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@@ -11,7 +11,7 @@ datasets:
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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-b-en-v1
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  results:
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  - task:
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  type: Classification
@@ -23,11 +23,11 @@ model-index:
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  revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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  metrics:
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  - type: accuracy
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- value: 66.58208955223881
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  - type: ap
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- value: 28.455148149555754
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  - type: f1
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- value: 59.973775371110385
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  - task:
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  type: Classification
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  dataset:
@@ -38,11 +38,11 @@ model-index:
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  revision: e2d317d38cd51312af73b3d32a06d1a08b442046
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  metrics:
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  - type: accuracy
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- value: 65.09505
42
  - type: ap
43
- value: 61.387245649832614
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  - type: f1
45
- value: 62.96831291412068
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  - task:
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  type: Classification
48
  dataset:
@@ -53,9 +53,9 @@ model-index:
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  revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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  metrics:
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  - type: accuracy
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- value: 30.633999999999993
57
  - type: f1
58
- value: 29.638828990078647
59
  - task:
60
  type: Retrieval
61
  dataset:
@@ -66,65 +66,65 @@ 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: 25.889
70
  - type: map_at_10
71
- value: 40.604
72
  - type: map_at_100
73
- value: 41.697
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  - type: map_at_1000
75
- value: 41.705999999999996
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  - type: map_at_3
77
- value: 35.217999999999996
78
  - type: map_at_5
79
- value: 38.326
80
  - type: mrr_at_1
81
- value: 26.245
82
  - type: mrr_at_10
83
- value: 40.736
84
  - type: mrr_at_100
85
- value: 41.829
86
  - type: mrr_at_1000
87
- value: 41.837999999999994
88
  - type: mrr_at_3
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- value: 35.349000000000004
90
  - type: mrr_at_5
91
- value: 38.425
92
  - type: ndcg_at_1
93
- value: 25.889
94
  - type: ndcg_at_10
95
- value: 49.347
96
  - type: ndcg_at_100
97
- value: 53.956
98
  - type: ndcg_at_1000
99
- value: 54.2
100
  - type: ndcg_at_3
101
- value: 38.282
102
  - type: ndcg_at_5
103
- value: 43.895
104
  - type: precision_at_1
105
- value: 25.889
106
  - type: precision_at_10
107
- value: 7.752000000000001
108
  - type: precision_at_100
109
- value: 0.976
110
  - type: precision_at_1000
111
- value: 0.1
112
  - type: precision_at_3
113
- value: 15.717999999999998
114
  - type: precision_at_5
115
- value: 12.162
116
  - type: recall_at_1
117
- value: 25.889
118
  - type: recall_at_10
119
- value: 77.525
120
  - type: recall_at_100
121
- value: 97.58200000000001
122
  - type: recall_at_1000
123
- value: 99.502
124
  - type: recall_at_3
125
- value: 47.155
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  - type: recall_at_5
127
- value: 60.81100000000001
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  - task:
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  type: Clustering
130
  dataset:
@@ -135,7 +135,7 @@ model-index:
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  revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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  metrics:
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  - type: v_measure
138
- value: 39.2179862062943
139
  - task:
140
  type: Clustering
141
  dataset:
@@ -146,7 +146,7 @@ model-index:
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  revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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  metrics:
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  - type: v_measure
149
- value: 29.87826673088078
150
  - task:
151
  type: Reranking
152
  dataset:
@@ -157,9 +157,9 @@ model-index:
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  revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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  metrics:
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  - type: map
160
- value: 62.72401299412015
161
  - type: mrr
162
- value: 75.45167743921206
163
  - task:
164
  type: STS
165
  dataset:
@@ -170,17 +170,17 @@ model-index:
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  revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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  metrics:
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  - type: cos_sim_pearson
173
- value: 85.96510928112639
174
  - type: cos_sim_spearman
175
- value: 82.64224450538681
176
  - type: euclidean_pearson
177
- value: 52.03458755006108
178
  - type: euclidean_spearman
179
- value: 52.83192670285616
180
  - type: manhattan_pearson
181
- value: 52.14561955040935
182
  - type: manhattan_spearman
183
- value: 52.9584356095438
184
  - task:
185
  type: Classification
186
  dataset:
@@ -191,9 +191,9 @@ model-index:
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  revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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  metrics:
193
  - type: accuracy
194
- value: 84.11363636363636
195
  - type: f1
196
- value: 84.01098114920124
197
  - task:
198
  type: Clustering
199
  dataset:
@@ -204,7 +204,7 @@ model-index:
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  revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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  metrics:
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  - type: v_measure
207
- value: 32.991971466919026
208
  - task:
209
  type: Clustering
210
  dataset:
@@ -215,7 +215,904 @@ model-index:
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  revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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  metrics:
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  - type: v_measure
218
- value: 26.48807922559519
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
219
  - task:
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  type: Retrieval
221
  dataset:
@@ -226,65 +1123,65 @@ model-index:
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  revision: None
227
  metrics:
228
  - type: map_at_1
229
- value: 8.014000000000001
230
  - type: map_at_10
231
- value: 14.149999999999999
232
  - type: map_at_100
233
- value: 15.539
234
  - type: map_at_1000
235
- value: 15.711
236
  - type: map_at_3
237
- value: 11.913
238
  - type: map_at_5
239
- value: 12.982
240
  - type: mrr_at_1
241
