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@@ -14,11 +14,11 @@ model-index:
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  revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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  metrics:
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  - type: accuracy
17
- value: 77.56716417910448
18
  - type: ap
19
- value: 40.91549063721234
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  - type: f1
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- value: 71.51708294746035
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  - task:
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  type: Classification
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  dataset:
@@ -29,11 +29,11 @@ model-index:
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  revision: e2d317d38cd51312af73b3d32a06d1a08b442046
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  metrics:
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  - type: accuracy
32
- value: 89.50825
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  - type: ap
34
- value: 86.00556056390054
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  - type: f1
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- value: 89.48068855084334
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  - task:
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  type: Classification
39
  dataset:
@@ -44,9 +44,9 @@ model-index:
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  revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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  metrics:
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  - type: accuracy
47
- value: 46.82399999999999
48
  - type: f1
49
- value: 46.272112748273315
50
  - task:
51
  type: Retrieval
52
  dataset:
@@ -57,65 +57,65 @@ model-index:
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  revision: None
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  metrics:
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  - type: map_at_1
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- value: 28.592000000000002
61
  - type: map_at_10
62
- value: 44.37
63
  - type: map_at_100
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- value: 45.355000000000004
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  - type: map_at_1000
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- value: 45.363
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  - type: map_at_3
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- value: 39.272
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  - type: map_at_5
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- value: 42.405
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  - type: mrr_at_1
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- value: 29.445
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  - type: mrr_at_10
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- value: 44.668
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  - type: mrr_at_100
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- value: 45.646
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  - type: mrr_at_1000
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- value: 45.655
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  - type: mrr_at_3
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- value: 39.545
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  - type: mrr_at_5
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- value: 42.674
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  - type: ndcg_at_1
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- value: 28.592000000000002
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  - type: ndcg_at_10
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- value: 53.230999999999995
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  - type: ndcg_at_100
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- value: 57.188
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  - type: ndcg_at_1000
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- value: 57.371
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  - type: ndcg_at_3
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- value: 42.842
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  - type: ndcg_at_5
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- value: 48.538
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  - type: precision_at_1
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- value: 28.592000000000002
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  - type: precision_at_10
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- value: 8.151
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  - type: precision_at_100
100
- value: 0.9820000000000001
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  - type: precision_at_1000
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  value: 0.1
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  - type: precision_at_3
104
- value: 17.733999999999998
105
  - type: precision_at_5
106
- value: 13.428
107
  - type: recall_at_1
108
- value: 28.592000000000002
109
  - type: recall_at_10
110
- value: 81.50800000000001
111
  - type: recall_at_100
112
- value: 98.222
113
  - type: recall_at_1000
114
  value: 99.57300000000001
115
  - type: recall_at_3
116
- value: 53.201
117
  - type: recall_at_5
118
- value: 67.14099999999999
119
  - task:
120
  type: Clustering
121
  dataset:
@@ -126,7 +126,7 @@ model-index:
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  revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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  metrics:
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  - type: v_measure
129
- value: 45.83975081280601
130
  - task:
131
  type: Clustering
132
  dataset:
@@ -137,7 +137,7 @@ model-index:
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  revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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  metrics:
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  - type: v_measure
140
- value: 36.20880276672235
141
  - task:
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  type: Reranking
143
  dataset:
@@ -148,9 +148,9 @@ model-index:
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  revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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  metrics:
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  - type: map
151
- value: 60.88591268158169
152
  - type: mrr
153
- value: 75.19709361122104
154
  - task:
155
  type: STS
156
  dataset:
@@ -161,17 +161,17 @@ model-index:
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  revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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  metrics:
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  - type: cos_sim_pearson
164
- value: 89.65453333525659
165
  - type: cos_sim_spearman
166
- value: 86.84535232424253
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  - type: euclidean_pearson
168
- value: 88.44638498736246
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  - type: euclidean_spearman
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- value: 86.84535232424253
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  - type: manhattan_pearson
172
- value: 88.73402151565195
173
  - type: manhattan_spearman
174
- value: 87.24415659199119
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  - task:
176
  type: Classification
177
  dataset:
@@ -182,9 +182,9 @@ model-index:
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  revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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  metrics:
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  - type: accuracy
185
- value: 84.7564935064935
186
  - type: f1
187
- value: 84.70138093263196
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  - task:
189
  type: Clustering
190
  dataset:
@@ -195,7 +195,7 @@ model-index:
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  revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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  metrics:
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  - type: v_measure
198
- value: 38.272839537742655
199
  - task:
200
  type: Clustering
201
  dataset:
@@ -206,7 +206,7 @@ model-index:
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  revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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  metrics:
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  - type: v_measure
209
- value: 33.03251777955244
210
  - task:
211
  type: Retrieval
212
  dataset:
@@ -217,65 +217,65 @@ model-index:
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  revision: None
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  metrics:
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  - type: map_at_1
220
- value: 30.319000000000003
221
  - type: map_at_10
222
- value: 40.161
223
  - type: map_at_100
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- value: 41.557
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  - type: map_at_1000
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- value: 41.678
227
  - type: map_at_3
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- value: 37.008
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  - type: map_at_5
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- value: 38.592
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  - type: mrr_at_1
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- value: 37.053000000000004
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  - type: mrr_at_10
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- value: 45.597
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  - type: mrr_at_100
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- value: 46.443
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  - type: mrr_at_1000
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- value: 46.489000000000004
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  - type: mrr_at_3
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- value: 43.085
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  - type: mrr_at_5
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- value: 44.43
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  - type: ndcg_at_1
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- value: 37.053000000000004
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  - type: ndcg_at_10
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- value: 45.948
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  - type: ndcg_at_100
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- value: 51.44800000000001
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  - type: ndcg_at_1000
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- value: 53.54
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  - type: ndcg_at_3
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- value: 41.316
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  - type: ndcg_at_5
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- value: 43.15
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  - type: precision_at_1
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- value: 37.053000000000004
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  - type: precision_at_10
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- value: 8.569
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  - type: precision_at_100
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- value: 1.425
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  - type: precision_at_1000
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- value: 0.189
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  - type: precision_at_3
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- value: 19.695
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  - type: precision_at_5
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- value: 13.763
267
  - type: recall_at_1
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- value: 30.319000000000003
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  - type: recall_at_10
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- value: 57.233000000000004
271
  - type: recall_at_100
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- value: 80.441
273
  - type: recall_at_1000
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- value: 94.041
275
  - type: recall_at_3
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- value: 43.028
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  - type: recall_at_5
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- value: 48.806
279
  - task:
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  type: Retrieval
281
  dataset:
@@ -286,65 +286,65 @@ model-index:
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  revision: None
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  metrics:
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  - type: map_at_1
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- value: 31.022
290
  - type: map_at_10
291
- value: 41.305
292
  - type: map_at_100
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- value: 42.576
294
  - type: map_at_1000
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- value: 42.707
296
  - type: map_at_3
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- value: 38.271
298
  - type: map_at_5
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- value: 40.048
300
  - type: mrr_at_1
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- value: 39.427
302
  - type: mrr_at_10
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- value: 47.707
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  - type: mrr_at_100
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- value: 48.394
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  - type: mrr_at_1000
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- value: 48.439
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  - type: mrr_at_3
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- value: 45.552
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  - type: mrr_at_5
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- value: 46.823
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  - type: ndcg_at_1
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- value: 39.427
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  - type: ndcg_at_10
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- value: 47.121
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  - type: ndcg_at_100
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- value: 51.458999999999996
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  - type: ndcg_at_1000
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- value: 53.461000000000006
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  - type: ndcg_at_3
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- value: 43.001
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  - type: ndcg_at_5
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- value: 45.025
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  - type: precision_at_1
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- value: 39.427
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  - type: precision_at_10
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- value: 8.994
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  - type: precision_at_100
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- value: 1.456
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  - type: precision_at_1000
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- value: 0.192
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  - type: precision_at_3
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- value: 20.913
334
  - type: precision_at_5
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- value: 14.917
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  - type: recall_at_1
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- value: 31.022
