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@@ -10,6 +10,9 @@ datasets:
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  - jinaai/negation-dataset
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  language: en
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  license: apache-2.0
 
 
 
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  model-index:
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  - name: jina-embedding-s-en-v1
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  results:
@@ -23,11 +26,11 @@ model-index:
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  revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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  metrics:
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  - type: accuracy
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- value: 64.58208955223881
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  - type: ap
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- value: 27.24359671025387
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  - type: f1
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- value: 58.201387941715495
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  - task:
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  type: Classification
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  dataset:
@@ -38,11 +41,11 @@ model-index:
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  revision: e2d317d38cd51312af73b3d32a06d1a08b442046
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  metrics:
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  - type: accuracy
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- value: 61.926550000000006
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  - type: ap
43
- value: 58.40954250092862
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  - type: f1
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- value: 59.921771639047904
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  - task:
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  type: Classification
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  dataset:
@@ -53,9 +56,9 @@ model-index:
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  revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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  metrics:
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  - type: accuracy
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- value: 28.499999999999996
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  - type: f1
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- value: 27.160929516206465
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  - task:
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  type: Retrieval
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  dataset:
@@ -66,65 +69,65 @@ 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: 22.262
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  - type: map_at_10
71
- value: 36.677
72
  - type: map_at_100
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- value: 37.839
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  - type: map_at_1000
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- value: 37.857
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  - type: map_at_3
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- value: 31.685999999999996
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  - type: map_at_5
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- value: 34.544999999999995
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  - type: mrr_at_1
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  value: 22.404
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  - type: mrr_at_10
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- value: 36.713
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  - type: mrr_at_100
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- value: 37.881
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  - type: mrr_at_1000
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- value: 37.899
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  - type: mrr_at_3
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- value: 31.709
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  - type: mrr_at_5
91
- value: 34.629
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  - type: ndcg_at_1
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- value: 22.262
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  - type: ndcg_at_10
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- value: 45.18
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  - type: ndcg_at_100
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- value: 50.4
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  - type: ndcg_at_1000
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- value: 50.841
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  - type: ndcg_at_3
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- value: 34.882000000000005
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  - type: ndcg_at_5
103
- value: 40.036
104
  - type: precision_at_1
105
- value: 22.262
106
  - type: precision_at_10
107
- value: 7.255000000000001
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  - type: precision_at_100
109
- value: 0.959
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  - type: precision_at_1000
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  value: 0.099
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  - type: precision_at_3
113
- value: 14.723
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  - type: precision_at_5
115
- value: 11.337
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  - type: recall_at_1
117
- value: 22.262
118
  - type: recall_at_10
119
- value: 72.54599999999999
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  - type: recall_at_100
121
- value: 95.946
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  - type: recall_at_1000
123
- value: 99.36
124
  - type: recall_at_3
125
- value: 44.168
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  - type: recall_at_5
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- value: 56.686
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  - task:
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  type: Clustering
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  dataset:
@@ -135,7 +138,7 @@ model-index:
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  revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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  metrics:
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  - type: v_measure
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- value: 34.97570470844357
139
  - task:
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  type: Clustering
141
  dataset:
@@ -146,7 +149,7 @@ model-index:
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  revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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  metrics:
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  - type: v_measure
149
- value: 24.372872291698265
150
