avsolatorio commited on
Commit
80189c6
1 Parent(s): 1c5a6fc

Update model

Browse files

Signed-off-by: Aivin V. Solatorio <avsolatorio@gmail.com>

Files changed (4) hide show
  1. README.md +970 -970
  2. commit-info.json +1 -1
  3. config.json +1 -1
  4. model.safetensors +1 -1
README.md CHANGED
@@ -23,11 +23,11 @@ model-index:
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  revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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  metrics:
25
  - type: accuracy
26
- value: 73.40298507462688
27
  - type: ap
28
- value: 36.01661955459773
29
  - type: f1
30
- value: 67.35688942295793
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  - task:
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  type: Classification
33
  dataset:
@@ -38,11 +38,11 @@ model-index:
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  revision: e2d317d38cd51312af73b3d32a06d1a08b442046
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  metrics:
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  - type: accuracy
41
- value: 92.71195000000002
42
  - type: ap
43
- value: 89.33528835459364
44
  - type: f1
45
- value: 92.69653287380515
46
  - task:
47
  type: Classification
48
  dataset:
@@ -53,9 +53,9 @@ model-index:
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  revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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  metrics:
55
  - type: accuracy
56
- value: 49.007999999999996
57
  - type: f1
58
- value: 48.44310279702607
59
  - task:
60
  type: Retrieval
61
  dataset:
@@ -66,65 +66,65 @@ model-index:
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  revision: None
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  metrics:
68
  - type: map_at_1
69
- value: 36.272999999999996
70
  - type: map_at_10
71
- value: 52.059999999999995
72
  - type: map_at_100
73
- value: 52.75300000000001
74
  - type: map_at_1000
75
- value: 52.756
76
  - type: map_at_3
77
- value: 47.57
78
  - type: map_at_5
79
- value: 50.236999999999995
80
  - type: mrr_at_1
81
- value: 36.272999999999996
82
  - type: mrr_at_10
83
- value: 51.942
84
  - type: mrr_at_100
85
- value: 52.634
86
  - type: mrr_at_1000
87
- value: 52.637
88
  - type: mrr_at_3
89
- value: 47.475
90
  - type: mrr_at_5
91
- value: 50.11
92
  - type: ndcg_at_1
93
- value: 36.272999999999996
94
  - type: ndcg_at_10
95
- value: 60.558
96
  - type: ndcg_at_100
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- value: 63.293
98
  - type: ndcg_at_1000
99
- value: 63.375
100
  - type: ndcg_at_3
101
- value: 51.364
102
  - type: ndcg_at_5
103
- value: 56.154
104
  - type: precision_at_1
105
- value: 36.272999999999996
106
  - type: precision_at_10
107
- value: 8.755
108
  - type: precision_at_100
109
- value: 0.9900000000000001
110
  - type: precision_at_1000
111
  value: 0.1
112
  - type: precision_at_3
113
- value: 20.791999999999998
114
  - type: precision_at_5
115
- value: 14.793999999999999
116
  - type: recall_at_1
117
- value: 36.272999999999996
118
  - type: recall_at_10
119
- value: 87.553
120
  - type: recall_at_100
121
- value: 99.004
122
  - type: recall_at_1000
123
- value: 99.644
124
  - type: recall_at_3
125
- value: 62.376
126
  - type: recall_at_5
127
- value: 73.969
128
  - task:
129
  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: 47.79137102109872
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: 40.03049595085257
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: 62.868157850825256
161
  - type: mrr
162
- value: 75.33922525612276
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: 88.96056116438724
174
  - type: cos_sim_spearman
175
- value: 87.32608616965557
176
  - type: euclidean_pearson
177
- value: 87.40536769084146
178
  - type: euclidean_spearman
179
- value: 87.39235273982528
180
  - type: manhattan_pearson
181
- value: 87.4496043849794
182
  - type: manhattan_spearman
183
- value: 87.1128282983821
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: 86.16883116883116
195
  - type: f1
196
- value: 86.1338488750026
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: 38.950791675044
208
  - task:
209
  type: Clustering
210
  dataset:
@@ -215,7 +215,7 @@ model-index:
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  revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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  metrics:
217
  - type: v_measure
218
- value: 35.40686850755838