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  - type: recall_at_10
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- value: 56.769999999999996
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  - type: recall_at_100
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- value: 75.154
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  - type: recall_at_1000
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- value: 87.832
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  - type: recall_at_3
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- value: 44.295
346
  - type: recall_at_5
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- value: 50.041000000000004
348
  - task:
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  type: Retrieval
350
  dataset:
@@ -355,65 +355,65 @@ model-index:
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  revision: None
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  metrics:
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  - type: map_at_1
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- value: 41.021
359
  - type: map_at_10
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- value: 52.931
361
  - type: map_at_100
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- value: 53.846000000000004
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  - type: map_at_1000
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- value: 53.905
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  - type: map_at_3
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- value: 49.952000000000005
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  - type: map_at_5
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- value: 51.566
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  - type: mrr_at_1
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  value: 46.708
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  - type: mrr_at_10
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- value: 56.467999999999996
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  - type: mrr_at_100
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- value: 57.06400000000001
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  - type: mrr_at_1000
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- value: 57.096999999999994
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  - type: mrr_at_3
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- value: 54.295
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  - type: mrr_at_5
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- value: 55.52
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  - type: ndcg_at_1
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  value: 46.708
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  - type: ndcg_at_10
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- value: 58.458
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  - type: ndcg_at_100
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- value: 62.21
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  - type: ndcg_at_1000
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- value: 63.438
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  - type: ndcg_at_3
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- value: 53.493
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  - type: ndcg_at_5
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- value: 55.824
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  - type: precision_at_1
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  value: 46.708
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  - type: precision_at_10
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- value: 9.166
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  - type: precision_at_100
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- value: 1.199
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  - type: precision_at_1000
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- value: 0.135
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  - type: precision_at_3
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- value: 23.532
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  - type: precision_at_5
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- value: 15.862000000000002
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  - type: recall_at_1
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- value: 41.021
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  - type: recall_at_10
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- value: 71.25
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  - type: recall_at_100
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- value: 87.507
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  - type: recall_at_1000
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- value: 96.206
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  - type: recall_at_3
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- value: 58.089
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  - type: recall_at_5
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- value: 63.82
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  - task:
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  type: Retrieval
419
  dataset:
@@ -424,65 +424,65 @@ model-index:
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  revision: None
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  metrics:
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  - type: map_at_1
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- value: 26.413999999999998
428
  - type: map_at_10
429
- value: 34.404
430
  - type: map_at_100
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- value: 35.359
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  - type: map_at_1000
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- value: 35.435
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  - type: map_at_3
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- value: 32.017
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  - type: map_at_5
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- value: 33.243
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  - type: mrr_at_1
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- value: 28.362
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  - type: mrr_at_10
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- value: 36.393
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  - type: mrr_at_100
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- value: 37.211
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  - type: mrr_at_1000
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- value: 37.273
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  - type: mrr_at_3
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- value: 33.992
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  - type: mrr_at_5
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- value: 35.309000000000005
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  - type: ndcg_at_1
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- value: 28.362
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  - type: ndcg_at_10
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- value: 38.964
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  - type: ndcg_at_100
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- value: 43.791000000000004
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  - type: ndcg_at_1000
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- value: 45.89
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  - type: ndcg_at_3
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- value: 34.201
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  - type: ndcg_at_5
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- value: 36.334
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  - type: precision_at_1
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- value: 28.362
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  - type: precision_at_10
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- value: 5.842
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  - type: precision_at_100
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- value: 0.868
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  - type: precision_at_1000
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- value: 0.109
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  - type: precision_at_3
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- value: 14.049
472
  - type: precision_at_5
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- value: 9.695
474
  - type: recall_at_1
475
- value: 26.413999999999998
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  - type: recall_at_10
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- value: 51.017999999999994
478
  - type: recall_at_100
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- value: 73.551
480
  - type: recall_at_1000
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- value: 89.51
482
  - type: recall_at_3
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- value: 38.385000000000005
484
  - type: recall_at_5
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- value: 43.351
486
  - task:
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  type: Retrieval
488
  dataset:
@@ -493,65 +493,65 @@ model-index:
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  revision: None
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  metrics:
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  - type: map_at_1
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- value: 17.721999999999998
497
  - type: map_at_10
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- value: 24.55
499
  - type: map_at_100
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- value: 25.586
501
  - type: map_at_1000
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- value: 25.715
503
  - type: map_at_3
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- value: 22.445
505
  - type: map_at_5
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- value: 23.497
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  - type: mrr_at_1
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- value: 21.642
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  - type: mrr_at_10
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- value: 28.979
511
  - type: mrr_at_100
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- value: 29.898000000000003
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  - type: mrr_at_1000
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- value: 29.981
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  - type: mrr_at_3
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- value: 26.886
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  - type: mrr_at_5
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- value: 28.055999999999997
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  - type: ndcg_at_1
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- value: 21.642
521
  - type: ndcg_at_10
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- value: 29.158
523
  - type: ndcg_at_100
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- value: 34.352
525
  - type: ndcg_at_1000
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- value: 37.456
527
  - type: ndcg_at_3
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- value: 25.302000000000003
529
  - type: ndcg_at_5
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- value: 26.916
531
  - type: precision_at_1
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- value: 21.642
533
  - type: precision_at_10
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- value: 5.274
535
  - type: precision_at_100
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- value: 0.907
537
  - type: precision_at_1000
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- value: 0.131
539
  - type: precision_at_3
540
- value: 12.148
541
  - type: precision_at_5
542
- value: 8.458
543
  - type: recall_at_1
544
- value: 17.721999999999998
545
  - type: recall_at_10
546
- value: 38.926
547
  - type: recall_at_100
548
- value: 61.698
549
  - type: recall_at_1000
550
- value: 83.742
551
  - type: recall_at_3
552
- value: 28.209
553
  - type: recall_at_5
554
- value: 32.462999999999994
555
  - task:
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  type: Retrieval
557
  dataset:
@@ -562,65 +562,65 @@ model-index:
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  revision: None
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  metrics:
564
  - type: map_at_1
565
- value: 28.429
566
  - type: map_at_10
567
- value: 38.0
568
  - type: map_at_100
569
- value: 39.262
570
  - type: map_at_1000
571
- value: 39.371
572
  - type: map_at_3
573
- value: 35.031
574
  - type: map_at_5
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- value: 36.935
576
  - type: mrr_at_1
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  value: 33.782000000000004
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  - type: mrr_at_10
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- value: 43.164
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  - type: mrr_at_100
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- value: 43.962
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  - type: mrr_at_1000
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- value: 44.012
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  - type: mrr_at_3
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- value: 40.711999999999996
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  - type: mrr_at_5
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- value: 42.32
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  - type: ndcg_at_1
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  value: 33.782000000000004
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  - type: ndcg_at_10
591
- value: 43.574
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  - type: ndcg_at_100
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- value: 48.903999999999996
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  - type: ndcg_at_1000
595
- value: 51.074
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  - type: ndcg_at_3
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- value: 38.858
598
  - type: ndcg_at_5
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- value: 41.581
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  - type: precision_at_1
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  value: 33.782000000000004
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  - type: precision_at_10
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- value: 7.7
604
  - type: precision_at_100
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- value: 1.217
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  - type: precision_at_1000
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- value: 0.157
608
  - type: precision_at_3
609
- value: 18.157999999999998
610
  - type: precision_at_5
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- value: 13.128
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  - type: recall_at_1
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- value: 28.429
614
  - type: recall_at_10
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- value: 54.63
616
  - type: recall_at_100
617
- value: 77.183
618
  - type: recall_at_1000
619
- value: 91.708
620
  - type: recall_at_3
621
- value: 41.81
622
  - type: recall_at_5
623
- value: 48.794
624
  - task:
625
  type: Retrieval
626
  dataset:
@@ -631,65 +631,65 @@ model-index:
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  revision: None
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  metrics:
633
  - type: map_at_1
634
- value: 25.579
635
  - type: map_at_10
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- value: 35.135
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  - type: map_at_100
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- value: 36.382999999999996
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  - type: map_at_1000
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- value: 36.482