- value: 18.046
242
  - type: mrr_at_10
243
- value: 28.224
244
  - type: mrr_at_100
245
- value: 29.293000000000003
246
  - type: mrr_at_1000
247
- value: 29.348999999999997
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  - type: mrr_at_3
249
- value: 25.179000000000002
250
  - type: mrr_at_5
251
- value: 26.827
252
  - type: ndcg_at_1
253
- value: 18.046
254
  - type: ndcg_at_10
255
- value: 20.784
256
  - type: ndcg_at_100
257
- value: 26.939999999999998
258
  - type: ndcg_at_1000
259
- value: 30.453999999999997
260
  - type: ndcg_at_3
261
- value: 16.694
262
  - type: ndcg_at_5
263
- value: 18.049
264
  - type: precision_at_1
265
- value: 18.046
266
  - type: precision_at_10
267
- value: 6.5280000000000005
268
  - type: precision_at_100
269
- value: 1.2959999999999998
270
  - type: precision_at_1000
271
- value: 0.19499999999999998
272
  - type: precision_at_3
273
- value: 12.465
274
  - type: precision_at_5
275
- value: 9.511
276
  - type: recall_at_1
277
- value: 8.014000000000001
278
  - type: recall_at_10
279
- value: 26.021
280
  - type: recall_at_100
281
- value: 47.692
282
  - type: recall_at_1000
283
- value: 67.63
284
  - type: recall_at_3
285
- value: 16.122
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  - type: recall_at_5
287
- value: 19.817
288
  - task:
289
  type: Retrieval
290
  dataset:
@@ -295,65 +1192,65 @@ model-index:
295
  revision: None
296
  metrics:
297
  - type: map_at_1
298
- value: 7.396
299
  - type: map_at_10
300
- value: 14.543000000000001
301
  - type: map_at_100
302
- value: 19.235
303
  - type: map_at_1000
304
- value: 20.384
305
  - type: map_at_3
306
- value: 10.886
307
  - type: map_at_5
308
- value: 12.61
309
  - type: mrr_at_1
310
- value: 55.50000000000001
311
  - type: mrr_at_10
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- value: 63.731
313
  - type: mrr_at_100
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- value: 64.256
315
  - type: mrr_at_1000
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- value: 64.27000000000001
317
  - type: mrr_at_3
318
- value: 61.583
319
  - type: mrr_at_5
320
- value: 62.92100000000001
321
  - type: ndcg_at_1
322
- value: 43.375
323
  - type: ndcg_at_10
324
- value: 31.352000000000004
325
  - type: ndcg_at_100
326
- value: 34.717999999999996
327
  - type: ndcg_at_1000
328
- value: 41.959
329
  - type: ndcg_at_3
330
- value: 35.319
331
  - type: ndcg_at_5
332
- value: 33.222
333
  - type: precision_at_1
334
- value: 55.50000000000001
335
  - type: precision_at_10
336
- value: 24.15
337
  - type: precision_at_100
338
- value: 7.42
339
  - type: precision_at_1000
340
- value: 1.66
341
  - type: precision_at_3
342
- value: 37.917
343
  - type: precision_at_5
344
- value: 31.900000000000002
345
  - type: recall_at_1
346
- value: 7.396
347
  - type: recall_at_10
348
- value: 19.686999999999998
349
  - type: recall_at_100
350
- value: 40.465
351
  - type: recall_at_1000
352
- value: 63.79899999999999
353
  - type: recall_at_3
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- value: 12.124
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  - type: recall_at_5
356
- value: 15.28
357
  - task:
358
  type: Classification
359
  dataset:
@@ -364,9 +1261,9 @@ model-index:
364
  revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
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  metrics:
366
  - type: accuracy
367
- value: 41.33
368
  - type: f1
369
- value: 37.682972473685496
370
  - task:
371
  type: Retrieval
372
  dataset:
@@ -377,65 +1274,65 @@ model-index:
377
  revision: None
378
  metrics:
379
  - type: map_at_1
380
- value: 49.019
381
  - type: map_at_10
382
- value: 61.219
383
  - type: map_at_100
384
- value: 61.753
385
  - type: map_at_1000
386
- value: 61.771
387
  - type: map_at_3
388
- value: 58.952000000000005
389
  - type: map_at_5
390
- value: 60.239
391
  - type: mrr_at_1
392
- value: 53
393
  - type: mrr_at_10
394
- value: 65.678
395
  - type: mrr_at_100
396
- value: 66.147
397
  - type: mrr_at_1000
398
- value: 66.155
399
  - type: mrr_at_3
400
- value: 63.495999999999995
401
  - type: mrr_at_5
402
- value: 64.75800000000001
403
  - type: ndcg_at_1
404
- value: 53
405
  - type: ndcg_at_10
406
- value: 67.587
407
  - type: ndcg_at_100
408
- value: 69.877
409
  - type: ndcg_at_1000
410
- value: 70.25200000000001
411
  - type: ndcg_at_3
412
- value: 63.174
413
  - type: ndcg_at_5
414
- value: 65.351
415
  - type: precision_at_1
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- value: 53
417
  - type: precision_at_10
418
- value: 9.067
419
  - type: precision_at_100
420
- value: 1.026
421
  - type: precision_at_1000
422
- value: 0.107
423
  - type: precision_at_3
424
- value: 25.728
425
  - type: precision_at_5
426
- value: 16.637
427
  - type: recall_at_1
428
- value: 49.019
429
  - type: recall_at_10
430
- value: 82.962
431
  - type: recall_at_100
432
- value: 92.917
433
  - type: recall_at_1000
434
- value: 95.511
435
  - type: recall_at_3
436
- value: 70.838
437
  - type: recall_at_5
438
- value: 76.201
439
  - task:
440
  type: Retrieval
441
  dataset:
@@ -446,65 +1343,65 @@ model-index:
446
  revision: None
447
  metrics:
448
  - type: map_at_1
449
- value: 16.714000000000002
450
  - type: map_at_10
451
- value: 28.041
452
  - type: map_at_100
453
- value: 29.75
454
  - type: map_at_1000
455
- value: 29.944
456
  - type: map_at_3
457
- value: 23.884
458
  - type: map_at_5
459
- value: 26.468000000000004
460
  - type: mrr_at_1
461
- value: 33.796
462
  - type: mrr_at_10
463
- value: 42.757
464
  - type: mrr_at_100
465
- value: 43.705
466
  - type: mrr_at_1000
467
- value: 43.751
468
  - type: mrr_at_3
469
- value: 40.406
470
  - type: mrr_at_5
471
- value: 41.88
472
  - type: ndcg_at_1
473
- value: 33.796
474
  - type: ndcg_at_10
475
- value: 35.482
476
  - type: ndcg_at_100
477
- value: 42.44
478
  - type: ndcg_at_1000
479
- value: 45.903
480
  - type: ndcg_at_3
481
- value: 31.922
482
  - type: ndcg_at_5
483
- value: 33.516
484
  - type: precision_at_1
485
- value: 33.796
486
  - type: precision_at_10
487
- value: 10.108
488
  - type: precision_at_100
489
- value: 1.735
490
  - type: precision_at_1000
491
- value: 0.23500000000000001
492
  - type: precision_at_3
493
- value: 21.759
494
  - type: precision_at_5
495
- value: 16.605
496
  - type: recall_at_1
497
- value: 16.714000000000002
498
  - type: recall_at_10
499
- value: 42.38
500
  - type: recall_at_100
501
- value: 68.84700000000001
502
  - type: recall_at_1000
503
- value: 90.036
504
  - type: recall_at_3
505
- value: 28.776000000000003
506
  - type: recall_at_5
507
- value: 35.606
508
  - task:
509
  type: Retrieval
510
  dataset:
@@ -515,65 +1412,65 @@ model-index:
515
  revision: None
516
  metrics:
517
  - type: map_at_1
518
- value: 29.534
519
  - type: map_at_10
520
- value: 40.857
521
  - type: map_at_100
522
- value: 41.715999999999994
523
  - type: map_at_1000
524
- value: 41.795
525
  - type: map_at_3
526
- value: 38.415
527
  - type: map_at_5
528
- value: 39.833
529
  - type: mrr_at_1
530
- value: 59.068
531
  - type: mrr_at_10
532
- value: 66.034
533
  - type: mrr_at_100
534
- value: 66.479
535
  - type: mrr_at_1000
536
- value: 66.50399999999999
537
  - type: mrr_at_3
538
- value: 64.38000000000001
539
  - type: mrr_at_5
540
- value: 65.40599999999999
541
  - type: ndcg_at_1
542
- value: 59.068
543
  - type: ndcg_at_10
544
- value: 49.638
545
  - type: ndcg_at_100
546
- value: 53.093999999999994
547
  - type: ndcg_at_1000
548
- value: 54.813
549
  - type: ndcg_at_3
550
- value: 45.537
551
  - type: ndcg_at_5
552
- value: 47.671
553
  - type: precision_at_1
554