219
  - task:
220
  type: Retrieval
221
  dataset:
@@ -226,65 +226,65 @@ model-index:
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  revision: None
227
  metrics:
228
  - type: map_at_1
229
- value: 30.891000000000002
230
  - type: map_at_10
231
- value: 42.624
232
  - type: map_at_100
233
- value: 44.205
234
  - type: map_at_1000
235
- value: 44.336999999999996
236
  - type: map_at_3
237
- value: 38.81
238
  - type: map_at_5
239
- value: 41.152
240
  - type: mrr_at_1
241
- value: 38.196999999999996
242
  - type: mrr_at_10
243
- value: 48.641
244
  - type: mrr_at_100
245
- value: 49.329
246
  - type: mrr_at_1000
247
- value: 49.376
248
  - type: mrr_at_3
249
- value: 45.637
250
  - type: mrr_at_5
251
- value: 47.611
252
  - type: ndcg_at_1
253
- value: 38.196999999999996
254
  - type: ndcg_at_10
255
- value: 49.274
256
  - type: ndcg_at_100
257
- value: 54.716
258
  - type: ndcg_at_1000
259
- value: 56.654
260
  - type: ndcg_at_3
261
- value: 43.787
262
  - type: ndcg_at_5
263
- value: 46.719
264
  - type: precision_at_1
265
- value: 38.196999999999996
266
  - type: precision_at_10
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- value: 9.585
268
  - type: precision_at_100
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- value: 1.545
270
  - type: precision_at_1000
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- value: 0.20400000000000001
272
  - type: precision_at_3
273
- value: 21.173000000000002
274
  - type: precision_at_5
275
- value: 15.536
276
  - type: recall_at_1
277
- value: 30.891000000000002
278
  - type: recall_at_10
279
- value: 61.792
280
  - type: recall_at_100
281
- value: 84.526
282
  - type: recall_at_1000
283
- value: 96.717
284
  - type: recall_at_3
285
- value: 46.472
286
  - type: recall_at_5
287
- value: 54.391999999999996
288
  - task:
289
  type: Retrieval
290
  dataset:
@@ -295,65 +295,65 @@ model-index:
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  revision: None
296
  metrics:
297
  - type: map_at_1
298
- value: 30.266
299
  - type: map_at_10
300
- value: 39.717999999999996
301
  - type: map_at_100
302
- value: 40.971000000000004
303
  - type: map_at_1000
304
- value: 41.097
305
  - type: map_at_3
306
- value: 36.858999999999995
307
  - type: map_at_5
308
- value: 38.405
309
  - type: mrr_at_1
310
- value: 37.452000000000005
311
  - type: mrr_at_10
312
- value: 45.528
313
  - type: mrr_at_100
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- value: 46.178000000000004
315
  - type: mrr_at_1000
316
- value: 46.221000000000004
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  - type: mrr_at_3
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- value: 43.089
319
  - type: mrr_at_5
320
- value: 44.497
321
  - type: ndcg_at_1
322
- value: 37.452000000000005
323
  - type: ndcg_at_10
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- value: 45.282
325
  - type: ndcg_at_100
326
- value: 49.742
327
  - type: ndcg_at_1000
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- value: 51.754999999999995
329
  - type: ndcg_at_3
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- value: 41.024
331
  - type: ndcg_at_5
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- value: 42.912
333
  - type: precision_at_1
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- value: 37.452000000000005
335
  - type: precision_at_10
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- value: 8.516
337
  - type: precision_at_100
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- value: 1.3679999999999999
339
  - type: precision_at_1000
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  value: 0.184
341
  - type: precision_at_3
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- value: 19.575
343
  - type: precision_at_5
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- value: 13.771
345
  - type: recall_at_1
346
- value: 30.266
347
  - type: recall_at_10
348
- value: 55.086
349
  - type: recall_at_100
350
- value: 74.083
351
  - type: recall_at_1000
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- value: 86.722
353
  - type: recall_at_3
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- value: 42.449999999999996
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  - type: recall_at_5
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- value: 47.975
357
  - task:
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  type: Retrieval
359
  dataset:
@@ -364,65 +364,65 @@ 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: 39.217