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  - type: map_at_3
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- value: 32.25
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  - type: map_at_5
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- value: 33.873999999999995
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  - type: mrr_at_1
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- value: 31.279
647
  - type: mrr_at_10
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- value: 40.261
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  - type: mrr_at_100
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- value: 41.128
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  - type: mrr_at_1000
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- value: 41.175
653
  - type: mrr_at_3
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- value: 37.823
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  - type: mrr_at_5
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- value: 39.245000000000005
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  - type: ndcg_at_1
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- value: 31.279
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  - type: ndcg_at_10
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- value: 40.64
661
  - type: ndcg_at_100
662
- value: 46.224
663
  - type: ndcg_at_1000
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- value: 48.392
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  - type: ndcg_at_3
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- value: 35.913000000000004
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  - type: ndcg_at_5
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- value: 38.086999999999996
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  - type: precision_at_1
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- value: 31.279
671
  - type: precision_at_10
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- value: 7.306
673
  - type: precision_at_100
674
- value: 1.185
675
  - type: precision_at_1000
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- value: 0.154
677
  - type: precision_at_3
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- value: 17.009
679
  - type: precision_at_5
680
- value: 12.123000000000001
681
  - type: recall_at_1
682
- value: 25.579
683
  - type: recall_at_10
684
- value: 52.018
685
  - type: recall_at_100
686
- value: 76.02799999999999
687
  - type: recall_at_1000
688
- value: 90.996
689
  - type: recall_at_3
690
- value: 38.769
691
  - type: recall_at_5
692
- value: 44.417
693
  - task:
694
  type: Retrieval
695
  dataset:
@@ -700,65 +700,65 @@ model-index:
700
  revision: None
701
  metrics:
702
  - type: map_at_1
703
- value: 26.15416666666666
704
  - type: map_at_10
705
- value: 34.64533333333333
706
  - type: map_at_100
707
- value: 35.7715
708
  - type: map_at_1000
709
- value: 35.885333333333335
710
  - type: map_at_3
711
- value: 32.03941666666667
712
  - type: map_at_5
713
- value: 33.47041666666667
714
  - type: mrr_at_1
715
- value: 30.654583333333328
716
  - type: mrr_at_10
717
- value: 38.71783333333333
718
  - type: mrr_at_100
719
- value: 39.52499999999999
720
  - type: mrr_at_1000
721
- value: 39.584250000000004
722
  - type: mrr_at_3
723
- value: 36.42975
724
  - type: mrr_at_5
725
- value: 37.72874999999999
726
  - type: ndcg_at_1
727
- value: 30.654583333333328
728
  - type: ndcg_at_10
729
- value: 39.663583333333335
730
  - type: ndcg_at_100
731
- value: 44.600249999999996
732
  - type: ndcg_at_1000
733
- value: 46.93808333333333
734
  - type: ndcg_at_3
735
- value: 35.2025
736
  - type: ndcg_at_5
737
- value: 37.27008333333333
738
  - type: precision_at_1
739
- value: 30.654583333333328
740
  - type: precision_at_10
741
- value: 6.8140833333333335
742
  - type: precision_at_100
743
- value: 1.1011666666666666
744
  - type: precision_at_1000
745
- value: 0.14883333333333335
746
  - type: precision_at_3
747
- value: 15.982249999999997
748
  - type: precision_at_5
749
- value: 11.254916666666666
750
  - type: recall_at_1
751
- value: 26.15416666666666
752
  - type: recall_at_10
753
- value: 50.44783333333333
754
  - type: recall_at_100
755
- value: 72.172
756
  - type: recall_at_1000
757
- value: 88.49900000000001
758
  - type: recall_at_3
759
- value: 38.030750000000005
760
  - type: recall_at_5
761
- value: 43.37716666666667
762
  - task:
763
  type: Retrieval
764
  dataset:
@@ -769,65 +769,65 @@ model-index:
769
  revision: None
770
  metrics:
771
  - type: map_at_1
772
- value: 24.936
773
  - type: map_at_10
774
- value: 31.274
775
  - type: map_at_100
776
- value: 32.127
777
  - type: map_at_1000
778
- value: 32.218999999999994
779
  - type: map_at_3
780
- value: 29.036
781
  - type: map_at_5
782
- value: 30.128
783
  - type: mrr_at_1
784
- value: 27.454
785
  - type: mrr_at_10
786
- value: 33.973
787
  - type: mrr_at_100
788
- value: 34.75
789
  - type: mrr_at_1000
790
- value: 34.821999999999996
791
  - type: mrr_at_3
792
- value: 31.979000000000003
793
  - type: mrr_at_5
794
- value: 32.975
795
  - type: ndcg_at_1
796
- value: 27.454
797
  - type: ndcg_at_10
798
- value: 35.259
799
  - type: ndcg_at_100
800
- value: 39.513
801
  - type: ndcg_at_1000
802
- value: 41.913
803
  - type: ndcg_at_3
804
- value: 31.184
805
  - type: ndcg_at_5
806
- value: 32.804
807
  - type: precision_at_1
808
- value: 27.454
809
  - type: precision_at_10
810
- value: 5.445
811
  - type: precision_at_100
812
- value: 0.8250000000000001
813
  - type: precision_at_1000
814
- value: 0.109
815
  - type: precision_at_3
816
- value: 12.986
817
  - type: precision_at_5
818
- value: 8.895999999999999
819
  - type: recall_at_1
820
- value: 24.936
821
  - type: recall_at_10
822
- value: 44.807
823
  - type: recall_at_100
824
- value: 64.046
825
  - type: recall_at_1000
826
- value: 81.959
827
  - type: recall_at_3
828
- value: 33.587
829
  - type: recall_at_5
830
- value: 37.665
831
  - task:
832
  type: Retrieval
833
  dataset:
@@ -838,65 +838,65 @@ model-index:
838
  revision: None
839
  metrics:
840
  - type: map_at_1
841
- value: 16.641000000000002
842
  - type: map_at_10
843
- value: 23.794
844
  - type: map_at_100
845
- value: 24.769
846
  - type: map_at_1000
847
- value: 24.898999999999997
848
  - type: map_at_3
849
- value: 21.67
850
  - type: map_at_5
851
- value: 22.933
852
  - type: mrr_at_1
853
- value: 20.061999999999998
854
  - type: mrr_at_10
855
- value: 27.467999999999996
856
  - type: mrr_at_100
857
- value: 28.303
858
  - type: mrr_at_1000
859
- value: 28.387
860
  - type: mrr_at_3
861
- value: 25.361
862
  - type: mrr_at_5
863
- value: 26.676
864
  - type: ndcg_at_1
865
- value: 20.061999999999998
866
  - type: ndcg_at_10
867
- value: 28.218
868
  - type: ndcg_at_100
869
- value: 32.988
870
  - type: ndcg_at_1000
871
- value: 36.083
872
  - type: ndcg_at_3
873
- value: 24.391
874
  - type: ndcg_at_5
875
- value: 26.349
876
  - type: precision_at_1
877
- value: 20.061999999999998
878
  - type: precision_at_10
879
- value: 4.997
880
  - type: precision_at_100
881
- value: 0.8670000000000001
882
  - type: precision_at_1000
883
- value: 0.131
884
  - type: precision_at_3
885
- value: 11.402
886
  - type: precision_at_5
887
- value: 8.273
888
  - type: recall_at_1
889
- value: 16.641000000000002
890
  - type: recall_at_10
891
- value: 37.925
892
  - type: recall_at_100
893
- value: 59.317
894
  - type: recall_at_1000
895
- value: 81.49499999999999
896
  - type: recall_at_3
897
- value: 27.381
898
  - type: recall_at_5
899
- value: 32.323
900
  - task:
901
  type: Retrieval
902
  dataset:
@@ -907,65 +907,65 @@ model-index:
907
  revision: None
908
  metrics:
909
  - type: map_at_1
910
- value: 25.684
911
  - type: map_at_10
912
- value: 33.499
913
  - type: map_at_100
914
- value: 34.533
915
  - type: map_at_1000
916
- value: 34.647
917
  - type: map_at_3
918
- value: 30.908
919
  - type: map_at_5
920
- value: 32.376
921
  - type: mrr_at_1
922
- value: 29.757
923
  - type: mrr_at_10
924
- value: 37.439
925
  - type: mrr_at_100
926
- value: 38.239000000000004
927
  - type: mrr_at_1000
928
- value: 38.307
929
  - type: mrr_at_3
930
- value: 34.997
931
  - type: mrr_at_5
932
- value: 36.359
933
  - type: ndcg_at_1
934
- value: 29.757
935
  - type: ndcg_at_10
936
- value: 38.334
937
  - type: ndcg_at_100
938
- value: 43.171
939
  - type: ndcg_at_1000
940
- value: 45.775
941
  - type: ndcg_at_3
942
- value: 33.611999999999995
943
  - type: ndcg_at_5
944
- value: 35.884
945
  - type: precision_at_1
946
- value: 29.757
947
  - type: precision_at_10
948
- value: 6.361999999999999
949
  - type: precision_at_100
950
- value: 0.98
951
  - type: precision_at_1000
952
- value: 0.133
953
  - type: precision_at_3
954
- value: 14.988000000000001
955
  - type: precision_at_5
956
- value: 10.653
957
  - type: recall_at_1
958
- value: 25.684
959
  - type: recall_at_10
960
- value: 49.059000000000005
961
  - type: recall_at_100
962
- value: 70.339
963
  - type: recall_at_1000
964
- value: 88.567
965
  - type: recall_at_3
966
- value: 36.233
967
  - type: recall_at_5
968
- value: 41.974000000000004
969
  - task:
970
  type: Retrieval
971
  dataset:
@@ -976,65 +976,65 @@ model-index:
976
  revision: None
977
  metrics:
978
  - type: map_at_1
979
- value: 24.265
980
  - type: map_at_10
981
- value: 31.948
982
  - type: map_at_100
983
- value: 33.558
984
  - type: map_at_1000
985
- value: 33.778999999999996
986
  - type: map_at_3
987
- value: 29.387999999999998
988
  - type: map_at_5
989
- value: 30.711
990
  - type: mrr_at_1
991
- value: 28.854000000000003
992
  - type: mrr_at_10
993
- value: 36.346000000000004
994
  - type: mrr_at_100
995
- value: 37.273
996
  - type: mrr_at_1000
997
- value: 37.336000000000006
998
  - type: mrr_at_3
999
- value: 33.794000000000004
1000
  - type: mrr_at_5
1001
- value: 35.168
1002
  - type: ndcg_at_1
1003
- value: 28.854000000000003
1004
  - type: ndcg_at_10
1005
- value: 37.281
1006
  - type: ndcg_at_100
1007
- value: 43.125
1008
  - type: ndcg_at_1000
1009
- value: 45.9
1010
  - type: ndcg_at_3
1011
- value: 32.637
1012
  - type: ndcg_at_5
1013
- value: 34.628
1014
  - type: precision_at_1
1015
- value: 28.854000000000003
1016
  - type: precision_at_10
1017
- value: 6.957000000000001
1018
  - type: precision_at_100
1019
- value: 1.455
1020
  - type: precision_at_1000
1021
  value: 0.231
1022
  - type: precision_at_3
1023
- value: 14.954
1024
  - type: precision_at_5
1025
- value: 10.751
1026
  - type: recall_at_1
1027
- value: 24.265
1028
  - type: recall_at_10
1029
- value: 47.709
1030
  - type: recall_at_100
1031
- value: 72.894
1032
  - type: recall_at_1000
1033
- value: 90.545
1034
  - type: recall_at_3
1035
- value: 34.618
1036
  - type: recall_at_5
1037
- value: 39.793
1038
  - task:
1039
  type: Retrieval
1040
  dataset:
@@ -1045,65 +1045,65 @@ model-index:
1045
  revision: None
1046
  metrics:
1047
  - type: map_at_1
1048
- value: 21.818
1049
  - type: map_at_10
1050
- value: 28.743000000000002
1051
  - type: map_at_100
1052
- value: 29.702
1053
  - type: map_at_1000
1054
- value: 29.787000000000003
1055
  - type: map_at_3
1056
- value: 26.497
1057
  - type: map_at_5
1058
- value: 27.742
1059
  - type: mrr_at_1
1060
- value: 23.474999999999998
1061
  - type: mrr_at_10
1062
- value: 30.819000000000003
1063
  - type: mrr_at_100
1064
- value: 31.635
1065
  - type: mrr_at_1000
1066
- value: 31.692999999999998
1067
  - type: mrr_at_3
1068
- value: 28.681
1069
  - type: mrr_at_5
1070
- value: 29.864
1071
  - type: ndcg_at_1
1072
- value: 23.474999999999998
1073
  - type: ndcg_at_10
1074
- value: 33.007999999999996
1075
  - type: ndcg_at_100
1076
- value: 38.018
1077
  - type: ndcg_at_1000
1078
- value: 40.335
1079
  - type: ndcg_at_3
1080
- value: 28.522
1081
  - type: ndcg_at_5
1082
- value: 30.659
1083
  - type: precision_at_1
1084
- value: 23.474999999999998
1085
  - type: precision_at_10
1086
- value: 5.157
1087
  - type: precision_at_100
1088
- value: 0.83
1089
  - type: precision_at_1000
1090
- value: 0.11499999999999999
1091
  - type: precision_at_3
1092
- value: 11.953
1093
  - type: precision_at_5
1094
- value: 8.540000000000001
1095
  - type: recall_at_1
1096
- value: 21.818
1097
  - type: recall_at_10
1098
- value: 44.029
1099
  - type: recall_at_100
1100
- value: 67.906
1101
  - type: recall_at_1000
1102
- value: 85.387
1103
  - type: recall_at_3
1104
- value: 31.965
1105
  - type: recall_at_5
1106
- value: 37.079
1107
  - task:
1108
  type: Retrieval
1109
  dataset:
@@ -1114,65 +1114,65 @@ model-index:
1114
  revision: None
1115
  metrics:
1116
  - type: map_at_1
1117
- value: 17.615
1118
  - type: map_at_10
1119
- value: 30.302
1120
  - type: map_at_100
1121
- value: 32.382
1122
  - type: map_at_1000
1123
- value: 32.573
1124
  - type: map_at_3
1125
- value: 25.689
1126
  - type: map_at_5
1127
- value: 28.137
1128
  - type: mrr_at_1
1129
- value: 40.847
1130
  - type: mrr_at_10
1131
- value: 53.577
1132
  - type: mrr_at_100
1133
- value: 54.19199999999999
1134
  - type: mrr_at_1000
1135
- value: 54.217999999999996
1136
  - type: mrr_at_3
1137
- value: 50.684
1138
  - type: mrr_at_5
1139
- value: 52.349000000000004
1140
  - type: ndcg_at_1
1141
- value: 40.847
1142
  - type: ndcg_at_10
1143
- value: 40.497
1144
  - type: ndcg_at_100
1145
- value: 47.575
1146
  - type: ndcg_at_1000
1147
- value: 50.663000000000004
1148
  - type: ndcg_at_3
1149
- value: 34.650999999999996
1150
  - type: ndcg_at_5
1151
- value: 36.503
1152
  - type: precision_at_1
1153
- value: 40.847
1154
  - type: precision_at_10
1155
- value: 12.469
1156
  - type: precision_at_100
1157
- value: 2.012
1158
  - type: precision_at_1000
1159
- value: 0.259
1160
  - type: precision_at_3
1161
- value: 26.124000000000002
1162
  - type: precision_at_5
1163
- value: 19.518
1164
  - type: recall_at_1
1165
- value: 17.615
1166
  - type: recall_at_10
1167
- value: 46.163
1168
  - type: recall_at_100
1169
- value: 69.985
1170
  - type: recall_at_1000
1171
- value: 87.033
1172
  - type: recall_at_3
1173
- value: 31.041999999999998
1174
  - type: recall_at_5
1175
- value: 37.419999999999995
1176
  - task:
1177
  type: Retrieval
1178
  dataset:
@@ -1183,65 +1183,65 @@ model-index:
1183
  revision: None
1184
  metrics:
1185
  - type: map_at_1
1186
- value: 8.616999999999999
1187
  - type: map_at_10
1188
- value: 20.591
1189
  - type: map_at_100
1190
- value: 29.738
1191
  - type: map_at_1000
1192
- value: 31.403
1193
  - type: map_at_3
1194
- value: 14.549999999999999
1195
  - type: map_at_5
1196
- value: 17.071
1197
  - type: mrr_at_1
1198
- value: 71.25
1199
  - type: mrr_at_10
1200
- value: 77.86699999999999
1201
  - type: mrr_at_100
1202
- value: 78.154
1203
  - type: mrr_at_1000
1204
- value: 78.159
1205
  - type: mrr_at_3
1206
- value: 76.333
1207
  - type: mrr_at_5
1208
- value: 77.146
1209
  - type: ndcg_at_1
1210
- value: 59.875
1211
  - type: ndcg_at_10
1212
- value: 45.233000000000004
1213
  - type: ndcg_at_100
1214
- value: 49.395
1215
  - type: ndcg_at_1000
1216
- value: 56.352000000000004
1217
  - type: ndcg_at_3
1218
- value: 50.171
1219
  - type: ndcg_at_5
1220
- value: 47.3
1221
  - type: precision_at_1
1222
- value: 71.25
1223
  - type: precision_at_10
1224
- value: 35.9
1225
  - type: precision_at_100
1226
- value: 11.733
1227
  - type: precision_at_1000
1228
- value: 2.111
1229
  - type: precision_at_3
1230
- value: 52.917
1231
  - type: precision_at_5
1232
- value: 45.25
1233
  - type: recall_at_1
1234
- value: 8.616999999999999
1235
  - type: recall_at_10
1236
- value: 26.571
1237
  - type: recall_at_100
1238
- value: 55.289
1239
  - type: recall_at_1000
1240
- value: 77.66300000000001
1241
  - type: recall_at_3
1242
- value: 15.823
1243
  - type: recall_at_5
1244
- value: 19.921
1245
  - task:
1246
  type: Classification
1247
  dataset:
@@ -1252,9 +1252,9 @@ model-index:
1252
  revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
1253
  metrics:
1254
  - type: accuracy
1255
- value: 48.584999999999994
1256
  - type: f1
1257
- value: 43.715445937798705
1258
  - task:
1259
  type: Retrieval
1260
  dataset:
@@ -1265,65 +1265,65 @@ model-index:
1265
  revision: None
1266
  metrics:
1267
  - type: map_at_1
1268
- value: 72.175
1269
  - type: map_at_10
1270
- value: 81.659
1271
  - type: map_at_100
1272
- value: 81.918
1273
  - type: map_at_1000
1274
- value: 81.931
1275
  - type: map_at_3
1276
- value: 80.304