- value: 59.068
555
  - type: precision_at_10
556
- value: 10.313
557
  - type: precision_at_100
558
- value: 1.304
559
  - type: precision_at_1000
560
- value: 0.153
561
  - type: precision_at_3
562
- value: 28.278
563
  - type: precision_at_5
564
- value: 18.658
565
  - type: recall_at_1
566
- value: 29.534
567
  - type: recall_at_10
568
- value: 51.56699999999999
569
  - type: recall_at_100
570
- value: 65.199
571
  - type: recall_at_1000
572
- value: 76.678
573
  - type: recall_at_3
574
- value: 42.417
575
  - type: recall_at_5
576
- value: 46.644000000000005
577
  - task:
578
  type: Classification
579
  dataset:
@@ -584,11 +1481,11 @@ model-index:
584
  revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
585
  metrics:
586
  - type: accuracy
587
- value: 65.74719999999999
588
  - type: ap
589
- value: 60.57322504947344
590
  - type: f1
591
- value: 65.37875006542282
592
  - task:
593
  type: Retrieval
594
  dataset:
@@ -599,65 +1496,65 @@ model-index:
599
  revision: None
600
  metrics:
601
  - type: map_at_1
602
- value: 15.695999999999998
603
  - type: map_at_10
604
- value: 26.661
605
  - type: map_at_100
606
- value: 27.982000000000003
607
  - type: map_at_1000
608
- value: 28.049000000000003
609
  - type: map_at_3
610
- value: 23.057
611
  - type: map_at_5
612
- value: 25.079
613
  - type: mrr_at_1
614
- value: 16.16
615
  - type: mrr_at_10
616
- value: 27.150999999999996
617
  - type: mrr_at_100
618
- value: 28.423
619
  - type: mrr_at_1000
620
- value: 28.483999999999998
621
  - type: mrr_at_3
622
- value: 23.577
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  - type: mrr_at_5
624
- value: 25.585
625
  - type: ndcg_at_1
626
- value: 16.16
627
  - type: ndcg_at_10
628
- value: 33.017
629
  - type: ndcg_at_100
630
- value: 39.582
631
  - type: ndcg_at_1000
632
- value: 41.28
633
  - type: ndcg_at_3
634
- value: 25.607000000000003
635
  - type: ndcg_at_5
636
- value: 29.214000000000002
637
  - type: precision_at_1
638
- value: 16.16
639
  - type: precision_at_10
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- value: 5.506
641
  - type: precision_at_100
642
- value: 0.882
643
  - type: precision_at_1000
644
- value: 0.10300000000000001
645
  - type: precision_at_3
646
- value: 11.199
647
  - type: precision_at_5
648
- value: 8.55
649
  - type: recall_at_1
650
- value: 15.695999999999998
651
  - type: recall_at_10
652
- value: 52.736000000000004
653
  - type: recall_at_100
654
- value: 83.523
655
  - type: recall_at_1000
656
- value: 96.588
657
  - type: recall_at_3
658
- value: 32.484
659
  - type: recall_at_5
660
- value: 41.117
661
  - task:
662
  type: Classification
663
  dataset:
@@ -668,9 +1565,9 @@ model-index:
668
  revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
669
  metrics:
670
  - type: accuracy
671
- value: 91.71682626538988
672
  - type: f1
673
- value: 91.60647677401211
674
  - task:
675
  type: Classification
676
  dataset:
@@ -681,9 +1578,9 @@ model-index:
681
  revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
682
  metrics:
683
  - type: accuracy
684
- value: 74.94756041951665
685
  - type: f1
686
- value: 57.26936028487369
687
  - task:
688
  type: Classification
689
  dataset:
@@ -694,9 +1591,9 @@ model-index:
694
  revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
695
  metrics:
696
  - type: accuracy
697
- value: 71.43241425689307
698
  - type: f1
699
- value: 68.80370629448252
700
  - task:
701
  type: Classification
702
  dataset:
@@ -707,9 +1604,9 @@ model-index:
707
  revision: 7d571f92784cd94a019292a1f45445077d0ef634
708
  metrics:
709
  - type: accuracy
710
- value: 77.04774714189642
711
  - type: f1
712
- value: 76.93545888412446
713
  - task:
714
  type: Clustering
715
  dataset:
@@ -720,7 +1617,7 @@ model-index:
720
  revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
721
  metrics:
722
  - type: v_measure
723
- value: 30.009784989313765
724
  - task:
725
  type: Clustering
726
  dataset:
@@ -731,7 +1628,7 @@ model-index:
731
  revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
732
  metrics:
733
  - type: v_measure
734
- value: 25.568442512328872
735
  - task:
736
  type: Reranking
737
  dataset:
@@ -742,9 +1639,9 @@ model-index:
742
  revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
743
  metrics:
744
  - type: map
745
- value: 31.013959341949697
746
  - type: mrr
747
- value: 31.998487836684575
748
  - task:
749
  type: Retrieval
750
  dataset:
@@ -755,65 +1652,65 @@ model-index:
755
  revision: None
756
  metrics:
757
  - type: map_at_1
758
- value: 4.316
759
  - type: map_at_10
760
- value: 10.287
761
  - type: map_at_100
762
- value: 12.817
763
  - type: map_at_1000
764
- value: 14.141
765
  - type: map_at_3
766
- value: 7.728
767
  - type: map_at_5
768
- value: 8.876000000000001
769
  - type: mrr_at_1
770
- value: 39.628
771
  - type: mrr_at_10
772
- value: 48.423
773
  - type: mrr_at_100
774
- value: 49.153999999999996
775
  - type: mrr_at_1000
776
- value: 49.198
777
  - type: mrr_at_3
778
- value: 45.666000000000004
779
  - type: mrr_at_5
780
- value: 47.477000000000004
781
  - type: ndcg_at_1
782
- value: 36.533
783
  - type: ndcg_at_10
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- value: 29.304000000000002
785
  - type: ndcg_at_100
786
- value: 27.078000000000003
787
  - type: ndcg_at_1000
788
- value: 36.221
789
  - type: ndcg_at_3
790
- value: 33.256
791
  - type: ndcg_at_5
792
- value: 31.465
793
  - type: precision_at_1
794
- value: 39.009
795
  - type: precision_at_10
796
- value: 22.043
797
  - type: precision_at_100
798
- value: 7.115
799
  - type: precision_at_1000
800
- value: 1.991
801
  - type: precision_at_3
802
- value: 31.476
803
  - type: precision_at_5
804
- value: 27.616000000000003
805
  - type: recall_at_1
806
- value: 4.316
807
  - type: recall_at_10
808
- value: 14.507
809
  - type: recall_at_100
810
- value: 28.847
811
  - type: recall_at_1000
812
- value: 61.758
813
  - type: recall_at_3
814
- value: 8.753
815
  - type: recall_at_5
816
- value: 11.153
817
  - task:
818
  type: Retrieval
819
  dataset:
@@ -824,65 +1721,65 @@ model-index:
824
  revision: None
825
  metrics:
826
  - type: map_at_1
827
- value: 22.374
828
  - type: map_at_10
829
- value: 36.095
830
  - type: map_at_100
831
- value: 37.413999999999994
832
  - type: map_at_1000
833
- value: 37.46
834
  - type: map_at_3
835
- value: 31.711
836
  - type: map_at_5
837
- value: 34.294999999999995
838
  - type: mrr_at_1
839
- value: 25.406000000000002
840
  - type: mrr_at_10
841
- value: 38.424
842
  - type: mrr_at_100
843
- value: 39.456
844
  - type: mrr_at_1000
845
- value: 39.488
846
  - type: mrr_at_3
847
- value: 34.613
848
  - type: mrr_at_5
849
- value: 36.864999999999995
850
  - type: ndcg_at_1
851
- value: 25.406000000000002
852
  - type: ndcg_at_10
853
- value: 43.614000000000004
854
  - type: ndcg_at_100
855
- value: 49.166
856
  - type: ndcg_at_1000
857
- value: 50.212
858
  - type: ndcg_at_3
859
- value: 35.221999999999994
860
  - type: ndcg_at_5
861
- value: 39.571
862
  - type: precision_at_1
863
- value: 25.406000000000002
864
  - type: precision_at_10
865
- value: 7.654
866
  - type: precision_at_100
867
- value: 1.0699999999999998
868
  - type: precision_at_1000
869
- value: 0.117
870
  - type: precision_at_3
871
- value: 16.425
872
  - type: precision_at_5
873
- value: 12.352
874
  - type: recall_at_1
875
- value: 22.374
876
  - type: recall_at_10
877
- value: 64.337
878
  - type: recall_at_100
879
- value: 88.374
880
  - type: recall_at_1000
881
- value: 96.101
882
  - type: recall_at_3
883
- value: 42.5
884
  - type: recall_at_5
885
- value: 52.556000000000004