368
  - type: map_at_10
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- value: 51.466
370
  - type: map_at_100
371
- value: 52.531000000000006
372
  - type: map_at_1000
373
- value: 52.586
374
  - type: map_at_3
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- value: 47.942
376
  - type: map_at_5
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- value: 49.988
378
  - type: mrr_at_1
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- value: 44.765
380
  - type: mrr_at_10
381
- value: 54.748
382
  - type: mrr_at_100
383
- value: 55.41199999999999
384
  - type: mrr_at_1000
385
- value: 55.437999999999995
386
  - type: mrr_at_3
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- value: 52.017
388
  - type: mrr_at_5
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- value: 53.693999999999996
390
  - type: ndcg_at_1
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- value: 44.765
392
  - type: ndcg_at_10
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- value: 57.397
394
  - type: ndcg_at_100
395
- value: 61.526
396
  - type: ndcg_at_1000
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- value: 62.577000000000005
398
  - type: ndcg_at_3
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- value: 51.414
400
  - type: ndcg_at_5
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- value: 54.486999999999995
402
  - type: precision_at_1
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- value: 44.765
404
  - type: precision_at_10
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- value: 9.354
406
  - type: precision_at_100
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- value: 1.2309999999999999
408
  - type: precision_at_1000
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  value: 0.136
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  - type: precision_at_3
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- value: 22.820999999999998
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  - type: precision_at_5
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- value: 16.012999999999998
414
  - type: recall_at_1
415
- value: 39.217
416
  - type: recall_at_10
417
- value: 71.588
418
  - type: recall_at_100
419
- value: 89.473
420
  - type: recall_at_1000
421
- value: 96.863
422
  - type: recall_at_3
423
- value: 55.943
424
  - type: recall_at_5
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- value: 63.14999999999999
426
  - task:
427
  type: Retrieval
428
  dataset:
@@ -433,65 +433,65 @@ model-index:
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  revision: None
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  metrics:
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  - type: map_at_1
436
- value: 26.451
437
  - type: map_at_10
438
- value: 34.738
439
  - type: map_at_100
440
- value: 35.769
441
  - type: map_at_1000
442
- value: 35.851
443
  - type: map_at_3
444
- value: 32.002
445
  - type: map_at_5
446
- value: 33.800999999999995
447
  - type: mrr_at_1
448
- value: 28.814
449
  - type: mrr_at_10
450
- value: 36.992000000000004
451
  - type: mrr_at_100
452
- value: 37.901
453
  - type: mrr_at_1000
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- value: 37.964
455
  - type: mrr_at_3
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- value: 34.426
457
  - type: mrr_at_5
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- value: 36.075
459
  - type: ndcg_at_1
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- value: 28.814
461
  - type: ndcg_at_10
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- value: 39.667
463
  - type: ndcg_at_100
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- value: 44.741
465
  - type: ndcg_at_1000
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- value: 46.763
467
  - type: ndcg_at_3
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- value: 34.461999999999996
469
  - type: ndcg_at_5
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- value: 37.472
471
  - type: precision_at_1
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- value: 28.814
473
  - type: precision_at_10
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- value: 6.045
475
  - type: precision_at_100
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- value: 0.903
477
  - type: precision_at_1000
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  value: 0.11199999999999999
479
  - type: precision_at_3