1277
  - type: map_at_5
1278
- value: 81.21199999999999
1279
  - type: mrr_at_1
1280
- value: 77.333
1281
  - type: mrr_at_10
1282
- value: 85.26
1283
  - type: mrr_at_100
1284
- value: 85.37400000000001
1285
  - type: mrr_at_1000
1286
- value: 85.37599999999999
1287
  - type: mrr_at_3
1288
- value: 84.378
1289
  - type: mrr_at_5
1290
- value: 85.001
1291
  - type: ndcg_at_1
1292
- value: 77.333
1293
  - type: ndcg_at_10
1294
- value: 85.533
1295
  - type: ndcg_at_100
1296
- value: 86.483
1297
  - type: ndcg_at_1000
1298
- value: 86.721
1299
  - type: ndcg_at_3
1300
- value: 83.434
1301
  - type: ndcg_at_5
1302
- value: 84.71
1303
  - type: precision_at_1
1304
- value: 77.333
1305
  - type: precision_at_10
1306
- value: 10.485999999999999
1307
  - type: precision_at_100
1308
- value: 1.121
1309
  - type: precision_at_1000
1310
- value: 0.116
1311
  - type: precision_at_3
1312
- value: 32.198
1313
  - type: precision_at_5
1314
- value: 20.222
1315
  - type: recall_at_1
1316
- value: 72.175
1317
  - type: recall_at_10
1318
- value: 93.633
1319
  - type: recall_at_100
1320
- value: 97.42699999999999
1321
  - type: recall_at_1000
1322
- value: 98.94
1323
  - type: recall_at_3
1324
- value: 88.07199999999999
1325
  - type: recall_at_5
1326
- value: 91.223
1327
  - task:
1328
  type: Retrieval
1329
  dataset:
@@ -1334,65 +1334,65 @@ model-index:
1334
  revision: None
1335
  metrics:
1336
  - type: map_at_1
1337
- value: 19.287000000000003
1338
  - type: map_at_10
1339
- value: 31.136000000000003
1340
  - type: map_at_100
1341
- value: 32.827
1342
  - type: map_at_1000
1343
- value: 33.011
1344
  - type: map_at_3
1345
- value: 27.150999999999996
1346
  - type: map_at_5
1347
- value: 29.459999999999997
1348
  - type: mrr_at_1
1349
- value: 37.963
1350
  - type: mrr_at_10
1351
- value: 46.449
1352
  - type: mrr_at_100
1353
- value: 47.353
1354
  - type: mrr_at_1000
1355
- value: 47.39
1356
  - type: mrr_at_3
1357
- value: 44.11
1358
  - type: mrr_at_5
1359
- value: 45.391
1360
  - type: ndcg_at_1
1361
- value: 37.963
1362
  - type: ndcg_at_10
1363
- value: 38.644
1364
  - type: ndcg_at_100
1365
- value: 44.923
1366
  - type: ndcg_at_1000
1367
- value: 48.059000000000005
1368
  - type: ndcg_at_3
1369
- value: 35.141
1370
  - type: ndcg_at_5
1371
- value: 36.335
1372
  - type: precision_at_1
1373
- value: 37.963
1374
  - type: precision_at_10
1375
  value: 10.494
1376
  - type: precision_at_100
1377
- value: 1.691
1378
  - type: precision_at_1000
1379
- value: 0.22699999999999998
1380
  - type: precision_at_3
1381
- value: 23.405
1382
  - type: precision_at_5
1383
- value: 17.16
1384
  - type: recall_at_1
1385
- value: 19.287000000000003
1386
  - type: recall_at_10
1387
- value: 45.558
1388
  - type: recall_at_100
1389
- value: 68.508
1390
  - type: recall_at_1000
1391
- value: 87.10900000000001
1392
  - type: recall_at_3
1393
- value: 31.991000000000003
1394
  - type: recall_at_5
1395
- value: 38.044
1396
  - task:
1397
  type: Retrieval
1398
  dataset:
@@ -1403,65 +1403,65 @@ model-index:
1403
  revision: None
1404
  metrics:
1405
  - type: map_at_1
1406
- value: 40.088
1407
  - type: map_at_10
1408
- value: 66.891
1409
  - type: map_at_100
1410
- value: 67.697
1411
  - type: map_at_1000
1412
- value: 67.75
1413
  - type: map_at_3
1414
- value: 63.517999999999994
1415
  - type: map_at_5
1416
- value: 65.667
1417
  - type: mrr_at_1
1418
- value: 80.176
1419
  - type: mrr_at_10
1420
- value: 85.662
1421
  - type: mrr_at_100
1422
- value: 85.827
1423
  - type: mrr_at_1000
1424
- value: 85.833
1425
  - type: mrr_at_3
1426
- value: 84.80799999999999
1427
  - type: mrr_at_5
1428
- value: 85.349
1429
  - type: ndcg_at_1
1430
- value: 80.176
1431
  - type: ndcg_at_10
1432
- value: 74.349
1433
  - type: ndcg_at_100
1434
- value: 77.10000000000001
1435
  - type: ndcg_at_1000
1436
- value: 78.084
1437
  - type: ndcg_at_3
1438
- value: 69.647
1439
  - type: ndcg_at_5
1440
- value: 72.312
1441
  - type: precision_at_1
1442
- value: 80.176
1443
  - type: precision_at_10
1444
- value: 15.629999999999999
1445
  - type: precision_at_100
1446
- value: 1.7760000000000002
1447
  - type: precision_at_1000
1448
- value: 0.191
1449
  - type: precision_at_3
1450
- value: 45.186
1451
  - type: precision_at_5
1452
- value: 29.215000000000003
1453
  - type: recall_at_1
1454
- value: 40.088
1455
  - type: recall_at_10
1456
- value: 78.14999999999999
1457
  - type: recall_at_100
1458
- value: 88.818
1459
  - type: recall_at_1000
1460
- value: 95.273
1461
  - type: recall_at_3
1462
- value: 67.779
1463
  - type: recall_at_5
1464
- value: 73.038
1465
  - task:
1466
  type: Classification
1467
  dataset:
@@ -1472,11 +1472,11 @@ model-index:
1472
  revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
1473
  metrics:
1474
  - type: accuracy
1475
- value: 83.81960000000002
1476
  - type: ap
1477
- value: 78.83196561301477
1478
  - type: f1
1479
- value: 83.75970806716482
1480
  - task:
1481
  type: Retrieval
1482
  dataset:
@@ -1487,65 +1487,65 @@ model-index:
1487
  revision: None
1488
  metrics:
1489
  - type: map_at_1
1490
- value: 23.318
1491
  - type: map_at_10
1492
- value: 35.988
1493
  - type: map_at_100
1494
- value: 37.172
1495
  - type: map_at_1000
1496
- value: 37.217
1497
  - type: map_at_3
1498
- value: 32.193
1499
  - type: map_at_5
1500
- value: 34.467
1501
  - type: mrr_at_1
1502
- value: 23.982999999999997
1503
  - type: mrr_at_10
1504
- value: 36.588
1505
  - type: mrr_at_100
1506
- value: 37.714999999999996
1507
  - type: mrr_at_1000
1508
- value: 37.754
1509
  - type: mrr_at_3
1510
- value: 32.844
1511
  - type: mrr_at_5
1512
- value: 35.106
1513
  - type: ndcg_at_1
1514
- value: 23.982999999999997
1515
  - type: ndcg_at_10
1516
- value: 42.870000000000005
1517
  - type: ndcg_at_100
1518
- value: 48.433
1519
  - type: ndcg_at_1000
1520
- value: 49.559
1521
  - type: ndcg_at_3
1522
- value: 35.211
1523
  - type: ndcg_at_5
1524
- value: 39.273
1525
  - type: precision_at_1
1526
- value: 23.982999999999997
1527
  - type: precision_at_10
1528
- value: 6.678000000000001
1529
  - type: precision_at_100
1530
- value: 0.9440000000000001
1531
  - type: precision_at_1000
1532
  value: 0.104
1533
  - type: precision_at_3
1534
- value: 14.981
1535
  - type: precision_at_5
1536
- value: 11.046
1537
  - type: recall_at_1
1538
- value: 23.318
1539
  - type: recall_at_10
1540
- value: 63.934999999999995
1541
  - type: recall_at_100
1542
- value: 89.335
1543
  - type: recall_at_1000
1544
- value: 97.966
1545
  - type: recall_at_3
1546
- value: 43.283
1547
  - type: recall_at_5
1548
- value: 53.041000000000004
1549
  - task:
1550
  type: Classification
1551
  dataset:
@@ -1556,9 +1556,9 @@ model-index:
1556
  revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
1557
  metrics:
1558
  - type: accuracy
1559
- value: 93.57045143638851
1560
  - type: f1
1561
- value: 93.27721271351861
1562
  - task:
1563
  type: Classification
1564
  dataset:
@@ -1569,9 +1569,9 @@ model-index:
1569
  revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1570
  metrics:
1571
  - type: accuracy
1572
- value: 75.33971728226174
1573
  - type: f1
1574
- value: 57.738940854439825
1575
  - task:
1576
  type: Classification
1577
  dataset:
@@ -1582,9 +1582,9 @@ model-index:
1582
  revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
1583
  metrics:
1584
  - type: accuracy
1585
- value: 73.05985205110962
1586
  - type: f1
1587
- value: 71.13355537275797
1588
  - task:
1589
  type: Classification
1590
  dataset:
@@ -1595,9 +1595,9 @@ model-index:
1595
  revision: 7d571f92784cd94a019292a1f45445077d0ef634
1596
  metrics:
1597
  - type: accuracy
1598
- value: 77.38063214525891
1599
  - type: f1
1600
- value: 77.50780716460197
1601
  - task:
1602
  type: Clustering
1603
  dataset:
@@ -1608,7 +1608,7 @@ model-index:
1608
  revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
1609
  metrics:
1610
  - type: v_measure
1611
- value: 32.74942819235406
1612
  - task:
1613
  type: Clustering
1614
  dataset:
@@ -1619,7 +1619,7 @@ model-index:
1619
  revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
1620
  metrics:
1621
  - type: v_measure
1622
- value: 30.696610712314364
1623
  - task:
1624
  type: Reranking
1625
  dataset:
@@ -1630,9 +1630,9 @@ model-index:
1630
  revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
1631
  metrics:
1632
  - type: map
1633
- value: 28.7236836309487
1634
  - type: mrr
1635
- value: 29.45527326120238
1636
  - task:
1637
  type: Retrieval
1638
  dataset:
@@ -1643,65 +1643,65 @@ model-index:
1643
  revision: None
1644
  metrics:
1645
  - type: map_at_1
1646
- value: 5.838
1647
  - type: map_at_10
1648
- value: 13.492999999999999
1649
  - type: map_at_100
1650
- value: 16.598
1651
  - type: map_at_1000
1652
- value: 17.937
1653
  - type: map_at_3
1654
- value: 10.119
1655
  - type: map_at_5
1656
- value: 11.666
1657
  - type: mrr_at_1
1658
  value: 45.201
1659
  - type: mrr_at_10
1660
- value: 54.391
1661
  - type: mrr_at_100
1662
- value: 54.913000000000004
1663
  - type: mrr_at_1000
1664
- value: 54.952
1665
  - type: mrr_at_3
1666
- value: 52.012
1667
  - type: mrr_at_5
1668
- value: 53.715
1669
  - type: ndcg_at_1
1670
- value: 43.498
1671
  - type: ndcg_at_10
1672
- value: 35.631
1673
  - type: ndcg_at_100
1674
- value: 31.522
1675
  - type: ndcg_at_1000
1676
- value: 39.967000000000006
1677
  - type: ndcg_at_3
1678
- value: 41.258
1679
  - type: ndcg_at_5
1680
- value: 39.007
1681
  - type: precision_at_1
1682
- value: 44.891999999999996
1683
  - type: precision_at_10
1684
- value: 26.409
1685
  - type: precision_at_100
1686
- value: 7.799
1687
  - type: precision_at_1000
1688
- value: 2.044
1689
  - type: precision_at_3
1690
- value: 39.216
1691
  - type: precision_at_5
1692
- value: 34.056
1693
  - type: recall_at_1
1694
- value: 5.838
1695
  - type: recall_at_10
1696
- value: 17.314
1697
  - type: recall_at_100
1698
- value: 30.653000000000002
1699
  - type: recall_at_1000
1700
- value: 61.092
1701
  - type: recall_at_3
1702
- value: 11.299
1703
  - type: recall_at_5
1704
- value: 13.689000000000002
1705
  - task:
1706
  type: Retrieval
1707
  dataset:
@@ -1712,65 +1712,65 @@ model-index:
1712
  revision: None
1713
  metrics:
1714
  - type: map_at_1
1715
- value: 37.08
1716
  - type: map_at_10
1717
- value: 52.493
1718
  - type: map_at_100
1719
- value: 53.39699999999999
1720
  - type: map_at_1000
1721
- value: 53.422000000000004
1722
  - type: map_at_3
1723
- value: 48.504000000000005
1724
  - type: map_at_5
1725
- value: 50.878
1726
  - type: mrr_at_1
1727
- value: 41.425
1728
  - type: mrr_at_10
1729
- value: 55.001999999999995
1730
  - type: mrr_at_100
1731
- value: 55.665
1732
  - type: mrr_at_1000
1733
- value: 55.681999999999995
1734
  - type: mrr_at_3
1735
- value: 51.873000000000005
1736
  - type: mrr_at_5
1737
- value: 53.801
1738
  - type: ndcg_at_1
1739
- value: 41.396
1740
  - type: ndcg_at_10
1741
- value: 59.77400000000001
1742
  - type: ndcg_at_100
1743
- value: 63.476
1744
  - type: ndcg_at_1000
1745
- value: 64.011
1746
  - type: ndcg_at_3
1747
- value: 52.504
1748
  - type: ndcg_at_5
1749
- value: 56.379000000000005
1750
  - type: precision_at_1
1751
- value: 41.396
1752
  - type: precision_at_10
1753
- value: 9.429
1754
  - type: precision_at_100
1755
- value: 1.1520000000000001
1756
  - type: precision_at_1000
1757
  value: 0.12
1758
  - type: precision_at_3
1759
- value: 23.445
1760
  - type: precision_at_5
1761
- value: 16.333000000000002
1762
  - type: recall_at_1
1763
- value: 37.08
1764
  - type: recall_at_10
1765
- value: 79.22
1766
  - type: recall_at_100
1767
- value: 95.013
1768
  - type: recall_at_1000
1769
- value: 98.921
1770
  - type: recall_at_3
1771
- value: 60.702
1772
  - type: recall_at_5
1773
- value: 69.539
1774
  - task:
1775
  type: Retrieval
1776
  dataset:
@@ -1781,65 +1781,65 @@ model-index:
1781
  revision: None
1782
  metrics:
1783
  - type: map_at_1
1784
- value: 70.218
1785
  - type: map_at_10
1786
- value: 83.871
1787
  - type: map_at_100
1788
- value: 84.494
1789
  - type: map_at_1000
1790
- value: 84.514
1791
  - type: map_at_3
1792
- value: 80.95
1793
  - type: map_at_5
1794
- value: 82.783
1795
  - type: mrr_at_1
1796
- value: 80.9
1797
  - type: mrr_at_10
1798
- value: 87.176
1799
  - type: mrr_at_100
1800
- value: 87.283
1801
  - type: mrr_at_1000
1802
- value: 87.28399999999999
1803
  - type: mrr_at_3
1804
- value: 86.173
1805
  - type: mrr_at_5
1806
- value: 86.872
1807
  - type: ndcg_at_1
1808
- value: 80.92
1809
  - type: ndcg_at_10
1810
- value: 87.76899999999999
1811
  - type: ndcg_at_100
1812
- value: 89.017
1813
  - type: ndcg_at_1000
1814
- value: 89.154
1815
  - type: ndcg_at_3
1816
- value: 84.87
1817
  - type: ndcg_at_5
1818
- value: 86.469
1819
  - type: precision_at_1
1820
- value: 80.92
1821
  - type: precision_at_10
1822
- value: 13.272
1823
  - type: precision_at_100
1824
- value: 1.5150000000000001
1825
  - type: precision_at_1000
1826
  value: 0.156
1827
  - type: precision_at_3
1828
- value: 37.03
1829
  - type: precision_at_5
1830
- value: 24.336
1831
  - type: recall_at_1
1832
- value: 70.218
1833
  - type: recall_at_10
1834
- value: 95.027
1835
  - type: recall_at_100
1836
- value: 99.29599999999999
1837
  - type: recall_at_1000
1838
- value: 99.936
1839
  - type: recall_at_3
1840
- value: 86.64
1841
  - type: recall_at_5
1842
- value: 91.23
1843
  - task:
1844
  type: Clustering
1845
  dataset:
@@ -1850,7 +1850,7 @@ model-index:
1850
  revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
1851
  metrics:
1852
  - type: v_measure
1853
- value: 56.98075987853009
1854
  - task:
1855
  type: Clustering
1856
  dataset:
@@ -1861,7 +1861,7 @@ model-index:
1861
  revision: 282350215ef01743dc01b456c7f5241fa8937f16
1862
  metrics:
1863
  - type: v_measure
1864
- value: 62.50448653901921
1865
  - task:
1866
  type: Retrieval
1867
  dataset:
@@ -1872,65 +1872,65 @@ model-index:
1872
  revision: None
1873
  metrics:
1874
  - type: map_at_1
1875
- value: 4.303
1876
  - type: map_at_10
1877
- value: 10.918999999999999
1878
  - type: map_at_100
1879
- value: 12.709999999999999
1880
  - type: map_at_1000
1881
- value: 12.985
1882
  - type: map_at_3
1883
- value: 7.924
1884
  - type: map_at_5
1885
- value: 9.299
1886
  - type: mrr_at_1
1887
- value: 21.2
1888
  - type: mrr_at_10
1889
- value: 31.732
1890
  - type: mrr_at_100
1891
- value: 32.716
1892
  - type: mrr_at_1000
1893
- value: 32.775999999999996
1894
  - type: mrr_at_3
1895
- value: 28.549999999999997
1896
  - type: mrr_at_5
1897
- value: 30.064999999999998
1898
  - type: ndcg_at_1
1899
- value: 21.2
1900
  - type: ndcg_at_10
1901
- value: 18.576999999999998
1902
  - type: ndcg_at_100
1903
- value: 25.648
1904
  - type: ndcg_at_1000
1905
- value: 30.733
1906
  - type: ndcg_at_3
1907
- value: 17.718999999999998
1908
  - type: ndcg_at_5
1909
- value: 15.123000000000001
1910
  - type: precision_at_1
1911
- value: 21.2
1912
  - type: precision_at_10
1913
- value: 9.71
1914
  - type: precision_at_100
1915
- value: 1.992
1916
  - type: precision_at_1000
1917
- value: 0.322
1918
  - type: precision_at_3
1919
- value: 16.7
1920
  - type: precision_at_5
1921
- value: 13.18
1922
  - type: recall_at_1
1923
- value: 4.303
1924
  - type: recall_at_10
1925
- value: 19.688
1926
  - type: recall_at_100
1927
- value: 40.453
1928
  - type: recall_at_1000
1929
- value: 65.348
1930
  - type: recall_at_3
1931
- value: 10.148
1932
  - type: recall_at_5
1933
- value: 13.347999999999999
1934
  - task:
1935
  type: STS
1936
  dataset:
@@ -1941,17 +1941,17 @@ model-index:
1941
  revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
1942
  metrics:
1943
  - type: cos_sim_pearson
1944
- value: 82.1158093156676
1945
  - type: cos_sim_spearman
1946
- value: 78.04442753931265
1947
  - type: euclidean_pearson
1948
- value: 79.96880352884281
1949
  - type: euclidean_spearman
1950
- value: 78.04442519916647
1951
  - type: manhattan_pearson
1952
- value: 79.95975401430859
1953
  - type: manhattan_spearman
1954
- value: 78.03343142853139
1955
  - task:
1956
  type: STS
1957
  dataset:
@@ -1962,17 +1962,17 @@ model-index:
1962
  revision: a0d554a64d88156834ff5ae9920b964011b16384
1963
  metrics:
1964
  - type: cos_sim_pearson
1965
- value: 83.79721434783521
1966
  - type: cos_sim_spearman
1967
- value: 78.25975096999896
1968
  - type: euclidean_pearson
1969
- value: 79.1424902310369
1970
  - type: euclidean_spearman
1971
- value: 78.25975658297341
1972
  - type: manhattan_pearson
1973