886
  - task:
887
  type: Retrieval
888
  dataset:
@@ -893,65 +1790,65 @@ model-index:
893
  revision: None
894
  metrics:
895
  - type: map_at_1
896
- value: 69.301
897
  - type: map_at_10
898
- value: 83.128
899
  - type: map_at_100
900
- value: 83.779
901
  - type: map_at_1000
902
- value: 83.798
903
  - type: map_at_3
904
- value: 80.11399999999999
905
  - type: map_at_5
906
- value: 82.00699999999999
907
  - type: mrr_at_1
908
- value: 79.81
909
  - type: mrr_at_10
910
- value: 86.28
911
  - type: mrr_at_100
912
- value: 86.399
913
  - type: mrr_at_1000
914
- value: 86.401
915
  - type: mrr_at_3
916
- value: 85.26
917
  - type: mrr_at_5
918
- value: 85.93499999999999
919
  - type: ndcg_at_1
920
- value: 79.80000000000001
921
  - type: ndcg_at_10
922
- value: 87.06700000000001
923
  - type: ndcg_at_100
924
- value: 88.41799999999999
925
  - type: ndcg_at_1000
926
- value: 88.554
927
  - type: ndcg_at_3
928
- value: 84.052
929
  - type: ndcg_at_5
930
- value: 85.711
931
  - type: precision_at_1
932
- value: 79.80000000000001
933
  - type: precision_at_10
934
- value: 13.224
935
  - type: precision_at_100
936
- value: 1.5230000000000001
937
  - type: precision_at_1000
938
- value: 0.157
939
  - type: precision_at_3
940
- value: 36.723
941
  - type: precision_at_5
942
- value: 24.192
943
  - type: recall_at_1
944
- value: 69.301
945
  - type: recall_at_10
946
- value: 94.589
947
  - type: recall_at_100
948
- value: 99.29299999999999
949
  - type: recall_at_1000
950
- value: 99.965
951
  - type: recall_at_3
952
- value: 86.045
953
  - type: recall_at_5
954
- value: 90.656
955
  - task:
956
  type: Clustering
957
  dataset:
@@ -962,7 +1859,7 @@ model-index:
962
  revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
963
  metrics:
964
  - type: v_measure
965
- value: 43.09903181165838
966
  - task:
967
  type: Clustering
968
  dataset:
@@ -973,7 +1870,7 @@ model-index:
973
  revision: 282350215ef01743dc01b456c7f5241fa8937f16
974
  metrics:
975
  - type: v_measure
976
- value: 51.710378422887594
977
  - task:
978
  type: Retrieval
979
  dataset:
@@ -984,65 +1881,65 @@ model-index:
984
  revision: None
985
  metrics:
986
  - type: map_at_1
987
- value: 4.138
988
  - type: map_at_10
989
- value: 10.419
990
  - type: map_at_100
991
- value: 12.321
992
  - type: map_at_1000
993
- value: 12.605
994
  - type: map_at_3
995
- value: 7.445
996
  - type: map_at_5
997
- value: 8.859
998
  - type: mrr_at_1
999
- value: 20.4
1000
  - type: mrr_at_10
1001
- value: 30.148999999999997
1002
  - type: mrr_at_100
1003
- value: 31.357000000000003
1004
  - type: mrr_at_1000
1005
- value: 31.424999999999997
1006
  - type: mrr_at_3
1007
- value: 26.983
1008
  - type: mrr_at_5
1009
- value: 28.883
1010
  - type: ndcg_at_1
1011
- value: 20.4
1012
  - type: ndcg_at_10
1013
- value: 17.713
1014
  - type: ndcg_at_100
1015
- value: 25.221
1016
  - type: ndcg_at_1000
1017
- value: 30.381999999999998
1018
  - type: ndcg_at_3
1019
- value: 16.607
1020
  - type: ndcg_at_5
1021
- value: 14.559
1022
  - type: precision_at_1
1023
- value: 20.4
1024
  - type: precision_at_10
1025
- value: 9.3
1026
  - type: precision_at_100
1027
- value: 2.0060000000000002
1028
  - type: precision_at_1000
1029
- value: 0.32399999999999995
1030
  - type: precision_at_3
1031
- value: 15.5
1032
  - type: precision_at_5
1033
- value: 12.839999999999998
1034
  - type: recall_at_1
1035
- value: 4.138
1036
  - type: recall_at_10
1037
- value: 18.813
1038
  - type: recall_at_100
1039
- value: 40.692
1040
  - type: recall_at_1000
1041
- value: 65.835
1042
  - type: recall_at_3
1043
- value: 9.418
1044
  - type: recall_at_5
1045
- value: 12.983
1046
  - task:
1047
  type: STS
1048
  dataset:
@@ -1053,17 +1950,17 @@ model-index:
1053
  revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
1054
  metrics:
1055
  - type: cos_sim_pearson
1056
- value: 83.25944192442188
1057
  - type: cos_sim_spearman
1058
- value: 75.04296759426568
1059
  - type: euclidean_pearson
1060
- value: 74.8130340249869
1061
  - type: euclidean_spearman
1062
- value: 68.40180320816793
1063
  - type: manhattan_pearson
1064
- value: 74.9149619199144
1065
  - type: manhattan_spearman
1066
- value: 68.52380798258379
1067
  - task:
1068
  type: STS
1069
  dataset:
@@ -1074,17 +1971,17 @@ model-index:
1074
  revision: a0d554a64d88156834ff5ae9920b964011b16384
1075
  metrics:
1076
  - type: cos_sim_pearson
1077
- value: 81.91983072545858
1078
  - type: cos_sim_spearman
1079
- value: 73.5129498787296
1080
  - type: euclidean_pearson
1081
- value: 66.76535523270856
1082
  - type: euclidean_spearman
1083
- value: 56.64797879544097
1084
  - type: manhattan_pearson
1085
- value: 66.12191731384162
1086
  - type: manhattan_spearman
1087
- value: 56.37753861965956
1088
  - task:
1089
  type: STS
1090
  dataset:
@@ -1095,17 +1992,17 @@ model-index:
1095
  revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
1096
  metrics:
1097
  - type: cos_sim_pearson
1098
- value: 77.71164758747632
1099
  - type: cos_sim_spearman
1100
- value: 79.1530762030973
1101
  - type: euclidean_pearson
1102
- value: 69.50621786400177
1103
  - type: euclidean_spearman
1104
- value: 70.44898083428744
1105
  - type: manhattan_pearson
1106
- value: 69.04018458995307
1107
  - type: manhattan_spearman
1108
- value: 70.00888532086853
1109
  - task:
1110
  type: STS
1111
  dataset:
@@ -1116,17 +2013,17 @@ model-index:
1116
  revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
1117
  metrics:
1118
  - type: cos_sim_pearson
1119
- value: 78.90774995778577
1120
  - type: cos_sim_spearman
1121
- value: 75.24229403562713
1122
  - type: euclidean_pearson
1123
- value: 68.5838924571539
1124
  - type: euclidean_spearman
1125
- value: 65.06652398167358
1126
  - type: manhattan_pearson
1127
- value: 68.23143277902628
1128
  - type: manhattan_spearman
1129
- value: 64.79624516012709
1130
  - task:
1131
  type: STS
1132
  dataset:
@@ -1137,17 +2034,17 @@ model-index:
1137
  revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
1138
  metrics:
1139
  - type: cos_sim_pearson
1140
- value: 83.78074322110155
1141
  - type: cos_sim_spearman
1142
- value: 85.12071478276958
1143
  - type: euclidean_pearson
1144
- value: 65.00147804089737
1145
  - type: euclidean_spearman
1146
- value: 66.02559342831921
1147
  - type: manhattan_pearson
1148
- value: 65.01270190203297
1149
  - type: manhattan_spearman
1150
- value: 66.13038450207748
1151
  - task:
1152
  type: STS
1153
  dataset:
@@ -1158,17 +2055,17 @@ model-index:
1158
  revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
1159
  metrics:
1160
  - type: cos_sim_pearson
1161
- value: 77.29395327338185
1162
  - type: cos_sim_spearman
1163
- value: 80.07128686563352
1164
  - type: euclidean_pearson
1165
- value: 65.97939065455975
1166
  - type: euclidean_spearman
1167
- value: 66.80283051081129
1168
  - type: manhattan_pearson
1169
- value: 65.6750450606584
1170
  - type: manhattan_spearman
1171
- value: 66.55805829330733
1172
  - task:
1173
  type: STS
1174
  dataset:
@@ -1179,17 +2076,17 @@ model-index:
1179
  revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
1180
  metrics:
1181
  - type: cos_sim_pearson
1182
- value: 87.64956503192369
1183
  - type: cos_sim_spearman
1184
- value: 87.95719598052727
1185
  - type: euclidean_pearson
1186
- value: 73.35178669405819
1187
  - type: euclidean_spearman
1188
- value: 71.58959083579994
1189
  - type: manhattan_pearson
1190
- value: 73.24156949179472
1191
  - type: manhattan_spearman
1192
- value: 71.35933730170666
1193
  - task:
1194
  type: STS
1195
  dataset:
@@ -1200,17 +2097,17 @@ model-index:
1200
  revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
1201
  metrics:
1202
  - type: cos_sim_pearson
1203
- value: 66.61640922485357
1204
  - type: cos_sim_spearman
1205
- value: 66.08406266387749
1206
  - type: euclidean_pearson
1207
- value: 43.684972836995776
1208
  - type: euclidean_spearman
1209
- value: 60.26686390609082
1210
  - type: manhattan_pearson
1211
- value: 43.694268683941154
1212
  - type: manhattan_spearman
1213
- value: 59.61419719435629
1214
  - task:
1215
  type: STS
1216
  dataset:
@@ -1221,17 +2118,17 @@ model-index:
1221
  revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
1222
  metrics:
1223
  - type: cos_sim_pearson
1224
- value: 81.73624666044613
1225
  - type: cos_sim_spearman
1226
- value: 81.68869881979401
1227
  - type: euclidean_pearson
1228
- value: 72.47205990508046
1229
  - type: euclidean_spearman
1230
- value: 71.02381428101695
1231
  - type: manhattan_pearson
1232
- value: 72.4947870027535
1233
  - type: manhattan_spearman
1234
- value: 71.0789806652577
1235
  - task:
1236
  type: Reranking
1237
  dataset:
@@ -1242,9 +2139,9 @@ model-index:
1242
  revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
1243
  metrics:
1244
  - type: map
1245
- value: 79.53671929012175
1246
  - type: mrr
1247
- value: 93.96566033820936
1248
  - task:
1249
  type: Retrieval
1250
  dataset:
@@ -1255,65 +2152,65 @@ model-index:
1255
  revision: None
1256
  metrics:
1257
  - type: map_at_1
1258
- value: 43.761
1259
  - type: map_at_10
1260
- value: 53.846000000000004
1261
  - type: map_at_100
1262
- value: 54.55799999999999
1263
  - type: map_at_1000
1264
- value: 54.620999999999995
1265
  - type: map_at_3
1266
- value: 51.513
1267
  - type: map_at_5
1268
- value: 52.591
1269
  - type: mrr_at_1
1270
- value: 46.666999999999994
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  - type: mrr_at_1000
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  - type: mrr_at_3
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- value: 53.5
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  - type: mrr_at_5
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  - type: ndcg_at_1
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  - type: precision_at_3
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- value: 21.667
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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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- value: 71.65599999999999
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  - type: recall_at_100
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- value: 84.433
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  - type: recall_at_1000
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- value: 97.5
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  - type: recall_at_3
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- value: 59.522
1315
  - type: recall_at_5
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- value: 63.632999999999996
1317
  - task:
1318
  type: PairClassification
1319
  dataset:
@@ -1324,51 +2221,51 @@ model-index:
1324
  revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
1325
  metrics:
1326
  - type: cos_sim_accuracy
1327
- value: 99.68811881188118
1328
  - type: cos_sim_ap
1329
- value: 91.08077352794682
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  - type: cos_sim_f1
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  - type: cos_sim_precision
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- value: 82.64621284755513
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  - type: cos_sim_recall
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- value: 86.2
1336
  - type: dot_accuracy
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- value: 99.14653465346535
1338
  - type: dot_ap
1339
- value: 45.24942149367904
1340
  - type: dot_f1
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- value: 46.470062555853445
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  - type: dot_precision
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- value: 42.003231017770595
1344
  - type: dot_recall
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- value: 52
1346
  - type: euclidean_accuracy
1347
- value: 99.56930693069307
1348
  - type: euclidean_ap
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- value: 80.28575652582506
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  - type: euclidean_f1
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- value: 75.52054023635341
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  - type: euclidean_precision
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- value: 86.35778635778635
1354
  - type: euclidean_recall
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- value: 67.10000000000001
1356
  - type: manhattan_accuracy
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- value: 99.56039603960396
1358
  - type: manhattan_ap
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- value: 79.74630510301085
1360
  - type: manhattan_f1
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- value: 74.67569091934575
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  - type: manhattan_precision
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- value: 85.64036222509702
1364
  - type: manhattan_recall
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- value: 66.2
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  - type: max_accuracy
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- value: 99.68811881188118
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  - type: max_ap
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- value: 91.08077352794682
1370
  - type: max_f1
1371
- value: 84.38570729319628
1372
  - task:
1373
  type: Clustering
1374
  dataset:
@@ -1379,7 +2276,7 @@ model-index:
1379
  revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
1380
  metrics:
1381
  - type: v_measure
1382
- value: 52.0788049295693
1383
  - task:
1384
  type: Clustering
1385
  dataset:
@@ -1390,7 +2287,7 @@ model-index:
1390
  revision: 815ca46b2622cec33ccafc3735d572c266efdb44
1391
  metrics:
1392
  - type: v_measure
1393
- value: 31.606006030205545
1394
  - task:
1395
  type: Reranking
1396
  dataset:
@@ -1401,9 +2298,9 @@ model-index:
1401
  revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
1402
  metrics:
1403
  - type: map
1404
- value: 50.87384988372756
1405
  - type: mrr
1406
- value: 51.62476922587217
1407
  - task:
1408
  type: Summarization
1409
  dataset:
@@ -1414,13 +2311,13 @@ model-index:
1414
  revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
1415
  metrics:
1416
  - type: cos_sim_pearson
1417
- value: 30.355859978837156
1418
  - type: cos_sim_spearman
1419
- value: 30.0847548337847
1420
  - type: dot_pearson
1421
- value: 19.391736817587557
1422
  - type: dot_spearman
1423
- value: 20.732256259543014
1424
  - task:
1425
  type: Retrieval
1426
  dataset:
@@ -1431,65 +2328,65 @@ model-index:
1431
  revision: None
1432
  metrics:
1433
  - type: map_at_1
1434
- value: 0.19
1435
  - type: map_at_10
1436
- value: 1.2850000000000001
1437
  - type: map_at_100
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- value: 6.376999999999999
1439
  - type: map_at_1000
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- value: 15.21
1441
  - type: map_at_3
1442
- value: 0.492
1443
  - type: map_at_5
1444
- value: 0.776
1445
  - type: mrr_at_1
1446
- value: 68
1447
  - type: mrr_at_10
1448
- value: 79.783
1449
  - type: mrr_at_100
1450
- value: 79.783
1451
  - type: mrr_at_1000
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- value: 79.783