  - task:
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  type: Reranking
152
  dataset:
@@ -157,9 +160,9 @@ model-index:
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  revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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  metrics:
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  - type: map
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- value: 60.58753030525579
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  - type: mrr
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- value: 75.03484588664644
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  - task:
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  type: STS
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  dataset:
@@ -170,17 +173,17 @@ model-index:
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  revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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  metrics:
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  - type: cos_sim_pearson
173
- value: 85.21378425036666
174
  - type: cos_sim_spearman
175
- value: 80.45665253651644
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  - type: euclidean_pearson
177
- value: 46.71436482437946
178
  - type: euclidean_spearman
179
- value: 45.13476336596072
180
  - type: manhattan_pearson
181
- value: 47.06449770246884
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  - type: manhattan_spearman
183
- value: 45.498627078529
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  - task:
185
  type: Classification
186
  dataset:
@@ -191,9 +194,9 @@ model-index:
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  revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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  metrics:
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  - type: accuracy
194
- value: 74.48701298701299
195
  - type: f1
196
- value: 73.30813366682357
197
  - task:
198
  type: Clustering
199
  dataset:
@@ -204,7 +207,7 @@ model-index:
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  revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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  metrics:
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  - type: v_measure
207
- value: 29.66289767477026
208
  - task:
209
  type: Clustering
210
  dataset:
@@ -215,7 +218,904 @@ model-index:
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  revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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  metrics:
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  - type: v_measure
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- value: 22.324367934720776
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - task:
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  type: Retrieval
221
  dataset:
@@ -226,65 +1126,65 @@ model-index:
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  revision: None
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  metrics:
228
  - type: map_at_1
229
- value: 6.524000000000001
230
  - type: map_at_10
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- value: 11.187
232
  - type: map_at_100
233
- value: 12.389999999999999
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  - type: map_at_1000
235
- value: 12.559000000000001
236
  - type: map_at_3
237
- value: 9.386
238
  - type: map_at_5
239
- value: 10.295
240
  - type: mrr_at_1
241
- value: 13.941
242
  - type: mrr_at_10
243
- value: 22.742
244
  - type: mrr_at_100
245
- value: 23.896
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  - type: mrr_at_1000
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- value: 23.965
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  - type: mrr_at_3
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- value: 19.881
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  - type: mrr_at_5
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- value: 21.555
252
  - type: ndcg_at_1
253
- value: 13.941
254
  - type: ndcg_at_10
255
- value: 16.619999999999997
256
  - type: ndcg_at_100
257
- value: 22.415
258
  - type: ndcg_at_1000
259
- value: 26.05
260
  - type: ndcg_at_3
261
- value: 13.148000000000001
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  - type: ndcg_at_5
263
- value: 14.433000000000002
264
  - type: precision_at_1
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- value: 13.941
266
  - type: precision_at_10
267
- value: 5.153
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  - type: precision_at_100
269
- value: 1.124
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  - type: precision_at_1000
271
- value: 0.178
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  - type: precision_at_3
273
- value: 9.685
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  - type: precision_at_5
275
- value: 7.582999999999999
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  - type: recall_at_1
277
- value: 6.524000000000001
278
  - type: recall_at_10
279
- value: 21.041999999999998
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  - type: recall_at_100
281
- value: 41.515
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  - type: recall_at_1000
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- value: 62.507999999999996
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  - type: recall_at_3
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- value: 12.549
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  - type: recall_at_5
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- value: 15.939999999999998
288
  - task:
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  type: Retrieval
290
  dataset:
@@ -295,65 +1195,65 @@ model-index:
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  revision: None
296
  metrics:
297
  - type: map_at_1
298
- value: 6.483
299
  - type: map_at_10
300
- value: 11.955
301
  - type: map_at_100
302
- value: 15.470999999999998
303
  - type: map_at_1000
304
- value: 16.308
305
  - type: map_at_3
306
- value: 9.292
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  - type: map_at_5
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- value: 10.459
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  - type: mrr_at_1
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- value: 50.74999999999999
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  - type: mrr_at_10
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- value: 58.743
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  - type: mrr_at_100
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- value: 59.41499999999999
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  - type: mrr_at_1000
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- value: 59.431999999999995
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  - type: mrr_at_3
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- value: 56.708000000000006
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  - type: mrr_at_5
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- value: 57.80800000000001
321
  - type: ndcg_at_1
322
- value: 39.0
323
  - type: ndcg_at_10
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- value: 26.721