- value: 79.18358724961024
1974
  - type: manhattan_spearman
1975
- value: 78.25842688776181
1976
  - task:
1977
  type: STS
1978
  dataset:
@@ -1983,17 +1983,17 @@ model-index:
1983
  revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
1984
  metrics:
1985
  - type: cos_sim_pearson
1986
- value: 83.01380419796578
1987
  - type: cos_sim_spearman
1988
- value: 84.25947132331721
1989
  - type: euclidean_pearson
1990
- value: 83.60092535471402
1991
  - type: euclidean_spearman
1992
- value: 84.25947132331721
1993
  - type: manhattan_pearson
1994
- value: 83.58567994241997
1995
  - type: manhattan_spearman
1996
- value: 84.26967070369717
1997
  - task:
1998
  type: STS
1999
  dataset:
@@ -2004,17 +2004,17 @@ model-index:
2004
  revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
2005
  metrics:
2006
  - type: cos_sim_pearson
2007
- value: 81.21721151989871
2008
  - type: cos_sim_spearman
2009
- value: 80.54270694465328
2010
  - type: euclidean_pearson
2011
- value: 80.59816986031214
2012
  - type: euclidean_spearman
2013
- value: 80.54271664913747
2014
  - type: manhattan_pearson
2015
- value: 80.5726582983618
2016
  - type: manhattan_spearman
2017
- value: 80.5337273819897
2018
  - task:
2019
  type: STS
2020
  dataset:
@@ -2025,17 +2025,17 @@ model-index:
2025
  revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
2026
  metrics:
2027
  - type: cos_sim_pearson
2028
- value: 85.37279580582026
2029
  - type: cos_sim_spearman
2030
- value: 86.49650639126628
2031
  - type: euclidean_pearson
2032
- value: 86.16280095909306
2033
  - type: euclidean_spearman
2034
- value: 86.49650639126628
2035
  - type: manhattan_pearson
2036
- value: 86.10906620664134
2037
  - type: manhattan_spearman
2038
- value: 86.43874476942065
2039
  - task:
2040
  type: STS
2041
  dataset:
@@ -2046,17 +2046,17 @@ model-index:
2046
  revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
2047
  metrics:
2048
  - type: cos_sim_pearson
2049
- value: 83.25909618059293
2050
  - type: cos_sim_spearman
2051
- value: 85.13586725576114
2052
  - type: euclidean_pearson
2053
- value: 84.23420740305912
2054
  - type: euclidean_spearman
2055
- value: 85.13586725576114
2056
  - type: manhattan_pearson
2057
- value: 84.31272025462884
2058
  - type: manhattan_spearman
2059
- value: 85.21734270533285
2060
  - task:
2061
  type: STS
2062
  dataset:
@@ -2067,17 +2067,17 @@ model-index:
2067
  revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
2068
  metrics:
2069
  - type: cos_sim_pearson
2070
- value: 86.36016115914764
2071
  - type: cos_sim_spearman
2072
- value: 86.50087120712864
2073
  - type: euclidean_pearson
2074
- value: 87.43563849261436
2075
  - type: euclidean_spearman
2076
- value: 86.50087120712864
2077
  - type: manhattan_pearson
2078
- value: 87.3340358043399
2079
  - type: manhattan_spearman
2080
- value: 86.48887803473512
2081
  - task:
2082
  type: STS
2083
  dataset:
@@ -2088,17 +2088,17 @@ model-index:
2088
  revision: eea2b4fe26a775864c896887d910b76a8098ad3f
2089
  metrics:
2090
  - type: cos_sim_pearson
2091
- value: 65.4382473357056
2092
  - type: cos_sim_spearman
2093
- value: 65.02380140355883
2094
  - type: euclidean_pearson
2095
- value: 66.29732592598693
2096
  - type: euclidean_spearman
2097
- value: 65.02380140355883
2098
  - type: manhattan_pearson
2099
- value: 66.60136092354136
2100
  - type: manhattan_spearman
2101
- value: 65.21766397453412
2102
  - task:
2103
  type: STS
2104
  dataset:
@@ -2109,17 +2109,17 @@ model-index:
2109
  revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
2110
  metrics:
2111
  - type: cos_sim_pearson
2112
- value: 84.10229648323359
2113
  - type: cos_sim_spearman
2114
- value: 84.81137203891447
2115
  - type: euclidean_pearson
2116
- value: 84.30614386139715
2117
  - type: euclidean_spearman
2118
- value: 84.81137203891447
2119
  - type: manhattan_pearson
2120
- value: 84.34828274644255
2121
  - type: manhattan_spearman
2122
- value: 84.8268824733233
2123
  - task:
2124
  type: Reranking
2125
  dataset:
@@ -2130,9 +2130,9 @@ model-index:
2130
  revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
2131
  metrics:
2132
  - type: map
2133
- value: 81.0838765555117
2134
  - type: mrr
2135
- value: 94.65012928248223
2136
  - task:
2137
  type: Retrieval
2138
  dataset:
@@ -2143,65 +2143,65 @@ model-index:
2143
  revision: None
2144
  metrics:
2145
  - type: map_at_1
2146
- value: 57.760999999999996
2147
  - type: map_at_10
2148
- value: 67.12
2149
  - type: map_at_100
2150
- value: 67.69
2151
  - type: map_at_1000
2152
- value: 67.716
2153
  - type: map_at_3
2154
- value: 64.846
2155
  - type: map_at_5
2156
- value: 66.148
2157
  - type: mrr_at_1
2158
- value: 60.667
2159
  - type: mrr_at_10
2160
- value: 68.497
2161
  - type: mrr_at_100
2162
- value: 68.92200000000001
2163
  - type: mrr_at_1000
2164
- value: 68.944
2165
  - type: mrr_at_3
2166
- value: 66.889
2167
  - type: mrr_at_5
2168
- value: 67.839
2169
  - type: ndcg_at_1
2170
- value: 60.667
2171
  - type: ndcg_at_10
2172
- value: 71.429
2173
  - type: ndcg_at_100
2174
- value: 73.821
2175
  - type: ndcg_at_1000
2176
- value: 74.524
2177
  - type: ndcg_at_3
2178
- value: 67.57600000000001
2179
  - type: ndcg_at_5
2180
- value: 69.44500000000001
2181
  - type: precision_at_1
2182
- value: 60.667
2183
  - type: precision_at_10
2184
- value: 9.333
2185
  - type: precision_at_100
2186
- value: 1.0630000000000002
2187
  - type: precision_at_1000
2188
  value: 0.11199999999999999
2189
  - type: precision_at_3
2190
- value: 26.333000000000002
2191
  - type: precision_at_5
2192
- value: 17.133000000000003
2193
  - type: recall_at_1
2194
- value: 57.760999999999996
2195
  - type: recall_at_10
2196
- value: 83.122
2197
  - type: recall_at_100
2198
- value: 93.767
2199
  - type: recall_at_1000
2200
- value: 99.333
2201
  - type: recall_at_3
2202
- value: 72.64399999999999
2203
  - type: recall_at_5
2204
- value: 77.378
2205
  - task:
2206
  type: PairClassification
2207
  dataset:
@@ -2212,51 +2212,51 @@ model-index:
2212
  revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
2213
  metrics:
2214
  - type: cos_sim_accuracy
2215
- value: 99.8108910891089
2216
  - type: cos_sim_ap
2217
- value: 95.09566660724403
2218
  - type: cos_sim_f1
2219
- value: 90.20408163265306
2220
  - type: cos_sim_precision
2221
- value: 92.08333333333333
2222
  - type: cos_sim_recall
2223
- value: 88.4
2224
  - type: dot_accuracy
2225
- value: 99.8108910891089
2226
  - type: dot_ap
2227
- value: 95.09566660724403
2228
  - type: dot_f1
2229
- value: 90.20408163265306
2230
  - type: dot_precision
2231
- value: 92.08333333333333
2232
  - type: dot_recall
2233
- value: 88.4
2234
  - type: euclidean_accuracy
2235
- value: 99.8108910891089
2236
  - type: euclidean_ap
2237
- value: 95.09566660724404
2238
  - type: euclidean_f1
2239
- value: 90.20408163265306
2240
  - type: euclidean_precision
2241
- value: 92.08333333333333
2242
  - type: euclidean_recall
2243
- value: 88.4
2244
  - type: manhattan_accuracy
2245
- value: 99.8108910891089
2246
  - type: manhattan_ap
2247
- value: 95.05229326105041
2248
  - type: manhattan_f1
2249
- value: 90.30948756976154
2250
  - type: manhattan_precision
2251
- value: 91.65808444902163
2252
  - type: manhattan_recall
2253
- value: 89.0
2254
  - type: max_accuracy
2255
- value: 99.8108910891089
2256
  - type: max_ap
2257
- value: 95.09566660724404
2258
  - type: max_f1
2259
- value: 90.30948756976154
2260
  - task:
2261
  type: Clustering
2262
  dataset:
@@ -2267,7 +2267,7 @@ model-index:
2267
  revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2268
  metrics:
2269
  - type: v_measure
2270
- value: 63.716387449356304
2271
  - task:
2272
  type: Clustering
2273
  dataset:
@@ -2278,7 +2278,7 @@ model-index:
2278
  revision: 815ca46b2622cec33ccafc3735d572c266efdb44
2279
  metrics:
2280
  - type: v_measure
2281
- value: 33.57171985530598
2282
  - task:
2283
  type: Reranking
2284
  dataset:
@@ -2289,9 +2289,9 @@ model-index:
2289
  revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
2290
  metrics:
2291
  - type: map
2292
- value: 50.31022782714341
2293
  - type: mrr
2294
- value: 51.005100903997956
2295
  - task:
2296
  type: Summarization
2297
  dataset:
@@ -2302,13 +2302,13 @@ model-index:
2302
  revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
2303
  metrics:
2304
  - type: cos_sim_pearson
2305
- value: 30.55380844566254
2306
  - type: cos_sim_spearman
2307
- value: 30.694665194755576
2308
  - type: dot_pearson
2309
- value: 30.553807051946595
2310
  - type: dot_spearman
2311
- value: 30.694665194755576
2312
  - task:
2313
  type: Retrieval
2314
  dataset:
@@ -2319,65 +2319,65 @@ model-index:
2319
  revision: None
2320
  metrics:
2321
  - type: map_at_1
2322
- value: 0.231
2323
  - type: map_at_10
2324
- value: 2.097
2325
  - type: map_at_100
2326
- value: 11.899999999999999
2327
  - type: map_at_1000
2328
- value: 27.965
2329
  - type: map_at_3
2330
- value: 0.7040000000000001
2331
  - type: map_at_5
2332
- value: 1.13
2333
  - type: mrr_at_1
2334
- value: 88.0
2335
  - type: mrr_at_10
2336
- value: 94.0
2337
  - type: mrr_at_100
2338
- value: 94.0
2339
  - type: mrr_at_1000
2340
- value: 94.0
2341
  - type: mrr_at_3
2342
- value: 94.0
2343
  - type: mrr_at_5
2344
- value: 94.0
2345
  - type: ndcg_at_1
2346
- value: 82.0
2347
  - type: ndcg_at_10
2348
- value: 79.72
2349
  - type: ndcg_at_100
2350
- value: 60.731
2351
  - type: ndcg_at_1000
2352
- value: 52.528
2353
  - type: ndcg_at_3
2354
- value: 84.776
2355
  - type: ndcg_at_5
2356
- value: 83.977
2357
  - type: precision_at_1
2358
- value: 88.0
2359
  - type: precision_at_10
2360
- value: 84.8
2361
  - type: precision_at_100
2362
- value: 62.46000000000001
2363
  - type: precision_at_1000
2364
- value: 23.336000000000002
2365
  - type: precision_at_3
2366
- value: 91.333
2367
  - type: precision_at_5
2368
- value: 89.60000000000001
2369
  - type: recall_at_1
2370
- value: 0.231
2371
  - type: recall_at_10
2372
- value: 2.242
2373
  - type: recall_at_100
2374
- value: 14.629
2375
  - type: recall_at_1000
2376
- value: 48.937999999999995
2377
  - type: recall_at_3
2378
- value: 0.733
2379
  - type: recall_at_5
2380
- value: 1.187
2381
  - task:
2382
  type: Retrieval
2383
  dataset:
@@ -2388,65 +2388,65 @@ model-index:
2388
  revision: None
2389
  metrics:
2390
  - type: map_at_1
2391
- value: 2.326
2392
  - type: map_at_10
2393
- value: 11.613
2394
  - type: map_at_100
2395
- value: 17.999000000000002
2396
  - type: map_at_1000
2397
- value: 19.579
2398
  - type: map_at_3
2399
- value: 5.5280000000000005
2400
  - type: map_at_5
2401
- value: 8.235000000000001
2402
  - type: mrr_at_1
2403
  value: 28.571
2404
  - type: mrr_at_10
2405
- value: 47.865
2406
  - type: mrr_at_100
2407
- value: 48.638999999999996
2408
  - type: mrr_at_1000
2409
- value: 48.638999999999996
2410
  - type: mrr_at_3
2411
- value: 42.516999999999996
2412
  - type: mrr_at_5
2413
- value: 46.293
2414
  - type: ndcg_at_1
2415
  value: 25.509999999999998
2416
  - type: ndcg_at_10
2417
- value: 28.663
2418
  - type: ndcg_at_100
2419
- value: 39.208
2420
  - type: ndcg_at_1000
2421
- value: 50.32
2422
  - type: ndcg_at_3
2423
- value: 28.636
2424
  - type: ndcg_at_5
2425
- value: 28.819
2426
  - type: precision_at_1
2427
  value: 28.571
2428
  - type: precision_at_10
2429
- value: 27.143
2430
  - type: precision_at_100
2431
- value: 8.082
2432
  - type: precision_at_1000
2433
- value: 1.543
2434
  - type: precision_at_3
2435
- value: 31.293
2436
  - type: precision_at_5
2437
- value: 31.019999999999996
2438
  - type: recall_at_1
2439
- value: 2.326
2440
  - type: recall_at_10
2441
- value: 19.12
2442
  - type: recall_at_100
2443
- value: 49.721
2444
  - type: recall_at_1000
2445
- value: 83.123
2446
  - type: recall_at_3
2447
- value: 6.783
2448
  - type: recall_at_5
2449
- value: 11.472999999999999
2450
  - task:
2451
  type: Classification
2452
  dataset:
@@ -2457,11 +2457,11 @@ model-index:
2457
  revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
2458
  metrics:
2459
  - type: accuracy
2460
- value: 70.39139999999999
2461
  - type: ap
2462
- value: 14.323066144268354
2463
  - type: f1
2464
- value: 54.37688697193885
2465
  - task:
2466
  type: Classification
2467
  dataset:
@@ -2472,9 +2472,9 @@ model-index:
2472
  revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
2473
  metrics:
2474
  - type: accuracy
2475
- value: 59.81890209394454
2476
  - type: f1
2477
- value: 60.116654203584496
2478
  - task:
2479
  type: Clustering
2480
  dataset:
@@ -2485,7 +2485,7 @@ model-index:
2485
  revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
2486
  metrics:
2487
  - type: v_measure
2488
- value: 49.5398447532487
2489
  - task:
2490
  type: PairClassification
2491
  dataset:
@@ -2496,51 +2496,51 @@ model-index:
2496
  revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
2497
  metrics:
2498
  - type: cos_sim_accuracy
2499
- value: 85.62317458425225
2500
  - type: cos_sim_ap
2501
- value: 72.58795996654061
2502
  - type: cos_sim_f1
2503
- value: 66.74816625916871
2504
  - type: cos_sim_precision
2505
- value: 62.1867881548975
2506
  - type: cos_sim_recall
2507
- value: 72.0316622691293
2508
  - type: dot_accuracy
2509
- value: 85.62317458425225
2510
  - type: dot_ap
2511
- value: 72.58796057492127
2512
  - type: dot_f1
2513
- value: 66.74816625916871
2514
  - type: dot_precision
2515
- value: 62.1867881548975
2516
  - type: dot_recall
2517
- value: 72.0316622691293
2518
  - type: euclidean_accuracy
2519
- value: 85.62317458425225
2520
  - type: euclidean_ap
2521
- value: 72.58798058258095
2522
  - type: euclidean_f1
2523
- value: 66.74816625916871
2524
  - type: euclidean_precision
2525
- value: 62.1867881548975
2526
  - type: euclidean_recall
2527
- value: 72.0316622691293
2528
  - type: manhattan_accuracy
2529
- value: 85.5754902545151
2530
  - type: manhattan_ap
2531
- value: 72.5765018516196
2532
  - type: manhattan_f1
2533
- value: 66.70611906734524
2534
  - type: manhattan_precision
2535
- value: 60.485082635758744
2536
  - type: manhattan_recall
2537
- value: 74.35356200527704
2538
  - type: max_accuracy
2539
- value: 85.62317458425225
2540
  - type: max_ap
2541
- value: 72.58798058258095
2542
  - type: max_f1
2543
- value: 66.74816625916871
2544
  - task:
2545
  type: PairClassification
2546
  dataset:
@@ -2551,49 +2551,49 @@ model-index:
2551
  revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
2552
  metrics:
2553
  - type: cos_sim_accuracy
2554
- value: 89.03830480847596
2555
  - type: cos_sim_ap
2556
- value: 86.09219791618496
2557
  - type: cos_sim_f1
2558
- value: 78.19673991150107
2559
  - type: cos_sim_precision
2560
- value: 76.84531331301568
2561
  - type: cos_sim_recall
2562
- value: 79.59655066214968
2563
  - type: dot_accuracy
2564
- value: 89.03830480847596
2565
  - type: dot_ap
2566
- value: 86.09219596898019
2567
  - type: dot_f1
2568
- value: 78.19673991150107
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  - type: dot_precision
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- value: 76.84531331301568
2571
  - type: dot_recall
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- value: 79.59655066214968
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  - type: euclidean_accuracy
2574
- value: 89.03830480847596
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  - type: euclidean_ap
2576
- value: 86.09219836933755
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  - type: euclidean_f1
2578
- value: 78.19673991150107
2579
  - type: euclidean_precision
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- value: 76.84531331301568
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  - type: euclidean_recall
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- value: 79.59655066214968
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  - type: manhattan_accuracy
2584
- value: 89.04024527496411
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  - type: manhattan_ap
2586
- value: 86.07752622427454
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  - type: manhattan_f1
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  - type: manhattan_precision
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  - type: manhattan_recall
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  - type: max_accuracy
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  - type: max_ap
2596
- value: 86.09219836933755
2597
  - type: max_f1
2598
- value: 78.19673991150107
2599
  ---
 