1453
  - type: mrr_at_3
1454
- value: 77.333
1455
  - type: mrr_at_5
1456
- value: 79.533
1457
  - type: ndcg_at_1
1458
- value: 62
1459
  - type: ndcg_at_10
1460
- value: 54.635
1461
  - type: ndcg_at_100
1462
- value: 40.939
1463
  - type: ndcg_at_1000
1464
- value: 37.716
1465
  - type: ndcg_at_3
1466
- value: 58.531
1467
  - type: ndcg_at_5
1468
- value: 58.762
1469
  - type: precision_at_1
1470
- value: 68
1471
  - type: precision_at_10
1472
- value: 58.8
1473
  - type: precision_at_100
1474
- value: 41.74
1475
  - type: precision_at_1000
1476
- value: 16.938
1477
  - type: precision_at_3
1478
- value: 64
1479
  - type: precision_at_5
1480
- value: 64.8
1481
  - type: recall_at_1
1482
- value: 0.19
1483
  - type: recall_at_10
1484
- value: 1.547
1485
  - type: recall_at_100
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- value: 9.739
1487
  - type: recall_at_1000
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- value: 35.815000000000005
1489
  - type: recall_at_3
1490
- value: 0.528
1491
  - type: recall_at_5
1492
- value: 0.894
1493
  - task:
1494
  type: Retrieval
1495
  dataset:
@@ -1500,65 +2397,65 @@ model-index:
1500
  revision: None
1501
  metrics:
1502
  - type: map_at_1
1503
- value: 1.514
1504
  - type: map_at_10
1505
- value: 7.163
1506
  - type: map_at_100
1507
- value: 11.623999999999999
1508
  - type: map_at_1000
1509
- value: 13.062999999999999
1510
  - type: map_at_3
1511
- value: 3.51
1512
  - type: map_at_5
1513
- value: 4.661
1514
  - type: mrr_at_1
1515
- value: 20.408
1516
  - type: mrr_at_10
1517
- value: 33.993
1518
  - type: mrr_at_100
1519
- value: 35.257
1520
  - type: mrr_at_1000
1521
- value: 35.313
1522
  - type: mrr_at_3
1523
- value: 30.272
1524
  - type: mrr_at_5
1525
- value: 31.701
1526
  - type: ndcg_at_1
1527
- value: 18.367
1528
  - type: ndcg_at_10
1529
- value: 18.062
1530
  - type: ndcg_at_100
1531
- value: 28.441
1532
  - type: ndcg_at_1000
1533
- value: 40.748
1534
  - type: ndcg_at_3
1535
- value: 18.651999999999997
1536
  - type: ndcg_at_5
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- value: 17.055
1538
  - type: precision_at_1
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- value: 20.408
1540
  - type: precision_at_10
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- value: 17.551
1542
  - type: precision_at_100
1543
- value: 6.223999999999999
1544
  - type: precision_at_1000
1545
- value: 1.427
1546
  - type: precision_at_3
1547
- value: 20.408
1548
  - type: precision_at_5
1549
- value: 17.959
1550
  - type: recall_at_1
1551
- value: 1.514
1552
  - type: recall_at_10
1553
- value: 13.447000000000001
1554
  - type: recall_at_100
1555
- value: 39.77
1556
  - type: recall_at_1000
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- value: 76.95
1558
  - type: recall_at_3
1559
- value: 4.806
1560
  - type: recall_at_5
1561
- value: 6.873
1562
  - task:
1563
  type: Classification
1564
  dataset:
@@ -1569,11 +2466,11 @@ model-index:
1569
  revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
1570
  metrics:
1571
  - type: accuracy
1572
- value: 65.53179999999999
1573
  - type: ap
1574
- value: 11.504743595308318
1575
  - type: f1
1576
- value: 49.74264614001562
1577
  - task:
1578
  type: Classification
1579
  dataset:
@@ -1584,9 +2481,9 @@ model-index:
1584
  revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
1585
  metrics:
1586
  - type: accuracy
1587
- value: 56.47425014148275
1588
  - type: f1
1589
- value: 56.555750746223346
1590
  - task:
1591
  type: Clustering
1592
  dataset:
@@ -1597,7 +2494,7 @@ model-index:
1597
  revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
1598
  metrics:
1599
  - type: v_measure
1600
- value: 39.27004599453324
1601
  - task:
1602
  type: PairClassification
1603
  dataset:
@@ -1608,51 +2505,51 @@ model-index:
1608
  revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
1609
  metrics:
1610
  - type: cos_sim_accuracy
1611
- value: 84.47875067056088
1612
  - type: cos_sim_ap
1613
- value: 68.630858164926
1614
  - type: cos_sim_f1
1615
- value: 64.5112402121748
1616
  - type: cos_sim_precision
1617
- value: 61.87015503875969
1618
  - type: cos_sim_recall
1619
- value: 67.38786279683377
1620
  - type: dot_accuracy
1621
- value: 77.68969422423557
1622
  - type: dot_ap
1623
- value: 37.28838556128439
1624
  - type: dot_f1
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- value: 43.27918525376652
1626
  - type: dot_precision
1627
- value: 31.776047460140898
1628
  - type: dot_recall
1629
- value: 67.83641160949868
1630
  - type: euclidean_accuracy
1631
- value: 82.67866722298385
1632
  - type: euclidean_ap
1633
- value: 62.72011158877603
1634
  - type: euclidean_f1
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- value: 60.39579770339605
1636
  - type: euclidean_precision
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- value: 56.23293903548681
1638
  - type: euclidean_recall
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- value: 65.22427440633246
1640
  - type: manhattan_accuracy
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- value: 82.67866722298385
1642
  - type: manhattan_ap
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- value: 62.80364769571995
1644
  - type: manhattan_f1
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- value: 60.413827282864574
1646
  - type: manhattan_precision
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- value: 56.94931090866619
1648
  - type: manhattan_recall
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- value: 64.32717678100263
1650
  - type: max_accuracy
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- value: 84.47875067056088
1652
  - type: max_ap
1653
- value: 68.630858164926
1654
  - type: max_f1
1655
- value: 64.5112402121748
1656
  - task:
1657
  type: PairClassification
1658
  dataset:
@@ -1663,51 +2560,51 @@ model-index:
1663
  revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
1664
  metrics:
1665
  - type: cos_sim_accuracy
1666
- value: 88.4192959987581
1667
  - type: cos_sim_ap
1668
- value: 84.81803796578367
1669
  - type: cos_sim_f1
1670
- value: 77.1643709825528
1671
  - type: cos_sim_precision
1672
- value: 73.77958839643183
1673
  - type: cos_sim_recall
1674
- value: 80.874653526332
1675
  - type: dot_accuracy
1676
- value: 81.99441145651414
1677
  - type: dot_ap
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- value: 67.908510950511
1679
  - type: dot_f1
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- value: 64.4734255193656
1681
  - type: dot_precision
1682
- value: 56.120935539075866
1683
  - type: dot_recall
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- value: 75.74684323991376
1685
  - type: euclidean_accuracy
1686
- value: 82.67163426087632
1687
  - type: euclidean_ap
1688
- value: 70.1466353903414
1689
  - type: euclidean_f1
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- value: 62.686024087617795
1691
  - type: euclidean_precision
1692
- value: 59.42738875474301
1693
  - type: euclidean_recall
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- value: 66.32275947028026
1695
  - type: manhattan_accuracy
1696
- value: 82.6483486630186
1697
  - type: manhattan_ap
1698
- value: 70.12958345267741
1699
  - type: manhattan_f1
1700
- value: 62.5966218150587
1701
  - type: manhattan_precision
1702
- value: 58.47820272800214
1703
  - type: manhattan_recall
1704
- value: 67.33908222975053
1705
  - type: max_accuracy
1706
- value: 88.4192959987581
1707
  - type: max_ap
1708
- value: 84.81803796578367
1709
  - type: max_f1
1710
- value: 77.1643709825528
1711
  ---
1712
  ---
1713
 