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  - type: ndcg_at_100
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- value: 29.366999999999997
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  - type: ndcg_at_1000
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- value: 35.618
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  - type: ndcg_at_3
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- value: 31.244
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  - type: ndcg_at_5
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- value: 28.614
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  - type: precision_at_1
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- value: 50.74999999999999
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  - type: precision_at_10
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- value: 20.45
337
  - type: precision_at_100
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- value: 6.0600000000000005
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  - type: precision_at_1000
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- value: 1.346
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  - type: precision_at_3
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- value: 33.917
343
  - type: precision_at_5
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- value: 26.950000000000003
345
  - type: recall_at_1
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- value: 6.483
347
  - type: recall_at_10
348
- value: 16.215
349
  - type: recall_at_100
350
- value: 33.382
351
  - type: recall_at_1000
352
- value: 54.445
353
  - type: recall_at_3
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- value: 10.6
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  - type: recall_at_5
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- value: 12.889999999999999
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  - task:
358
  type: Classification
359
  dataset:
@@ -364,9 +1264,9 @@ model-index:
364
  revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
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  metrics:
366
  - type: accuracy
367
- value: 34.39
368
  - type: f1
369
- value: 31.334865751249474
370
  - task:
371
  type: Retrieval
372
  dataset:
@@ -377,65 +1277,65 @@ model-index:
377
  revision: None
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  metrics:
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  - type: map_at_1
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- value: 44.698
381
  - type: map_at_10
382
- value: 55.30500000000001
383
  - type: map_at_100
384
- value: 55.838
385
  - type: map_at_1000
386
- value: 55.87
387
  - type: map_at_3
388
- value: 52.884
389
  - type: map_at_5
390
- value: 54.352000000000004
391
  - type: mrr_at_1
392
- value: 48.32
393
  - type: mrr_at_10
394
- value: 59.39
395
  - type: mrr_at_100
396
- value: 59.89
397
  - type: mrr_at_1000
398
- value: 59.913000000000004
399
  - type: mrr_at_3
400
- value: 56.977999999999994
401
  - type: mrr_at_5
402
- value: 58.44200000000001
403
  - type: ndcg_at_1
404
- value: 48.32
405
  - type: ndcg_at_10
406
- value: 61.23800000000001
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  - type: ndcg_at_100
408
- value: 63.79
409
  - type: ndcg_at_1000
410
- value: 64.575
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  - type: ndcg_at_3
412
- value: 56.489999999999995
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  - type: ndcg_at_5
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- value: 59.016999999999996
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  - type: precision_at_1
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- value: 48.32
417
  - type: precision_at_10
418
- value: 8.288
419
  - type: precision_at_100
420
- value: 0.964
421
  - type: precision_at_1000
422
- value: 0.104
423
  - type: precision_at_3
424
- value: 22.867
425
  - type: precision_at_5
426
- value: 15.098
427
  - type: recall_at_1
428
- value: 44.698
429
  - type: recall_at_10
430
- value: 75.752
431
  - type: recall_at_100
432
- value: 87.402
433
  - type: recall_at_1000
434
- value: 93.316
435
  - type: recall_at_3
436
- value: 62.82600000000001
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  - type: recall_at_5
438
- value: 69.01899999999999
439
  - task:
440
  type: Retrieval
441
  dataset:
@@ -446,65 +1346,65 @@ model-index:
446
  revision: None
447
  metrics:
448
  - type: map_at_1
449
- value: 12.119
450
  - type: map_at_10
451
- value: 20.299
452
  - type: map_at_100
453
- value: 21.863
454
  - type: map_at_1000
455
- value: 22.064
456
  - type: map_at_3
457
- value: 17.485999999999997
458
  - type: map_at_5
459
- value: 19.148
460
  - type: mrr_at_1
461
- value: 24.383
462
  - type: mrr_at_10
463
- value: 33.074
464
  - type: mrr_at_100
465
- value: 34.03
466
  - type: mrr_at_1000
467
- value: 34.102
468
  - type: mrr_at_3
469
- value: 30.736
470
  - type: mrr_at_5
471
- value: 32.202
472
  - type: ndcg_at_1
473
- value: 24.383
474
  - type: ndcg_at_10
475
- value: 26.645999999999997
476
  - type: ndcg_at_100
477
- value: 33.348
478
  - type: ndcg_at_1000
479
- value: 37.294
480
  - type: ndcg_at_3
481
- value: 23.677
482
  - type: ndcg_at_5
483
- value: 24.935
484
  - type: precision_at_1
485
- value: 24.383
486
  - type: precision_at_10
487
- value: 7.654
488
  - type: precision_at_100
489
- value: 1.461
490
  - type: precision_at_1000
491
- value: 0.214
492
  - type: precision_at_3
493
- value: 16.101
494
  - type: precision_at_5
495
- value: 12.222
496
  - type: recall_at_1
497
- value: 12.119
498
  - type: recall_at_10
499
- value: 32.531
500
  - type: recall_at_100
501
- value: 58.028999999999996
502
  - type: recall_at_1000
503
- value: 82.513
504
  - type: recall_at_3
505
- value: 21.787
506
  - type: recall_at_5
507
- value: 27.229999999999997
508
  - task:
509
  type: Retrieval
510
  dataset:
@@ -515,65 +1415,65 @@ model-index:
515
  revision: None
516
  metrics:
517
  - type: map_at_1
518
- value: 26.057000000000002
519
  - type: map_at_10
520
- value: 34.892
521
  - type: map_at_100
522
- value: 35.687000000000005
523
  - type: map_at_1000
524
- value: 35.763
525
  - type: map_at_3
526
- value: 32.879000000000005
527
  - type: map_at_5
528
- value: 34.105000000000004
529
  - type: mrr_at_1
530
- value: 52.113
531
  - type: mrr_at_10
532
- value: 58.940000000000005
533
  - type: mrr_at_100
534
- value: 59.438
535
  - type: mrr_at_1000
536
- value: 59.473
537
  - type: mrr_at_3
538
- value: 57.299
539
  - type: mrr_at_5
540
- value: 58.353
541
  - type: ndcg_at_1
542
- value: 52.113
543
  - type: ndcg_at_10
544
- value: 43.105
545
  - type: ndcg_at_100
546
- value: 46.44
547
  - type: ndcg_at_1000
548
- value: 48.241
549
  - type: ndcg_at_3
550
- value: 39.566
551
  - type: ndcg_at_5
552
- value: 41.508
553
  - type: precision_at_1
554
- value: 52.113
555
  - type: precision_at_10
556
- value: 8.892999999999999
557
  - type: precision_at_100
558
- value: 1.1520000000000001
559
  - type: precision_at_1000
560
- value: 0.13899999999999998
561
  - type: precision_at_3
562
- value: 24.398
563
  - type: precision_at_5
564
- value: 16.181
565
  - type: recall_at_1
566
- value: 26.057000000000002
567
  - type: recall_at_10