14
  revision: e8379541af4e31359cca9fbcf4b00f2671dba205
15
  metrics:
16
  - type: accuracy
17
+ value: 78.67164179104476
18
  - type: ap
19
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20
  - type: f1
21
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22
  - task:
23
  type: Classification
24
  dataset:
 
29
  revision: e2d317d38cd51312af73b3d32a06d1a08b442046
30
  metrics:
31
  - type: accuracy
32
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33
  - type: ap
34
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35
  - type: f1
36
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37
  - task:
38
  type: Classification
39
  dataset:
 
44
  revision: 1399c76144fd37290681b995c656ef9b2e06e26d
45
  metrics:
46
  - type: accuracy
47
+ value: 47.80799999999999
48
  - type: f1
49
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50
  - task:
51
  type: Retrieval
52
  dataset:
 
57
  revision: None
58
  metrics:
59
  - type: map_at_1
60
+ value: 30.37
61
  - type: map_at_10
62
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63
  - type: map_at_100
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65
  - type: map_at_1000
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  - type: map_at_3
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  - type: map_at_5
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71
  - type: mrr_at_1
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  - type: mrr_at_1000
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  - type: mrr_at_3
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81
  - type: mrr_at_5
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  - type: ndcg_at_1
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  - type: ndcg_at_10
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89
  - type: ndcg_at_1000
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  - type: ndcg_at_3
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  - type: precision_at_1
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  - type: precision_at_100
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  - type: precision_at_1000
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  - type: precision_at_3
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  - type: precision_at_5
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  - type: recall_at_1
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  - type: recall_at_10
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  - type: recall_at_100
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  - type: recall_at_1000
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  - type: recall_at_3
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  - type: recall_at_5
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  - task:
120
  type: Clustering
121
  dataset:
 
