type: Retrieval
-    dataset:
-      type: quora
-      name: MTEB QuoraRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 69.753
-    - type: map_at_10
-      value: 83.56400000000001
-    - type: map_at_100
-      value: 84.19200000000001
-    - type: map_at_1000
-      value: 84.211
-    - type: map_at_3
-      value: 80.568
-    - type: map_at_5
-      value: 82.44500000000001
-    - type: mrr_at_1
-      value: 79.99000000000001
-    - type: mrr_at_10
-      value: 86.542
-    - type: mrr_at_100
-      value: 86.655
-    - type: mrr_at_1000
-      value: 86.656
-    - type: mrr_at_3
-      value: 85.505
-    - type: mrr_at_5
-      value: 86.21
-    - type: ndcg_at_1
-      value: 79.99000000000001
-    - type: ndcg_at_10
-      value: 87.449
-    - type: ndcg_at_100
-      value: 88.739
-    - type: ndcg_at_1000
-      value: 88.87
-    - type: ndcg_at_3
-      value: 84.418
-    - type: ndcg_at_5
-      value: 86.09599999999999
-    - type: precision_at_1
-      value: 79.99000000000001
-    - type: precision_at_10
-      value: 13.236999999999998
-    - type: precision_at_100
-      value: 1.516
-    - type: precision_at_1000
-      value: 0.156
-    - type: precision_at_3
-      value: 36.736999999999995
-    - type: precision_at_5
-      value: 24.227999999999998
-    - type: recall_at_1
-      value: 69.753
-    - type: recall_at_10
-      value: 94.967
-    - type: recall_at_100
-      value: 99.378
-    - type: recall_at_1000
-      value: 99.953
-    - type: recall_at_3
-      value: 86.408
-    - type: recall_at_5
-      value: 91.03
-  - task:
-      type: Retrieval
-    dataset:
-      type: scidocs
-      name: MTEB SCIDOCS
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 3.8080000000000003
-    - type: map_at_10
-      value: 9.222
-    - type: map_at_100
-      value: 10.779
-    - type: map_at_1000
-      value: 11.027000000000001
-    - type: map_at_3
-      value: 6.729
-    - type: map_at_5
-      value: 7.872999999999999
-    - type: mrr_at_1
-      value: 18.7
-    - type: mrr_at_10
-      value: 28.084999999999997
-    - type: mrr_at_100
-      value: 29.134999999999998
-    - type: mrr_at_1000
-      value: 29.214000000000002
-    - type: mrr_at_3
-      value: 24.917
-    - type: mrr_at_5
-      value: 26.651999999999997
-    - type: ndcg_at_1
-      value: 18.7
-    - type: ndcg_at_10
-      value: 15.969
-    - type: ndcg_at_100
-      value: 22.535
-    - type: ndcg_at_1000
-      value: 27.337
-    - type: ndcg_at_3
-      value: 15.112
-    - type: ndcg_at_5
-      value: 13.089
-    - type: precision_at_1
-      value: 18.7
-    - type: precision_at_10
-      value: 8.32
-    - type: precision_at_100
-      value: 1.786
-    - type: precision_at_1000
-      value: 0.293
-    - type: precision_at_3
-      value: 14.099999999999998
-    - type: precision_at_5
-      value: 11.42
-    - type: recall_at_1
-      value: 3.8080000000000003
-    - type: recall_at_10
-      value: 16.872
-    - type: recall_at_100
-      value: 36.235
-    - type: recall_at_1000
-      value: 59.587
-    - type: recall_at_3
-      value: 8.583
-    - type: recall_at_5
-      value: 11.562999999999999
-  - task:
-      type: Retrieval
-    dataset:
-      type: scifact
-      name: MTEB SciFact
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 53.994
-    - type: map_at_10
-      value: 63.56
-    - type: map_at_100
-      value: 64.247
-    - type: map_at_1000
-      value: 64.275
-    - type: map_at_3
-      value: 61.23499999999999
-    - type: map_at_5
-      value: 62.638000000000005
-    - type: mrr_at_1
-      value: 57.333
-    - type: mrr_at_10
-      value: 65.23299999999999
-    - type: mrr_at_100
-      value: 65.762
-    - type: mrr_at_1000
-      value: 65.78699999999999
-    - type: mrr_at_3
-      value: 63.556000000000004
-    - type: mrr_at_5
-      value: 64.572
-    - type: ndcg_at_1
-      value: 57.333
-    - type: ndcg_at_10
-      value: 67.88300000000001
-    - type: ndcg_at_100
-      value: 70.99
-    - type: ndcg_at_1000
-      value: 71.66
-    - type: ndcg_at_3
-      value: 64.16