568
- value: 44.463
569
  - type: recall_at_100
570
- value: 57.616
571
  - type: recall_at_1000
572
- value: 69.65599999999999
573
  - type: recall_at_3
574
- value: 36.597
575
  - type: recall_at_5
576
- value: 40.452
577
  - task:
578
  type: Classification
579
  dataset:
@@ -584,11 +1484,11 @@ model-index:
584
  revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
585
  metrics:
586
  - type: accuracy
587
- value: 58.268399999999986
588
  - type: ap
589
- value: 55.03852332714837
590
  - type: f1
591
- value: 57.23656436062262
592
  - task:
593
  type: Retrieval
594
  dataset:
@@ -599,65 +1499,65 @@ model-index:
599
  revision: None
600
  metrics:
601
  - type: map_at_1
602
- value: 14.273
603
  - type: map_at_10
604
- value: 23.953
605
  - type: map_at_100
606
- value: 25.207
607
  - type: map_at_1000
608
- value: 25.285999999999998
609
  - type: map_at_3
610
- value: 20.727
611
  - type: map_at_5
612
- value: 22.492
613
  - type: mrr_at_1
614
- value: 14.685
615
  - type: mrr_at_10
616
- value: 24.423000000000002
617
  - type: mrr_at_100
618
- value: 25.64
619
  - type: mrr_at_1000
620
- value: 25.713
621
  - type: mrr_at_3
622
- value: 21.213
623
  - type: mrr_at_5
624
- value: 22.979
625
  - type: ndcg_at_1
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- value: 14.685
627
  - type: ndcg_at_10
628
- value: 29.698
629
  - type: ndcg_at_100
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- value: 36.010999999999996
631
  - type: ndcg_at_1000
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- value: 38.102999999999994
633
  - type: ndcg_at_3
634
- value: 23.0
635
  - type: ndcg_at_5
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- value: 26.186
637
  - type: precision_at_1
638
- value: 14.685
639
  - type: precision_at_10
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- value: 4.954
641
  - type: precision_at_100
642
- value: 0.815
643
  - type: precision_at_1000
644
- value: 0.099
645
  - type: precision_at_3
646
- value: 10.038
647
  - type: precision_at_5
648
- value: 7.636
649
  - type: recall_at_1
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- value: 14.273
651
  - type: recall_at_10
652
- value: 47.559000000000005
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  - type: recall_at_100
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- value: 77.375
655
  - type: recall_at_1000
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- value: 93.616
657
  - type: recall_at_3
658
- value: 29.110999999999997
659
  - type: recall_at_5
660
- value: 36.825
661
  - task:
662
  type: Classification
663
  dataset:
@@ -668,9 +1568,9 @@ model-index:
668
  revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
669
  metrics:
670
  - type: accuracy
671
- value: 89.85636114911081
672
  - type: f1
673
- value: 89.65403786390279
674
  - task:
675
  type: Classification
676
  dataset:
@@ -681,9 +1581,9 @@ model-index:
681
  revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
682
  metrics:
683
  - type: accuracy
684
- value: 59.03784769721842
685
  - type: f1
686
- value: 42.57604111096128
687
  - task:
688
  type: Classification
689
  dataset:
@@ -694,9 +1594,9 @@ model-index:
694
  revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
695
  metrics:
696
  - type: accuracy
697
- value: 65.00336247478144
698
  - type: f1
699
- value: 63.12578076844032
700
  - task:
701
  type: Classification
702
  dataset:
@@ -707,9 +1607,9 @@ model-index:
707
  revision: 7d571f92784cd94a019292a1f45445077d0ef634
708
  metrics:
709
  - type: accuracy
710
- value: 72.14862138533962
711
  - type: f1
712
- value: 71.91174720216141
713
  - task:
714
  type: Clustering
715
  dataset:
@@ -720,7 +1620,7 @@ model-index:
720
  revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
721
  metrics:
722
  - type: v_measure
723
- value: 28.259326082067094
724
  - task:
725
  type: Clustering
726
  dataset:
@@ -731,7 +1631,7 @@ model-index:
731
  revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
732
  metrics:
733
  - type: v_measure
734
- value: 23.874256261395775
735
  - task:
736
  type: Reranking
737
  dataset:
@@ -742,9 +1642,9 @@ model-index:
742
  revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
743
  metrics:
744
  - type: map
745
- value: 29.251614283788385
746
  - type: mrr
747
- value: 29.9695581475798
748
  - task:
749
  type: Retrieval
750
  dataset:
@@ -755,65 +1655,65 @@ model-index:
755
  revision: None
756
  metrics:
757
  - type: map_at_1
758
- value: 3.9309999999999996
759
  - type: map_at_10
760
- value: 8.472
761
  - type: map_at_100
762
- value: 10.461
763
  - type: map_at_1000
764
- value: 11.588
765
  - type: map_at_3
766
- value: 6.343999999999999
767
  - type: map_at_5
768
- value: 7.379
769
  - type: mrr_at_1
770
- value: 35.913000000000004
771
  - type: mrr_at_10
772
- value: 43.91
773
  - type: mrr_at_100
774
- value: 44.519999999999996
775
  - type: mrr_at_1000
776
- value: 44.59
777
  - type: mrr_at_3
778
- value: 41.589
779
  - type: mrr_at_5
780
- value: 42.626
781
  - type: ndcg_at_1
782
- value: 34.52
783
  - type: ndcg_at_10
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- value: 25.128
785
  - type: ndcg_at_100
786
- value: 22.917
787
  - type: ndcg_at_1000
788
- value: 31.64
789
  - type: ndcg_at_3
790
- value: 29.866999999999997
791
  - type: ndcg_at_5
792
- value: 27.494000000000003
793
  - type: precision_at_1
794
- value: 35.913000000000004
795
  - type: precision_at_10
796
- value: 18.607000000000003
797
  - type: precision_at_100
798
- value: 6.006
799
  - type: precision_at_1000
800
- value: 1.814
801
  - type: precision_at_3
802
- value: 28.277
803
  - type: precision_at_5
804
- value: 23.777
805
  - type: recall_at_1
806
- value: 3.9309999999999996
807
  - type: recall_at_10
808
- value: 11.684
809
  - type: recall_at_100
810
- value: 24.212
811
  - type: recall_at_1000
812
- value: 55.36
813
  - type: recall_at_3
814
- value: 7.329
815
  - type: recall_at_5
816
- value: 9.059000000000001
817
  - task:
818
  type: Retrieval
819
  dataset:
@@ -824,65 +1724,65 @@ model-index:
824
  revision: None
825
  metrics:
826
  - type: map_at_1
827
- value: 19.03
828
  - type: map_at_10
829
- value: 30.990000000000002
830
  - type: map_at_100
831
- value: 32.211
832
  - type: map_at_1000
833
- value: 32.267
834
  - type: map_at_3
835
- value: 26.833000000000002
836
  - type: map_at_5
837
- value: 29.128
838
  - type: mrr_at_1
839
- value: 21.523999999999997
840
  - type: mrr_at_10
841
- value: 33.085
842
  - type: mrr_at_100
843
- value: 34.096
844
  - type: mrr_at_1000
845
- value: 34.139
846
  - type: mrr_at_3
847
- value: 29.354999999999997
848
  - type: mrr_at_5
849
- value: 31.441999999999997
850
  - type: ndcg_at_1
851
- value: 21.495
852
  - type: ndcg_at_10
853
- value: 37.971
854
  - type: ndcg_at_100
855
- value: 43.492999999999995
856
  - type: ndcg_at_1000
857
- value: 44.925
858
  - type: ndcg_at_3
859
- value: 29.808
860
  - type: ndcg_at_5
861
- value: 33.748
862
  - type: precision_at_1
863
- value: 21.495
864
  - type: precision_at_10
865
- value: 6.819
866
  - type: precision_at_100
867
- value: 0.991
868
  - type: precision_at_1000
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- value: 0.11299999999999999
870
  - type: precision_at_3
871
- value: 13.886000000000001