126
  revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
127
  metrics:
128
  - type: v_measure
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  - task:
131
  type: Clustering
132
  dataset:
 
137
  revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
138
  metrics:
139
  - type: v_measure
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141
  - task:
142
  type: Reranking
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  dataset:
 
148
  revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
149
  metrics:
150
  - type: map
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152
  - type: mrr
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  - task:
155
  type: STS
156
  dataset:
 
161
  revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
162
  metrics:
163
  - type: cos_sim_pearson
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165
  - type: cos_sim_spearman
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167
  - type: euclidean_pearson
168
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169
  - type: euclidean_spearman
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171
  - type: manhattan_pearson
172
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173
  - type: manhattan_spearman
174
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175
  - task:
176
  type: Classification
177
  dataset:
 
182
  revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
183
  metrics:
184
  - type: accuracy
185
+ value: 83.81818181818181
186
  - type: f1
187
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  - task:
189
  type: Clustering
190
  dataset:
 
195
  revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
196
  metrics:
197
  - type: v_measure
198
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  - task:
200
  type: Clustering
201
  dataset:
 
206
  revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
207
  metrics:
208
  - type: v_measure
209
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210
  - task:
211
  type: Retrieval
212
  dataset:
 
217
  revision: None
218
  metrics:
219
  - type: map_at_1
220
+ value: 29.725
221
  - type: map_at_10
222
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  - type: map_at_100
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225
  - type: map_at_1000
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227
  - type: map_at_3
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  - type: map_at_5
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235
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237
  - type: mrr_at_1000
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239
  - type: mrr_at_3
240
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241
  - type: mrr_at_5
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243
  - type: ndcg_at_1
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  - type: ndcg_at_10
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  - type: ndcg_at_100
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249
  - type: ndcg_at_1000
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251
  - type: ndcg_at_3
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253
  - type: ndcg_at_5
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  - type: precision_at_1
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  - type: precision_at_10
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  - type: precision_at_100
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261
  - type: precision_at_1000
262
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263
  - type: precision_at_3
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  - type: precision_at_5
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267
  - type: recall_at_1
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  - type: recall_at_10
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271
  - type: recall_at_100
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273
  - type: recall_at_1000
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275
  - type: recall_at_3
276
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277
  - type: recall_at_5
278
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279
  - task:
280
  type: Retrieval
281
  dataset:
 
286
  revision: None
287
  metrics:
288
  - type: map_at_1
289
+ value: 30.23
290
  - type: map_at_10
291
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292
  - type: map_at_100
293
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294
  - type: map_at_1000
295
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296
  - type: map_at_3
297
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298
  - type: map_at_5
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300
  - type: mrr_at_1
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302
  - type: mrr_at_10
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304
  - type: mrr_at_100
305
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306
  - type: mrr_at_1000
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308
  - type: mrr_at_3
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310
  - type: mrr_at_5
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312
  - type: ndcg_at_1
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314
  - type: ndcg_at_10
315
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316
  - type: ndcg_at_100
317
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318
  - type: ndcg_at_1000
319
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320
  - type: ndcg_at_3
321
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322
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323
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324
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326
  - type: precision_at_10
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  - type: precision_at_100
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330
  - type: precision_at_1000
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332
  - type: precision_at_3
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  - type: precision_at_5
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336
  - type: recall_at_1
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  - type: recall_at_10
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  - type: recall_at_100
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342
  - type: recall_at_1000
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  - type: recall_at_3
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346
  - type: recall_at_5
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348
  - task:
349
  type: Retrieval
350
  dataset:
 
355
  revision: None
356
  metrics:
357
  - type: map_at_1
358
+ value: 40.854
359
  - type: map_at_10
360
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361
  - type: map_at_100
362
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363
  - type: map_at_1000
364
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365
  - type: map_at_3
366
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  - type: map_at_5
368
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  - type: mrr_at_1
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  - type: mrr_at_10
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  - type: mrr_at_100
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  - type: mrr_at_1000
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  - type: mrr_at_3
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  - type: mrr_at_5
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  - type: ndcg_at_1
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383
  - type: ndcg_at_10
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385
  - type: ndcg_at_100
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387
  - type: ndcg_at_1000
388
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  - type: ndcg_at_3
390
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  - type: ndcg_at_5
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  - type: precision_at_1
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395
  - type: precision_at_10
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397
  - type: precision_at_100
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399
  - type: precision_at_1000
400
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401
  - type: precision_at_3
402
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403
  - type: precision_at_5
404
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405
  - type: recall_at_1
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  - type: recall_at_10
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  - type: recall_at_100
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411
  - type: recall_at_1000
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  - type: recall_at_3
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415
  - type: recall_at_5
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417
  - task:
418
  type: Retrieval
419
  dataset:
 
424
  revision: None
425
  metrics:
426
  - type: map_at_1
427
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428
  - type: map_at_10
429
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430
  - type: map_at_100
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432
  - type: map_at_1000
433
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  - type: map_at_3
435
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  - type: map_at_5
437
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  - type: mrr_at_3
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  - type: mrr_at_5
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  - type: ndcg_at_1
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  - type: ndcg_at_10
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  - type: ndcg_at_100
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  - type: ndcg_at_1000
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460
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  - type: precision_at_1
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  - type: precision_at_10
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  - type: precision_at_100
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  - type: precision_at_3
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  - type: precision_at_5
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  - type: recall_at_1
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  - type: recall_at_10
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  - type: recall_at_100
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  - type: recall_at_1000
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  - type: recall_at_3
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484
  - type: recall_at_5
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486
  - task:
487
  type: Retrieval
488
  dataset:
 
493
  revision: None
494
  metrics:
495
  - type: map_at_1
496
+ value: 16.634
497
  - type: map_at_10
498
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499
  - type: map_at_100
500
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501
  - type: map_at_1000
502
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  - type: map_at_3
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  - type: map_at_5
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  - type: mrr_at_100
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  - type: mrr_at_1000
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  - type: mrr_at_3
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  - type: mrr_at_5
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  - type: ndcg_at_1
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  - type: ndcg_at_10
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  - type: ndcg_at_100
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  - type: ndcg_at_1000
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531
  - type: precision_at_1
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  - type: precision_at_100
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  - type: precision_at_1000
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  - type: precision_at_3
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541
  - type: precision_at_5
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  - type: recall_at_1
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  - type: recall_at_10
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  - type: recall_at_100
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  - type: recall_at_1000
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  - type: recall_at_3
552
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553
  - type: recall_at_5
554
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555
  - task:
556
  type: Retrieval
557
  dataset:
 
562
  revision: None
563
  metrics:
564
  - type: map_at_1
565
+ value: 28.200999999999997
566
  - type: map_at_10
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  - type: mrr_at_1000
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  - type: mrr_at_3
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  - type: precision_at_5
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  - type: recall_at_10
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  - type: recall_at_100
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  - type: recall_at_1000
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  - type: recall_at_3
621
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622
  - type: recall_at_5
623
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624
  - task:
625
  type: Retrieval
626
  dataset:
 
631
  revision: None
632
  metrics:
633
  - type: map_at_1
634
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635
  - type: map_at_10
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  - type: recall_at_5
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  - task:
694
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695
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700
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701
  metrics:
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  - type: map_at_1
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  - type: recall_at_5
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  - task:
763
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  dataset:
 
769
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770
  metrics:
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  - type: map_at_1
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  - type: map_at_10
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  - type: recall_at_5
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  - task:
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  dataset:
 
838
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839
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  - type: map_at_1
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  - type: map_at_10
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  - type: map_at_100
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  - type: mrr_at_3
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  - task:
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  dataset:
 
907
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908
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  - type: map_at_1
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  - type: map_at_10
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  - type: mrr_at_1000
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  - type: mrr_at_3
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  - type: ndcg_at_10
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  - type: precision_at_10
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  - type: recall_at_100
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  - type: recall_at_5
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  dataset:
 
976
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977
  metrics:
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  - type: map_at_1
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  - type: map_at_10
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  - type: recall_at_5
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1039
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  dataset:
 
1045
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1046
  metrics:
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  - type: recall_at_5
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  dataset:
 
1114
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1115
  metrics:
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  - type: map_at_1
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1183
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1184
  metrics:
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  - type: map_at_1
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1252
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  - type: accuracy
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  - task:
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  dataset:
 
1265
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1266
  metrics:
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1334
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1335
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1403
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1472
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1556
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1608
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1630
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1643
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1781
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1941
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1962
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  - task:
1977
  type: STS
1978
  dataset:
 
