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1
  ---
2
  tags:
3
  - feature-extraction
 
4
  pipeline_tag: feature-extraction
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5
  ---
6
  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:
7
  Diverse Augmentation Towards Generalizable Dense Retrieval](https://arxiv.org/abs/2302.07452).
 
1
  ---
2
  tags:
3
  - feature-extraction
4
+ - mteb
5
  pipeline_tag: feature-extraction
6
+ model-index:
7
+ - name: dragon-plus
8
+ results:
9
+ - task:
10
+ type: Retrieval
11
+ dataset:
12
+ type: arguana
13
+ name: MTEB ArguAna
14
+ config: default
15
+ split: test
16
+ revision: None
17
+ metrics:
18
+ - type: map_at_1
19
+ value: 22.973
20
+ - type: map_at_10
21
+ value: 38.242
22
+ - type: map_at_100
23
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24
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25
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26
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28
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30
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47
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48
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50
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51
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52
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58
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59
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60
+ - type: precision_at_1000
61
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62
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64
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66
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68
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70
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72
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74
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75
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76
+ - type: recall_at_5
77
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78
+ - task:
79
+ type: Retrieval
80
+ dataset:
81
+ type: BeIR/cqadupstack
82
+ name: MTEB CQADupstackAndroidRetrieval
83
+ config: default
84
+ split: test
85
+ revision: None
86
+ metrics:
87
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88
+ value: 28.793000000000003
89
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95
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103
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107
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+ value: 41.321000000000005
109
+ - type: mrr_at_5
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+ - type: ndcg_at_1000
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119
+ - type: ndcg_at_3
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129
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131
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133
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135
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137
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+ - type: recall_at_100
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143
+ - type: recall_at_3
144
+ value: 41.581
145
+ - type: recall_at_5
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+ value: 47.066
147
+ - task:
148
+ type: Retrieval
149
+ dataset:
150
+ type: BeIR/cqadupstack
151
+ name: MTEB CQADupstackEnglishRetrieval
152
+ config: default
153
+ split: test
154
+ revision: None
155
+ metrics:
156
+ - type: map_at_1
157
+ value: 29.828
158
+ - type: map_at_10
159
+ value: 39.312999999999995
160
+ - type: map_at_100
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+ value: 40.607
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+ value: 42.856
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+ - type: mrr_at_5
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ value: 0.179
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+ - type: precision_at_3
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+ value: 19.533
202
+ - type: precision_at_5
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+ value: 13.732
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+ - type: recall_at_1
205
+ value: 29.828
206
+ - type: recall_at_10
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+ value: 54.339000000000006
208
+ - type: recall_at_100
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+ value: 72.217
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+ - type: recall_at_1000
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+ - type: recall_at_3
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+ value: 42.331
214
+ - type: recall_at_5
215
+ value: 47.612
216
+ - task:
217
+ type: Retrieval
218
+ dataset:
219
+ type: BeIR/cqadupstack
220
+ name: MTEB CQADupstackGamingRetrieval
221
+ config: default
222
+ split: test
223
+ revision: None
224
+ metrics:
225
+ - type: map_at_1
226
+ value: 37.919000000000004
227
+ - type: map_at_10
228
+ value: 49.225
229
+ - type: map_at_100
230
+ value: 50.306
231
+ - type: map_at_1000
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+ value: 50.364
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+ - type: map_at_3
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+ value: 46.459
235
+ - type: map_at_5
236
+ value: 48.173
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+ - type: mrr_at_1
238
+ value: 43.072
239
+ - type: mrr_at_10
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+ value: 52.437
241
+ - type: mrr_at_100
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+ value: 53.2
243
+ - type: mrr_at_1000
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+ value: 53.233
245
+ - type: mrr_at_3
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+ value: 50.219
247
+ - type: mrr_at_5
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+ value: 51.629999999999995
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+ - type: ndcg_at_1
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275