-    - type: ndcg_at_5
-      value: 66.042
-    - type: precision_at_1
-      value: 57.333
-    - type: precision_at_10
-      value: 8.967
-    - type: precision_at_100
-      value: 1.06
-    - type: precision_at_1000
-      value: 0.11199999999999999
-    - type: precision_at_3
-      value: 25.222
-    - type: precision_at_5
-      value: 16.467000000000002
-    - type: recall_at_1
-      value: 53.994
-    - type: recall_at_10
-      value: 79.289
-    - type: recall_at_100
-      value: 93.533
-    - type: recall_at_1000
-      value: 98.667
-    - type: recall_at_3
-      value: 69.267
-    - type: recall_at_5
-      value: 74.128
-  - task:
-      type: Retrieval
-    dataset:
-      type: trec-covid
-      name: MTEB TRECCOVID
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.212
-    - type: map_at_10
-      value: 1.925
-    - type: map_at_100
-      value: 9.235
-    - type: map_at_1000
-      value: 22.111
-    - type: map_at_3
-      value: 0.626
-    - type: map_at_5
-      value: 1.031
-    - type: mrr_at_1
-      value: 82.0
-    - type: mrr_at_10
-      value: 90.5
-    - type: mrr_at_100
-      value: 90.5
-    - type: mrr_at_1000
-      value: 90.5
-    - type: mrr_at_3
-      value: 90.0
-    - type: mrr_at_5
-      value: 90.5
-    - type: ndcg_at_1
-      value: 75.0
-    - type: ndcg_at_10
-      value: 75.851
-    - type: ndcg_at_100
-      value: 53.190000000000005
-    - type: ndcg_at_1000
-      value: 45.507999999999996
-    - type: ndcg_at_3
-      value: 80.19500000000001
-    - type: ndcg_at_5
-      value: 78.448
-    - type: precision_at_1
-      value: 82.0
-    - type: precision_at_10
-      value: 82.6
-    - type: precision_at_100
-      value: 54.48
-    - type: precision_at_1000
-      value: 20.785999999999998
-    - type: precision_at_3
-      value: 86.667
-    - type: precision_at_5
-      value: 85.2
-    - type: recall_at_1
-      value: 0.212
-    - type: recall_at_10
-      value: 2.13
-    - type: recall_at_100
-      value: 12.152000000000001
-    - type: recall_at_1000
-      value: 42.403
-    - type: recall_at_3
-      value: 0.6689999999999999
-    - type: recall_at_5
-      value: 1.121
-  - task:
-      type: Retrieval
-    dataset:
-      type: webis-touche2020
-      name: MTEB Touche2020
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 2.701
-    - type: map_at_10
-      value: 10.488999999999999
-    - type: map_at_100
-      value: 17.258000000000003
-    - type: map_at_1000
-      value: 18.797
-    - type: map_at_3
-      value: 5.563
-    - type: map_at_5
-      value: 7.268
-    - type: mrr_at_1
-      value: 30.612000000000002
-    - type: mrr_at_10
-      value: 48.197
-    - type: mrr_at_100
-      value: 48.762
-    - type: mrr_at_1000
-      value: 48.762
-    - type: mrr_at_3
-      value: 44.218
-    - type: mrr_at_5
-      value: 46.666999999999994
-    - type: ndcg_at_1
-      value: 28.571
-    - type: ndcg_at_10
-      value: 26.512
-    - type: ndcg_at_100
-      value: 38.356
-    - type: ndcg_at_1000
-      value: 49.57
-    - type: ndcg_at_3
-      value: 27.704
-    - type: ndcg_at_5
-      value: 27.342
-    - type: precision_at_1
-      value: 30.612000000000002
-    - type: precision_at_10
-      value: 24.285999999999998
-    - type: precision_at_100
-      value: 8.0
-    - type: precision_at_1000
-      value: 1.541
-    - type: precision_at_3
-      value: 29.252
-    - type: precision_at_5
-      value: 27.346999999999998
-    - type: recall_at_1
-      value: 2.701
-    - type: recall_at_10
-      value: 17.197000000000003
-    - type: recall_at_100
-      value: 49.061
-    - type: recall_at_1000
-      value: 82.82300000000001
-    - type: recall_at_3
-      value: 6.687
-    - type: recall_at_5
-      value: 9.868
 ---
 DRAGON+ is a BERT-base sized dense retriever initialized from [RetroMAE](https://huggingface.co/Shitao/RetroMAE) and further trained on the data augmented from MS MARCO corpus, following the approach described in [How to Train Your DRAGON:
 Diverse Augmentation Towards Generalizable Dense Retrieval](https://arxiv.org/abs/2302.07452).