872
  - type: precision_at_5
873
- value: 10.574
874
  - type: recall_at_1
875
- value: 19.03
876
  - type: recall_at_10
877
- value: 57.493
878
  - type: recall_at_100
879
- value: 82.03200000000001
880
  - type: recall_at_1000
881
- value: 92.879
882
  - type: recall_at_3
883
- value: 35.899
884
  - type: recall_at_5
885
- value: 45.092
886
  - task:
887
  type: Retrieval
888
  dataset:
@@ -893,65 +1793,65 @@ model-index:
893
  revision: None
894
  metrics:
895
  - type: map_at_1
896
- value: 67.97
897
  - type: map_at_10
898
- value: 81.478
899
  - type: map_at_100
900
- value: 82.147
901
  - type: map_at_1000
902
- value: 82.172
903
  - type: map_at_3
904
- value: 78.456
905
  - type: map_at_5
906
- value: 80.337
907
  - type: mrr_at_1
908
- value: 78.24
909
  - type: mrr_at_10
910
- value: 84.941
911
  - type: mrr_at_100
912
- value: 85.08099999999999
913
  - type: mrr_at_1000
914
- value: 85.083
915
  - type: mrr_at_3
916
- value: 83.743
917
  - type: mrr_at_5
918
- value: 84.553
919
  - type: ndcg_at_1
920
- value: 78.24
921
  - type: ndcg_at_10
922
- value: 85.61999999999999
923
  - type: ndcg_at_100
924
- value: 87.113
925
  - type: ndcg_at_1000
926
- value: 87.318
927
  - type: ndcg_at_3
928
- value: 82.403
929
  - type: ndcg_at_5
930
- value: 84.15700000000001
931
  - type: precision_at_1
932
- value: 78.24
933
  - type: precision_at_10
934
- value: 12.979
935
  - type: precision_at_100
936
- value: 1.503
937
  - type: precision_at_1000
938
  value: 0.156
939
  - type: precision_at_3
940
- value: 35.9
941
  - type: precision_at_5
942
- value: 23.704
943
  - type: recall_at_1
944
- value: 67.97
945
  - type: recall_at_10
946
- value: 93.563
947
  - type: recall_at_100
948
- value: 98.834
949
  - type: recall_at_1000
950
- value: 99.901
951
  - type: recall_at_3
952
- value: 84.319
953
  - type: recall_at_5
954
- value: 89.227
955
  - task:
956
  type: Clustering
957
  dataset:
@@ -962,7 +1862,7 @@ model-index:
962
  revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
963
  metrics:
964
  - type: v_measure
965
- value: 35.853649010160694
966
  - task:
967
  type: Clustering
968
  dataset:
@@ -973,7 +1873,7 @@ model-index:
973
  revision: 282350215ef01743dc01b456c7f5241fa8937f16
974
  metrics:
975
  - type: v_measure
976
- value: 47.270443152349415
977
  - task:
978
  type: Retrieval
979
  dataset:
@@ -984,65 +1884,65 @@ model-index:
984
  revision: None
985
  metrics:
986
  - type: map_at_1
987
- value: 3.803
988
  - type: map_at_10
989
- value: 8.790000000000001
990
  - type: map_at_100
991
- value: 10.313
992
  - type: map_at_1000
993
- value: 10.562000000000001
994
  - type: map_at_3
995
- value: 6.483
996
  - type: map_at_5
997
- value: 7.591
998
  - type: mrr_at_1
999
- value: 18.7
1000
  - type: mrr_at_10
1001
- value: 27.349
1002
  - type: mrr_at_100
1003
- value: 28.474
1004
  - type: mrr_at_1000
1005
- value: 28.544999999999998
1006
  - type: mrr_at_3
1007
- value: 24.567
1008
  - type: mrr_at_5
1009
- value: 26.172
1010
  - type: ndcg_at_1
1011
- value: 18.7
1012
  - type: ndcg_at_10
1013
- value: 15.155
1014
  - type: ndcg_at_100
1015
- value: 21.63
1016
  - type: ndcg_at_1000
1017
- value: 26.595999999999997
1018
  - type: ndcg_at_3
1019
- value: 14.706
1020
  - type: ndcg_at_5
1021
- value: 12.681999999999999
1022
  - type: precision_at_1
1023
- value: 18.7
1024
  - type: precision_at_10
1025
- value: 7.6899999999999995
1026
  - type: precision_at_100
1027
- value: 1.7080000000000002
1028
  - type: precision_at_1000
1029
- value: 0.291
1030
  - type: precision_at_3
1031
- value: 13.567000000000002
1032
  - type: precision_at_5
1033
- value: 10.9
1034
  - type: recall_at_1
1035
- value: 3.803
1036
  - type: recall_at_10
1037
- value: 15.607
1038
  - type: recall_at_100
1039
- value: 34.717999999999996
1040
  - type: recall_at_1000
1041
- value: 59.150000000000006
1042
  - type: recall_at_3
1043
- value: 8.258000000000001
1044
  - type: recall_at_5
1045
- value: 11.063
1046
  - task:
1047
  type: STS
1048
  dataset:
@@ -1053,17 +1953,17 @@ model-index:
1053
  revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
1054
  metrics:
1055
  - type: cos_sim_pearson
1056
- value: 81.05755556071047
1057
  - type: cos_sim_spearman
1058
- value: 72.44408263672771
1059
  - type: euclidean_pearson
1060
- value: 71.65314814604668
1061
  - type: euclidean_spearman
1062
- value: 65.1833695751109
1063
  - type: manhattan_pearson
1064
- value: 71.81874115177355
1065
  - type: manhattan_spearman
1066
- value: 65.45940792270201
1067
  - task:
1068
  type: STS
1069
  dataset:
@@ -1074,17 +1974,17 @@ model-index:
1074
  revision: a0d554a64d88156834ff5ae9920b964011b16384
1075
  metrics:
1076
  - type: cos_sim_pearson
1077
- value: 81.75836272926722
1078
  - type: cos_sim_spearman
1079
- value: 73.63905703662927
1080
  - type: euclidean_pearson
1081
- value: 67.58539517215293
1082
  - type: euclidean_spearman
1083
- value: 58.88440181413321
1084
  - type: manhattan_pearson
1085
- value: 66.56872028174024
1086
  - type: manhattan_spearman
1087
- value: 58.48195528793699
1088
  - task:
1089
  type: STS
1090
  dataset:
@@ -1095,17 +1995,17 @@ model-index:
1095
  revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
1096
  metrics:
1097
  - type: cos_sim_pearson
1098
- value: 76.58680032464127
1099
  - type: cos_sim_spearman
1100
- value: 78.03760988363273
1101
  - type: euclidean_pearson
1102
- value: 68.23192805876019
1103
  - type: euclidean_spearman
1104
- value: 69.21753515532978
1105
  - type: manhattan_pearson
1106
- value: 68.07876685109447
1107
  - type: manhattan_spearman
1108
- value: 69.08026107263751
1109
  - task:
1110
  type: STS
1111
  dataset:
@@ -1116,17 +2016,17 @@ model-index:
1116
  revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
1117
  metrics:
1118
  - type: cos_sim_pearson
1119
- value: 78.72357139489792
1120
  - type: cos_sim_spearman
1121
- value: 74.53681843472086
1122
  - type: euclidean_pearson
1123
- value: 66.73161230236408
1124
  - type: euclidean_spearman
1125
- value: 63.81392957525887
1126
  - type: manhattan_pearson
1127
- value: 66.33322201893088
1128
  - type: manhattan_spearman
1129
- value: 63.55218357111819
1130
  - task:
1131
  type: STS
1132
  dataset:
@@ -1137,17 +2037,17 @@ model-index:
1137
  revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
1138
  metrics:
1139
  - type: cos_sim_pearson
1140
- value: 82.62456549757793
1141
  - type: cos_sim_spearman
1142
- value: 83.89301877076606
1143
  - type: euclidean_pearson
1144
- value: 58.128415035981554
1145
  - type: euclidean_spearman
1146
- value: 58.47993973876889
1147
  - type: manhattan_pearson
1148
- value: 58.37634990795807
1149
  - type: manhattan_spearman
1150
- value: 58.89541748905865
1151
  - task:
1152
  type: STS
1153
  dataset:
@@ -1158,17 +2058,17 @@ model-index:
1158
  revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
1159
  metrics:
1160
  - type: cos_sim_pearson
1161
- value: 76.79731685895317
1162
  - type: cos_sim_spearman
1163
- value: 79.04240201103201
1164
  - type: euclidean_pearson
1165
- value: 64.26869512572189
1166
  - type: euclidean_spearman
1167
- value: 65.09728500847595
1168
  - type: manhattan_pearson
1169
- value: 64.2772185991136
1170
  - type: manhattan_spearman
1171
- value: 65.18852760227209
1172
  - task:
1173
  type: STS
1174
  dataset:
@@ -1179,17 +2079,17 @@ model-index:
1179
  revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
1180
  metrics:
1181
  - type: cos_sim_pearson
1182
- value: 86.30962737077412
1183
  - type: cos_sim_spearman
1184
- value: 86.77386963770132
1185
  - type: euclidean_pearson
1186
- value: 70.0534100015362
1187
  - type: euclidean_spearman
1188
- value: 68.17903243639661
1189
  - type: manhattan_pearson
1190
- value: 70.03048392176451
1191
  - type: manhattan_spearman
1192
- value: 68.19594588464386
1193
  - task:
1194
  type: STS
1195
  dataset:
@@ -1200,17 +2100,17 @@ model-index:
1200
  revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
1201
  metrics:
1202
  - type: cos_sim_pearson
1203
- value: 64.77791754851359
1204
  - type: cos_sim_spearman
1205
- value: 64.28210927783513
1206
  - type: euclidean_pearson
1207
- value: 36.337603238543956
1208
  - type: euclidean_spearman
1209
- value: 52.70617012481411
1210
  - type: manhattan_pearson
1211
- value: 35.49141141164909
1212
  - type: manhattan_spearman
1213
- value: 52.084744319382835
1214
  - task:
1215
  type: STS
1216
  dataset:
@@ -1221,17 +2121,17 @@ model-index:
1221
  revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
1222
  metrics:
1223
  - type: cos_sim_pearson
1224
- value: 79.741579322503
1225
  - type: cos_sim_spearman
1226
- value: 78.83687709048151
1227
  - type: euclidean_pearson
1228
- value: 66.59151974274772
1229
  - type: euclidean_spearman
1230
- value: 63.76907648545863
1231
  - type: manhattan_pearson
1232
- value: 66.91555116739791
1233
  - type: manhattan_spearman
1234
- value: 64.2024945118848
1235
  - task:
1236
  type: Reranking
1237
  dataset:
@@ -1242,9 +2142,9 @@ model-index:
1242
  revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
1243
  metrics:
1244
  - type: map
1245
- value: 74.31125049985503
1246
  - type: mrr
1247
- value: 91.5911222038673
1248
  - task:
1249
  type: Retrieval
1250
  dataset:
@@ -1255,65 +2155,65 @@ model-index:
1255
  revision: None
1256
  metrics:
1257
  - type: map_at_1
1258
- value: 39.983000000000004
1259
  - type: map_at_10
1260
- value: 48.79
1261
  - type: map_at_100
1262
- value: 49.419999999999995
1263
  - type: map_at_1000
1264
- value: 49.495
1265
  - type: map_at_3
1266
- value: 46.394000000000005
1267
  - type: map_at_5
1268
- value: 47.772999999999996
1269
  - type: mrr_at_1
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  - type: mrr_at_10
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- value: 51.088
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  - type: mrr_at_100
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- value: 51.498999999999995
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  - type: mrr_at_1000
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  - type: mrr_at_3
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- value: 49.111
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  - type: mrr_at_5
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- value: 50.278
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  - type: ndcg_at_1
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  - type: ndcg_at_100
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  - type: ndcg_at_1000
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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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- value: 19.444
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  - type: precision_at_5
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  - type: recall_at_1
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- value: 39.983000000000004
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  - type: recall_at_10
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- value: 66.333
1309
  - type: recall_at_100
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- value: 80.256
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  - type: recall_at_1000
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- value: 95.667
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  - type: recall_at_3
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- value: 53.449999999999996
1315
  - type: recall_at_5
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- value: 58.989000000000004
1317
  - task:
1318
  type: PairClassification
1319
  dataset:
@@ -1324,51 +2224,51 @@ model-index:
1324
  revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
1325
  metrics:
1326
  - type: cos_sim_accuracy
1327
- value: 99.6930693069307
1328
  - type: cos_sim_ap
1329
- value: 90.94265768188356
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  - type: cos_sim_f1
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- value: 84.15792103948026
1332
  - type: cos_sim_precision
1333
- value: 84.11588411588411
1334
  - type: cos_sim_recall
1335
- value: 84.2
1336
  - type: dot_accuracy
1337
- value: 99.12178217821783
1338
  - type: dot_ap
1339
- value: 42.77306613711772
1340
  - type: dot_f1
1341
- value: 44.23963133640553
1342
  - type: dot_precision
1343
- value: 38.0677721701514
1344
  - type: dot_recall
1345
- value: 52.800000000000004
1346
  - type: euclidean_accuracy
1347
- value: 99.55049504950495
1348
  - type: euclidean_ap
1349
- value: 78.83886818298362
1350
  - type: euclidean_f1
1351
- value: 74.54645409565696
1352
  - type: euclidean_precision
1353
- value: 82.78388278388277
1354
  - type: euclidean_recall
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- value: 67.80000000000001
1356
  - type: manhattan_accuracy
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- value: 99.54257425742574
1358
  - type: manhattan_ap
1359
- value: 77.98046807031727
1360
  - type: manhattan_f1
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- value: 74.18822234452395
1362
  - type: manhattan_precision
1363
- value: 82.4969400244798
1364
  - type: manhattan_recall
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- value: 67.4
1366
  - type: max_accuracy
1367
- value: 99.6930693069307
1368
  - type: max_ap
1369
- value: 90.94265768188356
1370
  - type: max_f1
1371
- value: 84.15792103948026
1372
  - task:
1373
  type: Clustering
1374
  dataset:
@@ -1379,7 +2279,7 @@ model-index:
1379
  revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
1380
  metrics:
1381
  - type: v_measure
1382
- value: 47.81120799399627
1383
  - task:
1384
  type: Clustering
1385
  dataset:
@@ -1390,7 +2290,7 @@ model-index:
1390
  revision: 815ca46b2622cec33ccafc3735d572c266efdb44
1391
  metrics:
1392
  - type: v_measure
1393
- value: 29.82642033698617
1394
  - task:
1395
  type: Reranking
1396
  dataset:
@@ -1401,9 +2301,9 @@ model-index:
1401
  revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
1402
  metrics:
1403
  - type: map
1404
- value: 47.861728758923675
1405
  - type: mrr
1406
- value: 48.53185213479331
1407
  - task:
1408
  type: Summarization
1409
  dataset:
@@ -1414,13 +2314,13 @@ model-index:
1414
  revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
1415
  metrics:
1416
  - type: cos_sim_pearson
1417
- value: 30.09237795780992
1418
  - type: cos_sim_spearman
1419
- value: 28.95547545518808
1420
  - type: dot_pearson
1421
- value: 19.99986205111785
1422
  - type: dot_spearman
1423