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282
+ value: 54.515
283
+ - type: recall_at_5
284
+ value: 60.684000000000005
285
+ - task:
286
+ type: Retrieval
287
+ dataset:
288
+ type: BeIR/cqadupstack
289
+ name: MTEB CQADupstackGisRetrieval
290
+ config: default
291
+ split: test
292
+ revision: None
293
+ metrics:
294
+ - type: map_at_1
295
+ value: 21.04
296
+ - type: map_at_10
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+ value: 27.665
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+ - type: map_at_100
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300
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+ - type: map_at_5
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+ - task:
355
+ type: Retrieval
356
+ dataset:
357
+ type: BeIR/cqadupstack
358
+ name: MTEB CQADupstackMathematicaRetrieval
359
+ config: default
360
+ split: test
361
+ revision: None
362
+ metrics:
363
+ - type: map_at_1
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422
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+ - task:
424
+ type: Retrieval
425
+ dataset:
426
+ type: BeIR/cqadupstack
427
+ name: MTEB CQADupstackPhysicsRetrieval
428
+ config: default
429
+ split: test
430
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431
+ metrics:
432
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433
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+ value: 65.762
1692
+ - type: mrr_at_1000
1693
+ value: 65.78699999999999
1694
+ - type: mrr_at_3
1695
+ value: 63.556000000000004
1696
+ - type: mrr_at_5
1697
+ value: 64.572
1698
+ - type: ndcg_at_1
1699
+ value: 57.333
1700
+ - type: ndcg_at_10
1701
+ value: 67.88300000000001
1702
+ - type: ndcg_at_100
1703
+ value: 70.99
1704
+ - type: ndcg_at_1000
1705
+ value: 71.66
1706
+ - type: ndcg_at_3
1707
+ value: 64.16
1708
+ - type: ndcg_at_5
1709
+ value: 66.042
1710
+ - type: precision_at_1
1711
+ value: 57.333
1712
+ - type: precision_at_10
1713
+ value: 8.967
1714
+ - type: precision_at_100
1715
+ value: 1.06
1716
+ - type: precision_at_1000
1717
+ value: 0.11199999999999999
1718
+ - type: precision_at_3
1719
+ value: 25.222
1720
+ - type: precision_at_5
1721
+ value: 16.467000000000002
1722
+ - type: recall_at_1
1723
+ value: 53.994
1724
+ - type: recall_at_10
1725
+ value: 79.289
1726
+ - type: recall_at_100
1727
+ value: 93.533
1728
+ - type: recall_at_1000
1729
+ value: 98.667
1730
+ - type: recall_at_3
1731
+ value: 69.267
1732
+ - type: recall_at_5
1733
+ value: 74.128
1734
+ - task:
1735
+ type: Retrieval
1736
+ dataset:
1737
+ type: trec-covid
1738
+ name: MTEB TRECCOVID
1739
+ config: default
1740
+ split: test
1741
+ revision: None
1742
+ metrics:
1743
+ - type: map_at_1
1744
+ value: 0.212
1745
+ - type: map_at_10
1746
+ value: 1.925
1747
+ - type: map_at_100
1748
+ value: 9.235
1749
+ - type: map_at_1000
1750
+ value: 22.111
1751
+ - type: map_at_3
1752
+ value: 0.626
1753
+ - type: map_at_5
1754
+ value: 1.031
1755
+ - type: mrr_at_1
1756
+ value: 82.0
1757
+ - type: mrr_at_10
1758
+ value: 90.5
1759
+ - type: mrr_at_100
1760
+ value: 90.5
1761
+ - type: mrr_at_1000
1762
+ value: 90.5
1763
+ - type: mrr_at_3
1764
+ value: 90.0
1765
+ - type: mrr_at_5
1766
+ value: 90.5
1767
+ - type: ndcg_at_1
1768
+ value: 75.0
1769
+ - type: ndcg_at_10
1770
+ value: 75.851
1771
+ - type: ndcg_at_100
1772
+ value: 53.190000000000005
1773
+ - type: ndcg_at_1000
1774
+ value: 45.507999999999996
1775
+ - type: ndcg_at_3
1776
+ value: 80.19500000000001
1777
+ - type: ndcg_at_5
1778
+ value: 78.448
1779
+ - type: precision_at_1
1780
+ value: 82.0
1781
+ - type: precision_at_10
1782
+ value: 82.6
1783
+ - type: precision_at_100
1784
+ value: 54.48
1785
+ - type: precision_at_1000
1786
+ value: 20.785999999999998
1787
+ - type: precision_at_3
1788
+ value: 86.667
1789
+ - type: precision_at_5
1790
+ value: 85.2
1791
+ - type: recall_at_1
1792
+ value: 0.212
1793
+ - type: recall_at_10
1794
+ value: 2.13
1795
+ - type: recall_at_100
1796
+ value: 12.152000000000001
1797
+ - type: recall_at_1000
1798
+ value: 42.403
1799
+ - type: recall_at_3
1800
+ value: 0.6689999999999999
1801
+ - type: recall_at_5
1802
+ value: 1.121
1803
+ - task:
1804
+ type: Retrieval
1805
+ dataset:
1806
+ type: webis-touche2020
1807
+ name: MTEB Touche2020
1808
+ config: default
1809
+ split: test
1810
+ revision: None
1811
+ metrics:
1812
+ - type: map_at_1
1813
+ value: 2.701
1814
+ - type: map_at_10
1815
+ value: 10.488999999999999
1816
+ - type: map_at_100
1817
+ value: 17.258000000000003
1818
+ - type: map_at_1000
1819
+ value: 18.797
1820
+ - type: map_at_3
1821
+ value: 5.563
1822
+ - type: map_at_5
1823
+ value: 7.268
1824
+ - type: mrr_at_1
1825
+ value: 30.612000000000002
1826
+ - type: mrr_at_10
1827
+ value: 48.197
1828
+ - type: mrr_at_100
1829
+ value: 48.762
1830
+ - type: mrr_at_1000
1831
+ value: 48.762
1832
+ - type: mrr_at_3
1833
+ value: 44.218
1834
+ - type: mrr_at_5
1835
+ value: 46.666999999999994
1836
+ - type: ndcg_at_1
1837
+ value: 28.571
1838
+ - type: ndcg_at_10
1839
+ value: 26.512
1840
+ - type: ndcg_at_100
1841
+ value: 38.356
1842
+ - type: ndcg_at_1000
1843
+ value: 49.57
1844
+ - type: ndcg_at_3
1845
+ value: 27.704
1846
+ - type: ndcg_at_5
1847
+ value: 27.342
1848
+ - type: precision_at_1
1849
+ value: 30.612000000000002
1850
+ - type: precision_at_10
1851
+ value: 24.285999999999998
1852
+ - type: precision_at_100
1853
+ value: 8.0
1854
+ - type: precision_at_1000
1855
+ value: 1.541
1856
+ - type: precision_at_3
1857
+ value: 29.252
1858
+ - type: precision_at_5
1859
+ value: 27.346999999999998
1860
+ - type: recall_at_1
1861
+ value: 2.701
1862
+ - type: recall_at_10
1863
+ value: 17.197000000000003
1864
+ - type: recall_at_100
1865
+ value: 49.061
1866
+ - type: recall_at_1000
1867
+ value: 82.82300000000001
1868
+ - type: recall_at_3
1869
+ value: 6.687
1870
+ - type: recall_at_5
1871
+ value: 9.868
1872
  ---
1873
  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:
1874
  Diverse Augmentation Towards Generalizable Dense Retrieval](https://arxiv.org/abs/2302.07452).