 
11
  language: en
12
  license: apache-2.0
13
  model-index:
14
+ - name: jina-embedding-s-en-v1
15
  results:
16
  - task:
17
  type: Classification
 
23
  revision: e8379541af4e31359cca9fbcf4b00f2671dba205
24
  metrics:
25
  - type: accuracy
26
+ value: 64.82089552238806
27
  - type: ap
28
+ value: 27.100981946230778
29
  - type: f1
30
+ value: 58.3354886367184
31
  - task:
32
  type: Classification
33
  dataset:
 
38
  revision: e2d317d38cd51312af73b3d32a06d1a08b442046
39
  metrics:
40
  - type: accuracy
41
+ value: 64.282775
42
  - type: ap
43
+ value: 60.350688924943796
44
  - type: f1
45
+ value: 62.06346948494396
46
  - task:
47
  type: Classification
48
  dataset:
 
53
  revision: 1399c76144fd37290681b995c656ef9b2e06e26d
54
  metrics:
55
  - type: accuracy
56
+ value: 30.623999999999995
57
  - type: f1
58
+ value: 29.427789186742153
59
  - task:
60
  type: Retrieval
61
  dataset:
 
66
  revision: None
67
  metrics:
68
  - type: map_at_1
69
+ value: 22.119
70
  - type: map_at_10
71
+ value: 35.609
72
  - type: map_at_100
73
+ value: 36.935
74
  - type: map_at_1000
75
+ value: 36.957
76
  - type: map_at_3
77
+ value: 31.046000000000003
78
  - type: map_at_5
79
+ value: 33.574
80
  - type: mrr_at_1
81
+ value: 22.404
82
  - type: mrr_at_10
83
+ value: 35.695
84
  - type: mrr_at_100
85
+ value: 37.021
86
  - type: mrr_at_1000
87
+ value: 37.043
88
  - type: mrr_at_3
89
+ value: 31.093
90
  - type: mrr_at_5
91
+ value: 33.635999999999996
92
  - type: ndcg_at_1
93
+ value: 22.119
94
  - type: ndcg_at_10
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+ value: 43.566
96
  - type: ndcg_at_100
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+ value: 49.370000000000005
98
  - type: ndcg_at_1000
99
+ value: 49.901
100
  - type: ndcg_at_3
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+ value: 34.06
102
  - type: ndcg_at_5
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+ value: 38.653999999999996
104
  - type: precision_at_1
105
+ value: 22.119
106
  - type: precision_at_10
107
+ value: 6.92
108
  - type: precision_at_100
109
+ value: 0.95
110
  - type: precision_at_1000
111
+ value: 0.099
112
  - type: precision_at_3
113
+ value: 14.272000000000002
114
  - type: precision_at_5
115
+ value: 10.811
116
  - type: recall_at_1
117
+ value: 22.119
118
  - type: recall_at_10
119
+ value: 69.203
120
  - type: recall_at_100
121
+ value: 95.021
122
  - type: recall_at_1000
123
+ value: 99.075
124
  - type: recall_at_3
125
+ value: 42.817
126
  - type: recall_at_5
127
+ value: 54.054
128
  - task:
129
  type: Clustering
130
  dataset:
 