- value: 21.34033389331779
1424
  - task:
1425
  type: Retrieval
1426
  dataset:
@@ -1431,65 +2331,65 @@ model-index:
1431
  revision: None
1432
  metrics:
1433
  - type: map_at_1
1434
- value: 0.169
1435
  - type: map_at_10
1436
- value: 1.077
1437
  - type: map_at_100
1438
- value: 4.9750000000000005
1439
  - type: map_at_1000
1440
- value: 11.802
1441
  - type: map_at_3
1442
- value: 0.48700000000000004
1443
  - type: map_at_5
1444
- value: 0.679
1445
  - type: mrr_at_1
1446
- value: 62.0
1447
  - type: mrr_at_10
1448
- value: 76.25
1449
  - type: mrr_at_100
1450
- value: 76.337
1451
  - type: mrr_at_1000
1452
- value: 76.337
1453
  - type: mrr_at_3
1454
- value: 74.333
1455
  - type: mrr_at_5
1456
- value: 75.333
1457
  - type: ndcg_at_1
1458
- value: 56.00000000000001
1459
  - type: ndcg_at_10
1460
- value: 50.631
1461
  - type: ndcg_at_100
1462
- value: 36.39
1463
  - type: ndcg_at_1000
1464
- value: 32.879000000000005
1465
  - type: ndcg_at_3
1466
- value: 59.961
1467
  - type: ndcg_at_5
1468
- value: 55.913999999999994
1469
  - type: precision_at_1
1470
- value: 62.0
1471
  - type: precision_at_10
1472
- value: 53.0
1473
  - type: precision_at_100
1474
- value: 37.2
1475
  - type: precision_at_1000
1476
- value: 14.804
1477
  - type: precision_at_3
1478
- value: 67.333
1479
  - type: precision_at_5
1480
- value: 60.4
1481
  - type: recall_at_1
1482
- value: 0.169
1483
  - type: recall_at_10
1484
- value: 1.324
1485
  - type: recall_at_100
1486
- value: 8.352
1487
  - type: recall_at_1000
1488
- value: 31.041999999999998
1489
  - type: recall_at_3
1490
- value: 0.532
1491
  - type: recall_at_5
1492
- value: 0.777
1493
  - task:
1494
  type: Retrieval
1495
  dataset:
@@ -1500,65 +2400,65 @@ model-index:
1500
  revision: None
1501
  metrics:
1502
  - type: map_at_1
1503
- value: 2.018
1504
  - type: map_at_10
1505
- value: 8.036
1506
  - type: map_at_100
1507
- value: 12.814
1508
  - type: map_at_1000
1509
- value: 14.204
1510
  - type: map_at_3
1511
- value: 3.9759999999999995
1512
  - type: map_at_5
1513
- value: 5.585
1514
  - type: mrr_at_1
1515
- value: 24.490000000000002
1516
  - type: mrr_at_10
1517
- value: 38.903
1518
  - type: mrr_at_100
1519
- value: 39.893
1520
  - type: mrr_at_1000
1521
- value: 39.895
1522
  - type: mrr_at_3
1523
- value: 35.034
1524
  - type: mrr_at_5
1525
- value: 37.789
1526
  - type: ndcg_at_1
1527
- value: 21.429000000000002
1528
  - type: ndcg_at_10
1529
- value: 20.082
1530
  - type: ndcg_at_100
1531
- value: 30.299
1532
  - type: ndcg_at_1000
1533
- value: 42.323
1534
  - type: ndcg_at_3
1535
- value: 19.826
1536
  - type: ndcg_at_5
1537
- value: 19.861
1538
  - type: precision_at_1
1539
- value: 24.490000000000002
1540
  - type: precision_at_10
1541
- value: 18.776
1542
  - type: precision_at_100
1543
- value: 6.551
1544
  - type: precision_at_1000
1545
- value: 1.455
1546
  - type: precision_at_3
1547
- value: 21.088
1548
  - type: precision_at_5
1549
- value: 21.633
1550
  - type: recall_at_1
1551
- value: 2.018
1552
  - type: recall_at_10
1553
- value: 14.094999999999999
1554
  - type: recall_at_100
1555
- value: 40.482
1556
  - type: recall_at_1000
1557
- value: 78.214
1558
  - type: recall_at_3
1559
- value: 4.884
1560
  - type: recall_at_5
1561
- value: 8.203000000000001
1562
  - task:
1563
  type: Classification
1564
  dataset:
@@ -1569,11 +2469,11 @@ model-index:
1569
  revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
1570
  metrics:
1571
  - type: accuracy
1572
- value: 59.69140000000001
1573
  - type: ap
1574
- value: 10.299275820958274
1575
  - type: f1
1576
- value: 45.697311005218154
1577
  - task:
1578
  type: Classification
1579
  dataset:
@@ -1584,9 +2484,9 @@ model-index:
1584
  revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
1585
  metrics:
1586
  - type: accuracy
1587
- value: 53.542727787209955
1588
  - type: f1
1589
- value: 53.59495510018717
1590
  - task:
1591
  type: Clustering
1592
  dataset:
@@ -1597,7 +2497,7 @@ model-index:
1597
  revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
1598
  metrics:
1599
  - type: v_measure
1600
- value: 32.405659957745534
1601
  - task:
1602
  type: PairClassification
1603
  dataset:
@@ -1608,51 +2508,51 @@ model-index:
1608
  revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
1609
  metrics:
1610
  - type: cos_sim_accuracy
1611
- value: 82.34487691482386
1612
  - type: cos_sim_ap
1613
- value: 61.4880638625752
1614
  - type: cos_sim_f1
1615
- value: 59.350775193798455
1616
  - type: cos_sim_precision
1617
- value: 54.858934169278996
1618
  - type: cos_sim_recall
1619
- value: 64.64379947229551
1620
  - type: dot_accuracy
1621
- value: 77.68373368301842
1622
  - type: dot_ap
1623
- value: 36.846940578266626
1624
  - type: dot_f1
1625
- value: 42.67407473787974
1626
  - type: dot_precision
1627
- value: 32.311032704573215
1628
  - type: dot_recall
1629
- value: 62.82321899736147
1630
  - type: euclidean_accuracy
1631
- value: 80.40770101925256
1632
  - type: euclidean_ap
1633
- value: 53.51906185864526
1634
  - type: euclidean_f1
1635
- value: 53.24030024315466
1636
  - type: euclidean_precision
1637
- value: 44.41700476274475
1638
  - type: euclidean_recall
1639
- value: 66.43799472295514
1640
  - type: manhattan_accuracy
1641
- value: 80.31829290099542
1642
  - type: manhattan_ap
1643
- value: 53.67183195163967
1644
  - type: manhattan_f1
1645
- value: 53.28358208955224
1646
  - type: manhattan_precision
1647
- value: 44.70483005366726
1648
  - type: manhattan_recall
1649
- value: 65.93667546174143
1650
  - type: max_accuracy
1651
- value: 82.34487691482386
1652
  - type: max_ap
1653
- value: 61.4880638625752
1654
  - type: max_f1
1655
- value: 59.350775193798455
1656
  - task:
1657
  type: PairClassification
1658
  dataset:
@@ -1663,52 +2563,51 @@ model-index:
1663
  revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
1664
  metrics:
1665
  - type: cos_sim_accuracy
1666
- value: 87.71684713005007
1667
  - type: cos_sim_ap
1668
- value: 82.85441942604702
1669
  - type: cos_sim_f1
1670
- value: 75.69942543843179
1671
  - type: cos_sim_precision
1672
- value: 73.88754490140019
1673
  - type: cos_sim_recall
1674
- value: 77.60240221743148
1675
  - type: dot_accuracy
1676
- value: 82.23696976753212
1677
  - type: dot_ap
1678
- value: 68.47562727147806
1679
  - type: dot_f1
1680
- value: 64.99698249849123
1681
  - type: dot_precision
1682
- value: 57.566219265946074
1683
  - type: dot_recall
1684
- value: 74.63042808746535
1685
  - type: euclidean_accuracy
1686
- value: 81.52481856638336
1687
  - type: euclidean_ap
1688
- value: 65.96678666430529
1689
  - type: euclidean_f1
1690
- value: 59.14671467146715
1691
  - type: euclidean_precision
1692
- value: 55.54879285859201
1693
  - type: euclidean_recall
1694
- value: 63.24299353249153
1695
  - type: manhattan_accuracy
1696
- value: 81.56750882912253
1697
  - type: manhattan_ap
1698
- value: 66.07646774834106
1699
  - type: manhattan_f1
1700
- value: 59.161485036907756
1701
  - type: manhattan_precision
1702
- value: 56.05319368841728
1703
  - type: manhattan_recall
1704
- value: 62.634739759778256
1705
  - type: max_accuracy
1706
- value: 87.71684713005007
1707
  - type: max_ap
1708
- value: 82.85441942604702
1709
  - type: max_f1
1710
- value: 75.69942543843179
1711
- ---
1712
  ---
1713
 