1983
  revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
1984
  metrics:
1985
  - type: cos_sim_pearson
1986
+ value: 77.81236960157503
1987
  - type: cos_sim_spearman
1988
+ value: 79.38801416063187
1989
  - type: euclidean_pearson
1990
+ value: 79.35003045476847
1991
  - type: euclidean_spearman
1992
+ value: 79.38797289536578
1993
  - type: manhattan_pearson
1994
+ value: 79.33155563344724
1995
  - type: manhattan_spearman
1996
+ value: 79.3858955436803
1997
  - task:
1998
  type: STS
1999
  dataset:
 
2004
  revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
2005
  metrics:
2006
  - type: cos_sim_pearson
2007
+ value: 77.35604880089507
2008
  - type: cos_sim_spearman
2009
+ value: 78.17327332594571
2010
  - type: euclidean_pearson
2011
+ value: 77.30302038209295
2012
  - type: euclidean_spearman
2013
+ value: 78.17327332594571
2014
  - type: manhattan_pearson
2015
+ value: 77.31323781935417
2016
  - type: manhattan_spearman
2017
+ value: 78.20141256686921
2018
  - task:
2019
  type: STS
2020
  dataset:
 
2025
  revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
2026
  metrics:
2027
  - type: cos_sim_pearson
2028
+ value: 84.29348597583
2029
  - type: cos_sim_spearman
2030
+ value: 85.50877410088334
2031
  - type: euclidean_pearson
2032
+ value: 85.22367284169081
2033
  - type: euclidean_spearman
2034
+ value: 85.50877410088334
2035
  - type: manhattan_pearson
2036
+ value: 85.17979979737612
2037
  - type: manhattan_spearman
2038
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2039
  - task:
2040
  type: STS
2041
  dataset:
 
2046
  revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
2047
  metrics:
2048
  - type: cos_sim_pearson
2049
+ value: 83.16190794761513
2050
  - type: cos_sim_spearman
2051
+ value: 84.94610605287254
2052
  - type: euclidean_pearson
2053
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2054
  - type: euclidean_spearman
2055
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2056
  - type: manhattan_pearson
2057
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2058
  - type: manhattan_spearman
2059
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2060
  - task:
2061
  type: STS
2062
  dataset:
 
2067
  revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
2068
  metrics:
2069
  - type: cos_sim_pearson
2070
+ value: 85.3047190687711
2071
  - type: cos_sim_spearman
2072
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2073
  - type: euclidean_pearson
2074
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2075
  - type: euclidean_spearman
2076
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2077
  - type: manhattan_pearson
2078
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2079
  - type: manhattan_spearman
2080
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2081
  - task:
2082
  type: STS
2083
  dataset:
 
2088
  revision: eea2b4fe26a775864c896887d910b76a8098ad3f
2089
  metrics:
2090
  - type: cos_sim_pearson
2091
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2092
  - type: cos_sim_spearman
2093
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2094
  - type: euclidean_pearson
2095
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2096
  - type: euclidean_spearman
2097
+ value: 64.27626667878636
2098
  - type: manhattan_pearson
2099
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2100
  - type: manhattan_spearman
2101
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2102
  - task:
2103
  type: STS
2104
  dataset:
 
2109
  revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
2110
  metrics:
2111
  - type: cos_sim_pearson
2112
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2113
  - type: cos_sim_spearman
2114
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2115
  - type: euclidean_pearson
2116
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2117
  - type: euclidean_spearman
2118
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2119
  - type: manhattan_pearson
2120
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2121
  - type: manhattan_spearman
2122
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2123
  - task:
2124
  type: Reranking
2125
  dataset:
 
2130
  revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
2131
  metrics:
2132
  - type: map
2133
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2134
  - type: mrr
2135
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2136
  - task:
2137
  type: Retrieval
2138
  dataset:
 
2143
  revision: None
2144
  metrics:
2145
  - type: map_at_1
2146
+ value: 58.594
2147
  - type: map_at_10
2148
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2149
  - type: map_at_100
2150
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2151
  - type: map_at_1000
2152
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2153
  - type: map_at_3
2154
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2155
  - type: map_at_5
2156
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2157
  - type: mrr_at_1
2158
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2159
  - type: mrr_at_10
2160
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2161
  - type: mrr_at_100
2162
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2163
  - type: mrr_at_1000
2164
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2165
  - type: mrr_at_3
2166
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2167
  - type: mrr_at_5
2168
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2169
  - type: ndcg_at_1
2170
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2171
  - type: ndcg_at_10
2172
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2173
  - type: ndcg_at_100
2174
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2175
  - type: ndcg_at_1000
2176
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2177
  - type: ndcg_at_3
2178
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2179
  - type: ndcg_at_5
2180
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2181
  - type: precision_at_1
2182
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2183
  - type: precision_at_10
2184
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2185
  - type: precision_at_100
2186
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2187
  - type: precision_at_1000
2188
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2189
  - type: precision_at_3
2190
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2191
  - type: precision_at_5
2192
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2193
  - type: recall_at_1
2194
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2195
  - type: recall_at_10
2196
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2197
  - type: recall_at_100
2198
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2199
  - type: recall_at_1000
2200
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2201
  - type: recall_at_3
2202
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2203
  - type: recall_at_5
2204
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2205
  - task:
2206
  type: PairClassification
2207
  dataset:
 
2212
  revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
2213
  metrics:
2214
  - type: cos_sim_accuracy
2215
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2216
  - type: cos_sim_ap
2217
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2218
  - type: cos_sim_f1
2219
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2220
  - type: cos_sim_precision
2221
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2222
  - type: cos_sim_recall
2223
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2224
  - type: dot_accuracy
2225
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2226
  - type: dot_ap
2227
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2228
  - type: dot_f1
2229
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2230
  - type: dot_precision
2231
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2232
  - type: dot_recall
2233
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2234
  - type: euclidean_accuracy
2235
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2236
  - type: euclidean_ap
2237
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2238
  - type: euclidean_f1
2239
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2240
  - type: euclidean_precision
2241
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2242
  - type: euclidean_recall
2243
+ value: 88.9
2244
  - type: manhattan_accuracy
2245
+ value: 99.8
2246
  - type: manhattan_ap
2247
+ value: 94.84210829841739
2248
  - type: manhattan_f1
2249
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2250
  - type: manhattan_precision
2251
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2252
  - type: manhattan_recall
2253
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2254
  - type: max_accuracy
2255
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2256
  - type: max_ap
2257
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2258
  - type: max_f1
2259
+ value: 89.75265017667844
2260
  - task:
2261
  type: Clustering
2262
  dataset:
 
2267
  revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2268
  metrics:
2269
  - type: v_measure
2270
+ value: 63.18343792633894
2271
  - task:
2272
  type: Clustering
2273
  dataset:
 
2278
  revision: 815ca46b2622cec33ccafc3735d572c266efdb44
2279
  metrics:
2280
  - type: v_measure
2281
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2282
  - task:
2283
  type: Reranking
2284
  dataset:
 
2289
  revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
2290
  metrics:
2291
  - type: map
2292
+ value: 48.89100016028111
2293
  - type: mrr
2294
+ value: 49.607630931160344
2295
  - task:
2296
  type: Summarization
2297
  dataset:
 
2302
  revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
2303
  metrics:
2304
  - type: cos_sim_pearson
2305
+ value: 30.628145384101522
2306
  - type: cos_sim_spearman
2307
+ value: 31.275306930726675
2308
  - type: dot_pearson
2309
+ value: 30.62814883550051
2310
  - type: dot_spearman
2311
+ value: 31.275306930726675
2312
  - task:
2313
  type: Retrieval
2314
  dataset:
 
2319
  revision: None
2320
  metrics:
2321
  - type: map_at_1
2322
+ value: 0.26
2323
  - type: map_at_10
2324
+ value: 2.163
2325
  - type: map_at_100
2326
+ value: 12.29
2327
  - type: map_at_1000
2328
+ value: 29.221999999999998
2329
  - type: map_at_3
2330
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2331
  - type: map_at_5
2332
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2333
  - type: mrr_at_1
2334
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2335
  - type: mrr_at_10
2336
+ value: 98.0
2337
  - type: mrr_at_100
2338
+ value: 98.0
2339
  - type: mrr_at_1000
2340
+ value: 98.0
2341
  - type: mrr_at_3
2342
+ value: 98.0
2343
  - type: mrr_at_5
2344
+ value: 98.0
2345
  - type: ndcg_at_1
2346
+ value: 89.0
2347
  - type: ndcg_at_10
2348
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2349
  - type: ndcg_at_100
2350
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2351
  - type: ndcg_at_1000
2352
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2353
  - type: ndcg_at_3
2354
+ value: 87.87700000000001
2355
  - type: ndcg_at_5
2356
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2357
  - type: precision_at_1
2358
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2359
  - type: precision_at_10
2360
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2361
  - type: precision_at_100
2362
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2363
  - type: precision_at_1000
2364
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2365
  - type: precision_at_3
2366
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2367
  - type: precision_at_5
2368
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2369
  - type: recall_at_1
2370
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2371
  - type: recall_at_10
2372
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2373
  - type: recall_at_100
2374
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2375
  - type: recall_at_1000
2376
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2377
  - type: recall_at_3
2378
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2379
  - type: recall_at_5
2380
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2381
  - task:
2382
  type: Retrieval
2383
  dataset:
 
2388
  revision: None
2389
  metrics:
2390
  - type: map_at_1
2391
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2392
  - type: map_at_10
2393
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2394
  - type: map_at_100
2395
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2396
  - type: map_at_1000
2397
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2398
  - type: map_at_3
2399
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2400
  - type: map_at_5
2401
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2402
  - type: mrr_at_1
2403
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2404
  - type: mrr_at_10
2405
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2406
  - type: mrr_at_100
2407
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2408
  - type: mrr_at_1000
2409
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2410
  - type: mrr_at_3
2411
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2412
  - type: mrr_at_5
2413
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2414
  - type: ndcg_at_1
2415
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2416
  - type: ndcg_at_10
2417
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2418
  - type: ndcg_at_100
2419
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2420
  - type: ndcg_at_1000
2421
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2422
  - type: ndcg_at_3
2423
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2424
  - type: ndcg_at_5
2425
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2426
  - type: precision_at_1
2427
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2428
  - type: precision_at_10
2429
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2430
  - type: precision_at_100
2431
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2432
  - type: precision_at_1000
2433
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2434
  - type: precision_at_3
2435
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2436
  - type: precision_at_5
2437
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2438
  - type: recall_at_1
2439
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2440
  - type: recall_at_10
2441
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2442
  - type: recall_at_100
2443
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2444
  - type: recall_at_1000
2445
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2446
  - type: recall_at_3
2447
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2448
  - type: recall_at_5
2449
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2450
  - task:
2451
  type: Classification
2452
  dataset:
 
2457
  revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
2458
  metrics:
2459
  - type: accuracy
2460
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2461
  - type: ap
2462
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2463
  - type: f1
2464
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2465
  - task:
2466
  type: Classification
2467
  dataset:
 
2472
  revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
2473
  metrics:
2474
  - type: accuracy
2475
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2476
  - type: f1
2477
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  - task:
2479
  type: Clustering
2480
  dataset:
 
2485
  revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
2486
  metrics:
2487
  - type: v_measure
2488
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  - task:
2490
  type: PairClassification
2491
  dataset:
 
2496
  revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
2497
  metrics:
2498
  - type: cos_sim_accuracy
2499
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2500
  - type: cos_sim_ap
2501
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2503
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  - type: dot_recall
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  - type: euclidean_accuracy
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  - type: euclidean_f1
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  - type: euclidean_recall
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  - type: manhattan_accuracy
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2531
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2533
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  - type: manhattan_recall
2537
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  - type: max_accuracy
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2542
  - type: max_f1
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2544
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2545
  type: PairClassification
2546
  dataset:
 
2551
  revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
2552
  metrics:
2553
  - type: cos_sim_accuracy
2554
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  - type: cos_sim_ap
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  - type: cos_sim_f1
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  - type: euclidean_accuracy
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  - type: euclidean_f1
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  - type: manhattan_accuracy
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2599
  ---