135
  revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
136
  metrics:
137
  - type: v_measure
138
+ value: 34.1740289109719
139
  - task:
140
  type: Clustering
141
  dataset:
 
146
  revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
147
  metrics:
148
  - type: v_measure
149
+ value: 23.985251383455463
150
  - task:
151
  type: Reranking
152
  dataset:
 
157
  revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
158
  metrics:
159
  - type: map
160
+ value: 60.24873612289029
161
  - type: mrr
162
+ value: 74.65692740623489
163
  - task:
164
  type: STS
165
  dataset:
 
170
  revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
171
  metrics:
172
  - type: cos_sim_pearson
173
+ value: 86.22415390332444
174
  - type: cos_sim_spearman
175
+ value: 82.9591191954711
176
  - type: euclidean_pearson
177
+ value: 44.096317524324945
178
  - type: euclidean_spearman
179
+ value: 42.95218351391625
180
  - type: manhattan_pearson
181
+ value: 44.07766490545065
182
  - type: manhattan_spearman
183
+ value: 42.78350497166606
184
  - task:
185
  type: Classification
186
  dataset:
 
191
  revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
192
  metrics:
193
  - type: accuracy
194
+ value: 74.64285714285714
195
  - type: f1
196
+ value: 73.53680835577447
197
  - task:
198
  type: Clustering
199
  dataset:
 
204
  revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
205
  metrics:
206
  - type: v_measure
207
+ value: 28.512813238490164
208
  - task:
209
  type: Clustering
210
  dataset:
 
215
  revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
216
  metrics:
217
  - type: v_measure
218
+ value: 20.942214972649488
219
+ - task:
220
+ type: Retrieval
221
+ dataset:
222
+ type: BeIR/cqadupstack
223
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224
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227
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228
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290
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291
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292
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297
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567
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844
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1123
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1192
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1261
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1274
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1343
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1412
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1628
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1639
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1652
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1721
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1790
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1791
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1859
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1870
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1881
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1882
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1944
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1945
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1950
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1951
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1954
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1956
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1958
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1960
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1965
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1971
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1973
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1975
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1986
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1992
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1993
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1995
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1996
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1998
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2000
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2003
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2004
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2005
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2007
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2013
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2015
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2019
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2021
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2055
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2076
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2077
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2097
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2118
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  - task:
2146
  type: Retrieval
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  dataset:
 
2152
  revision: None
2153
  metrics:
2154
  - type: map_at_1
2155
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  - type: map_at_10
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  - type: precision_at_3
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  - type: recall_at_1000
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  - type: recall_at_5
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2215
  type: PairClassification
2216
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2221
  revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
2222
  metrics:
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  - type: cos_sim_accuracy
2224
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2226
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  - type: cos_sim_f1
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  - type: cos_sim_recall
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  - type: dot_accuracy
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2239
  - type: dot_precision
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  - type: dot_recall
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  - type: euclidean_accuracy
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2245
  - type: euclidean_ap
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2247
  - type: euclidean_f1
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2249
  - type: euclidean_precision
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2251
  - type: euclidean_recall
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2253
  - type: manhattan_accuracy
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  - type: manhattan_ap
2256
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2257
  - type: manhattan_f1
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2259
  - type: manhattan_precision
2260
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2261
  - type: manhattan_recall
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2263
  - type: max_accuracy
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  - type: max_ap
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2267
  - type: max_f1
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2269
  - task:
2270
  type: Clustering
2271
  dataset:
 
2276
  revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2277
  metrics:
2278
  - type: v_measure
2279
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2280
  - task:
2281
  type: Clustering
2282
  dataset:
 
2287
  revision: 815ca46b2622cec33ccafc3735d572c266efdb44
2288
  metrics:
2289
  - type: v_measure
2290
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2291
  - task:
2292
  type: Reranking
2293
  dataset:
 
2298
  revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
2299
  metrics:
2300
  - type: map
2301
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2302
  - type: mrr
2303
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2304
  - task:
2305
  type: Summarization
2306
  dataset:
 
2311
  revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
2312
  metrics:
2313
  - type: cos_sim_pearson
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  - type: cos_sim_spearman
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  - type: dot_pearson
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  - type: dot_spearman
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2321
  - task:
2322
  type: Retrieval
2323
  dataset:
 
2328
  revision: None
2329
  metrics:
2330
  - type: map_at_1
2331
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2332
  - type: map_at_10
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2334
  - type: map_at_100
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2336
  - type: map_at_1000
2337
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2338
  - type: map_at_3
2339
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  - type: map_at_5
2341
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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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2356
  - type: ndcg_at_10
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2358
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2360
  - type: ndcg_at_1000
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2362
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2365
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2366
  - type: precision_at_1
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2368
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2369
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2370
  - type: precision_at_100
2371
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2372
  - type: precision_at_1000
2373
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2375
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  - type: precision_at_5
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  - type: recall_at_1
2379
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  - type: recall_at_10
2381
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  - type: recall_at_1000
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  - type: recall_at_3
2387
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  - type: recall_at_5
2389
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2390
  - task:
2391
  type: Retrieval
2392
  dataset:
 
2397
  revision: None
2398
  metrics:
2399
  - type: map_at_1
2400
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2401
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2402
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  - type: map_at_5
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2437
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2439
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2441
  - type: precision_at_1000
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2444
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2445
  - type: precision_at_5
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  - type: recall_at_1
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2449
  - type: recall_at_10
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2451
  - type: recall_at_100
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  - type: recall_at_1000
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2455
  - type: recall_at_3
2456
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2457
  - type: recall_at_5
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2459
  - task:
2460
  type: Classification
2461
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2466
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2467
  metrics:
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  - type: accuracy
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2476
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2481
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2482
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2483
  - type: accuracy
2484
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2489
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2494
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2496
  - type: v_measure
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2499
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2500
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2505
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2506
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2507
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2508
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2554
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2555
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2560
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2561
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2608
  ---
2609
  ---
2610