1714
  <br><br>
 
10
  - jinaai/negation-dataset
11
  language: en
12
  license: apache-2.0
13
+ ---
14
+ tags:
15
+ - mteb
16
  model-index:
17
  - name: jina-embedding-s-en-v1
18
  results:
 
26
  revision: e8379541af4e31359cca9fbcf4b00f2671dba205
27
  metrics:
28
  - type: accuracy
29
+ value: 64.82089552238806
30
  - type: ap
31
+ value: 27.100981946230778
32
  - type: f1
33
+ value: 58.3354886367184
34
  - task:
35
  type: Classification
36
  dataset:
 
41
  revision: e2d317d38cd51312af73b3d32a06d1a08b442046
42
  metrics:
43
  - type: accuracy
44
+ value: 64.282775
45
  - type: ap
46
+ value: 60.350688924943796
47
  - type: f1
48
+ value: 62.06346948494396
49
  - task:
50
  type: Classification
51
  dataset:
 
56
  revision: 1399c76144fd37290681b995c656ef9b2e06e26d
57
  metrics:
58
  - type: accuracy
59
+ value: 30.623999999999995
60
  - type: f1
61
+ value: 29.427789186742153
62
  - task:
63
  type: Retrieval
64
  dataset:
 
69
  revision: None
70
  metrics:
71
  - type: map_at_1
72
+ value: 22.119
73
  - type: map_at_10
74
+ value: 35.609
75
  - type: map_at_100
76
+ value: 36.935
77
  - type: map_at_1000
78
+ value: 36.957
79
  - type: map_at_3
80
+ value: 31.046000000000003
81
  - type: map_at_5
82
+ value: 33.574
83
  - type: mrr_at_1
84
  value: 22.404
85
  - type: mrr_at_10
86
+ value: 35.695
87
  - type: mrr_at_100
88
+ value: 37.021
89
  - type: mrr_at_1000
90
+ value: 37.043
91
  - type: mrr_at_3
92
+ value: 31.093
93
  - type: mrr_at_5
94
+ value: 33.635999999999996
95
  - type: ndcg_at_1
96
+ value: 22.119
97
  - type: ndcg_at_10
98
+ value: 43.566
99
  - type: ndcg_at_100
100
+ value: 49.370000000000005
101
  - type: ndcg_at_1000
102
+ value: 49.901
103
  - type: ndcg_at_3
104
+ value: 34.06
105
  - type: ndcg_at_5
106
+ value: 38.653999999999996
107
  - type: precision_at_1
108
+ value: 22.119
109
  - type: precision_at_10
110
+ value: 6.92
111
  - type: precision_at_100
112
+ value: 0.95
113
  - type: precision_at_1000
114
  value: 0.099
115
  - type: precision_at_3
116
+ value: 14.272000000000002
117
  - type: precision_at_5
118
+ value: 10.811
119
  - type: recall_at_1
120
+ value: 22.119
121
  - type: recall_at_10
122
+ value: 69.203
123
  - type: recall_at_100
124
+ value: 95.021
125
  - type: recall_at_1000
126
+ value: 99.075
127
  - type: recall_at_3
128
+ value: 42.817
129
  - type: recall_at_5
130
+ value: 54.054
131
  - task:
132
  type: Clustering
133
  dataset:
 
138
  revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
139
  metrics:
140
  - type: v_measure
141
+ value: 34.1740289109719
142
  - task:
143
  type: Clustering
144
  dataset:
 
149
  revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
150
  metrics:
151
  - type: v_measure
152
+ value: 23.985251383455463
153
  - task:
154
  type: Reranking
155
  dataset:
 
160
  revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
161
  metrics:
162
  - type: map
163
+ value: 60.24873612289029
164
  - type: mrr
165
+ value: 74.65692740623489
166
  - task:
167
  type: STS
168
  dataset:
 
173
  revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
174
  metrics:
175
  - type: cos_sim_pearson
176
+ value: 86.22415390332444
177
  - type: cos_sim_spearman
178
+ value: 82.9591191954711
179
  - type: euclidean_pearson
180
+ value: 44.096317524324945
181
  - type: euclidean_spearman
182
+ value: 42.95218351391625
183
  - type: manhattan_pearson
184
+ value: 44.07766490545065
185
  - type: manhattan_spearman
186
+ value: 42.78350497166606
187
  - task:
188
  type: Classification
189
  dataset:
 
194
  revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
195
  metrics:
196
  - type: accuracy
197
+ value: 74.64285714285714
198
  - type: f1
199
+ value: 73.53680835577447
200
  - task:
201
  type: Clustering
202
  dataset:
 
207
  revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
208
  metrics:
209
  - type: v_measure
210
+ value: 28.512813238490164
211
  - task:
212
  type: Clustering
213
  dataset:
 
218
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  - type: v_measure
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+ type: Retrieval
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+ dataset:
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+ type: BeIR/cqadupstack
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+ name: MTEB CQADupstackAndroidRetrieval
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+ config: default
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+ split: test
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+ revision: None
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231
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294
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+ name: MTEB CQADupstackEnglishRetrieval
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300
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846
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1126
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1195
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1264
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1277
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1346
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1347
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1415
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1484
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1500
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1568
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1607
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1620
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1631
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1642
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1655
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1724
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1793
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1794
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1862
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1873
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1884
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1885
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1947
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1948
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1953
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1954
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1955
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1968
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1974
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1980
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1988
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1989
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1995
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1996
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1998
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1999
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2003
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2006
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2007
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2010
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2016
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2018
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2020
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2037
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2079
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2100
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2121
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2136
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2142
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  - type: map
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  - task:
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  type: Retrieval
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  dataset:
 
2155
  revision: None
2156
  metrics:
2157
  - type: map_at_1
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  - type: map_at_10
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  - type: recall_at_5
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2218
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2219
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2224
  revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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  - type: cos_sim_accuracy
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  - type: euclidean_accuracy
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2250
  - type: euclidean_f1
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  - type: euclidean_recall
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  - type: manhattan_accuracy
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  - type: manhattan_f1
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  - type: manhattan_recall
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  - type: max_f1
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  - task:
2273
  type: Clustering
2274
  dataset:
 
2279
  revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2280
  metrics:
2281
  - type: v_measure
2282
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  - task:
2284
  type: Clustering
2285
  dataset:
 
2290
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2291
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2292
  - type: v_measure
2293
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  - task:
2295
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2296
  dataset:
 
2301
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2302
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2303
  - type: map
2304
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  - type: mrr
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  - task:
2308
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2309
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2314
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2315
  metrics:
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  - type: cos_sim_pearson
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  - type: cos_sim_spearman
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  - task:
2325
  type: Retrieval
2326
  dataset:
 
2331
  revision: None
2332
  metrics:
2333
  - type: map_at_1
2334
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2335
  - type: map_at_10
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  - type: map_at_1000
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2341
  - type: map_at_3
2342
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  - type: map_at_5
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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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2359
  - type: ndcg_at_10
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  - type: ndcg_at_1000
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2369
  - type: precision_at_1
2370
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2371
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2372
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  - type: precision_at_100
2374
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  - type: precision_at_1000
2376
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  - type: precision_at_3
2378
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2379
  - type: precision_at_5
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  - type: recall_at_1
2382
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  - type: recall_at_10
2384
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  - type: recall_at_100
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  - type: recall_at_1000
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  - type: recall_at_3
2390
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2391
  - type: recall_at_5
2392
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2393
  - task:
2394
  type: Retrieval
2395
  dataset:
 
2400
  revision: None
2401
  metrics:
2402
  - type: map_at_1
2403
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2404
  - type: map_at_10
2405
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  - type: map_at_1000
2409
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  - type: map_at_3
2411
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  - type: map_at_5
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  - type: mrr_at_1
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  - type: mrr_at_10
2417
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  - type: mrr_at_3
2423
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2424
  - type: mrr_at_5
2425
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2428
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2431
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2432
  - type: ndcg_at_1000
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2436
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2438
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2440
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2441
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2442
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  - type: precision_at_1000
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2447
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2448
  - type: precision_at_5
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  - type: recall_at_1
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2452
  - type: recall_at_10
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2454
  - type: recall_at_100
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  - type: recall_at_1000
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2458
  - type: recall_at_3
2459
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2460
  - type: recall_at_5
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2462
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2463
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2464
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2469
  revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
2470
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  - type: accuracy
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2479
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2484
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2485
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2486
  - type: accuracy
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2492
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2497
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2498
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2499
  - type: v_measure
2500
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2502
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2503
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2508
  revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
2509
  metrics:
2510
  - type: cos_sim_accuracy
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2557
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2558
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2563
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2564
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2611
  ---
2612
 
2613
  <br><br>