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- value: 14.463000000000001
481
  - type: precision_at_5
482
- value: 10.418
483
  - type: recall_at_1
484
- value: 26.451
485
  - type: recall_at_10
486
- value: 52.751999999999995
487
  - type: recall_at_100
488
- value: 75.971
489
  - type: recall_at_1000
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- value: 91.02
491
  - type: recall_at_3
492
- value: 38.896
493
  - type: recall_at_5
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- value: 46.126
495
  - task:
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  type: Retrieval
497
  dataset:
@@ -502,65 +502,65 @@ 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: 16.03
506
  - type: map_at_10
507
- value: 24.474999999999998
508
  - type: map_at_100
509
- value: 25.650000000000002
510
  - type: map_at_1000
511
- value: 25.764
512
  - type: map_at_3
513
- value: 21.656
514
  - type: map_at_5
515
- value: 23.269000000000002
516
  - type: mrr_at_1
517
- value: 20.025000000000002
518
  - type: mrr_at_10
519
- value: 29.325000000000003
520
  - type: mrr_at_100
521
- value: 30.264999999999997
522
  - type: mrr_at_1000
523
- value: 30.325000000000003
524
  - type: mrr_at_3
525
- value: 26.493
526
  - type: mrr_at_5
527
- value: 28.197
528
  - type: ndcg_at_1
529
- value: 20.025000000000002
530
  - type: ndcg_at_10
531
- value: 30.012
532
  - type: ndcg_at_100
533
- value: 35.760999999999996
534
  - type: ndcg_at_1000
535
- value: 38.53
536
  - type: ndcg_at_3
537
- value: 24.863
538
  - type: ndcg_at_5
539
- value: 27.36
540
  - type: precision_at_1
541
- value: 20.025000000000002
542
  - type: precision_at_10
543
- value: 5.721
544
  - type: precision_at_100
545
- value: 0.9809999999999999
546
  - type: precision_at_1000
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  value: 0.136
548
  - type: precision_at_3
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- value: 12.189
550
  - type: precision_at_5
551
- value: 9.08
552
  - type: recall_at_1
553
- value: 16.03
554
  - type: recall_at_10
555
- value: 42.263
556
  - type: recall_at_100
557
- value: 67.868
558
  - type: recall_at_1000
559
- value: 87.77000000000001
560
  - type: recall_at_3
561
- value: 27.932000000000002
562
  - type: recall_at_5
563
- value: 34.46
564
  - task:
565
  type: Retrieval
566
  dataset:
@@ -571,65 +571,65 @@ model-index:
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  revision: None
572
  metrics:
573
  - type: map_at_1
574
- value: 29.358
575
  - type: map_at_10
576
- value: 39.753
577
  - type: map_at_100
578
- value: 41.031
579
  - type: map_at_1000
580
- value: 41.135
581
  - type: map_at_3
582
- value: 36.515
583
  - type: map_at_5
584
- value: 38.346999999999994
585
  - type: mrr_at_1
586
- value: 35.9
587
  - type: mrr_at_10
588
- value: 45.336
589
  - type: mrr_at_100
590
- value: 46.087
591
  - type: mrr_at_1000
592
- value: 46.129999999999995
593
  - type: mrr_at_3
594
- value: 42.620999999999995
595
  - type: mrr_at_5
596
- value: 44.224000000000004
597
  - type: ndcg_at_1
598
- value: 35.9
599
  - type: ndcg_at_10
600
- value: 45.85
601
  - type: ndcg_at_100
602
- value: 51.186
603
  - type: ndcg_at_1000
604
- value: 53.154999999999994
605
  - type: ndcg_at_3
606
- value: 40.594
607
  - type: ndcg_at_5
608
- value: 43.169999999999995
609
  - type: precision_at_1
610
- value: 35.9
611
  - type: precision_at_10
612
- value: 8.402
613
  - type: precision_at_100
614
- value: 1.2850000000000001
615
  - type: precision_at_1000
616
- value: 0.164
617
  - type: precision_at_3
618
- value: 19.249
619
  - type: precision_at_5
620
- value: 13.763
621
  - type: recall_at_1
622
- value: 29.358
623
  - type: recall_at_10
624
- value: 58.257000000000005
625
  - type: recall_at_100
626
- value: 81.22200000000001
627
  - type: recall_at_1000
628
- value: 94.045
629
  - type: recall_at_3
630
- value: 43.599
631
  - type: recall_at_5
632
- value: 50.232
633
  - task:
634
  type: Retrieval
635
  dataset:
@@ -640,65 +640,65 @@ model-index:
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  revision: None
641
  metrics:
642
  - type: map_at_1
643
- value: 23.954
644
  - type: map_at_10
645
- value: 33.767
646
  - type: map_at_100
647
- value: 35.225
648
  - type: map_at_1000
649
- value: 35.339
650
  - type: map_at_3
651
- value: 30.746000000000002
652
  - type: map_at_5
653
- value: 32.318000000000005
654
  - type: mrr_at_1
655
- value: 30.137000000000004
656
  - type: mrr_at_10
657
- value: 39.24
658
  - type: mrr_at_100
659
- value: 40.235
660
  - type: mrr_at_1000
661
- value: 40.294999999999995
662
  - type: mrr_at_3
663
- value: 36.758
664
  - type: mrr_at_5
665
- value: 38.031
666
  - type: ndcg_at_1
667
- value: 30.137000000000004
668
  - type: ndcg_at_10
669
- value: 39.711999999999996
670
  - type: ndcg_at_100
671
- value: 45.795
672
  - type: ndcg_at_1000
673
- value: 48.178
674
  - type: ndcg_at_3
675
- value: 34.768
676
  - type: ndcg_at_5
677
- value: 36.756
678
  - type: precision_at_1
679
- value: 30.137000000000004
680
  - type: precision_at_10
681
- value: 7.443
682
  - type: precision_at_100
683
- value: 1.221
684
  - type: precision_at_1000
685
- value: 0.159
686
  - type: precision_at_3
687
  value: 16.933
688
  - type: precision_at_5
689
- value: 11.918
690
  - type: recall_at_1
691
- value: 23.954
692
  - type: recall_at_10
693
- value: 52.234
694
  - type: recall_at_100
695
- value: 77.75800000000001
696
  - type: recall_at_1000
697
- value: 94.072
698
  - type: recall_at_3
699
- value: 37.876
700
  - type: recall_at_5
701
- value: 43.494
702
  - task:
703
  type: Retrieval
704
  dataset:
@@ -709,65 +709,65 @@ model-index:
709
  revision: None
710
  metrics:
711
  - type: map_at_1
712
- value: 25.478416666666664
713
  - type: map_at_10
714
- value: 34.483999999999995
715
  - type: map_at_100
716
- value: 35.71641666666667
717
  - type: map_at_1000
718
- value: 35.8315
719
  - type: map_at_3
720
- value: 31.571083333333334
721
  - type: map_at_5
722
- value: 33.229749999999996
723
  - type: mrr_at_1
724
- value: 30.122416666666663
725
  - type: mrr_at_10
726
- value: 38.608333333333334
727
  - type: mrr_at_100
728
- value: 39.465500000000006
729
  - type: mrr_at_1000
730
- value: 39.52375
731
  - type: mrr_at_3
732
- value: 36.047916666666666
733
  - type: mrr_at_5
734
- value: 37.53833333333333
735
  - type: ndcg_at_1
736
- value: 30.122416666666663
737
  - type: ndcg_at_10
738
- value: 39.87575
739
  - type: ndcg_at_100
740
- value: 45.15691666666666
741
  - type: ndcg_at_1000
742
- value: 47.43891666666667
743
  - type: ndcg_at_3
744
- value: 34.88666666666666
745
  - type: ndcg_at_5
746
- value: 37.30966666666667
747
  - type: precision_at_1
748
- value: 30.122416666666663
749
  - type: precision_at_10
750
- value: 7.056500000000001
751
  - type: precision_at_100
752
- value: 1.1415000000000002
753
  - type: precision_at_1000
754
- value: 0.15308333333333332
755
  - type: precision_at_3
756
- value: 16.03525
757
  - type: precision_at_5
758
- value: 11.51125
759
  - type: recall_at_1
760
- value: 25.478416666666664
761
  - type: recall_at_10
762
- value: 51.72658333333333
763
  - type: recall_at_100
764
- value: 74.94641666666666
765
  - type: recall_at_1000
766
- value: 90.75300000000001
767
  - type: recall_at_3
768
- value: 37.93833333333333
769
  - type: recall_at_5
770
- value: 44.15625
771
  - task:
772
  type: Retrieval
773
  dataset:
@@ -778,65 +778,65 @@ model-index:
778
  revision: None
779
  metrics:
780
  - type: map_at_1
781
- value: 24.697
782
  - type: map_at_10
783
- value: 30.919999999999998
784
  - type: map_at_100
785
- value: 31.889
786
  - type: map_at_1000
787
- value: 31.985000000000003
788
  - type: map_at_3
789
- value: 29.046
790
  - type: map_at_5
791
- value: 29.902
792
  - type: mrr_at_1
793
- value: 27.454
794
  - type: mrr_at_10
795
- value: 33.517
796
  - type: mrr_at_100
797
- value: 34.381
798
  - type: mrr_at_1000
799
- value: 34.452
800
  - type: mrr_at_3
801
- value: 31.747999999999998
802
  - type: mrr_at_5
803
- value: 32.561
804
  - type: ndcg_at_1
805
- value: 27.454
806
  - type: ndcg_at_10
807
- value: 34.687
808
  - type: ndcg_at_100
809
- value: 39.395
810
  - type: ndcg_at_1000
811
- value: 41.826
812
  - type: ndcg_at_3
813
- value: 31.102
814
  - type: ndcg_at_5
815
- value: 32.435
816
  - type: precision_at_1
817
- value: 27.454
818
  - type: precision_at_10
819
- value: 5.322
820
  - type: precision_at_100
821
- value: 0.83
822
  - type: precision_at_1000
823
  value: 0.11199999999999999
824
  - type: precision_at_3
825
- value: 13.088
826
  - type: precision_at_5
827
- value: 8.803999999999998
828
  - type: recall_at_1
829
- value: 24.697
830
  - type: recall_at_10
831
- value: 43.688
832
  - type: recall_at_100
833
- value: 64.893
834
  - type: recall_at_1000
835
- value: 82.755
836
  - type: recall_at_3
837
- value: 33.896
838
  - type: recall_at_5
839
- value: 37.174
840
  - task:
841
  type: Retrieval
842
  dataset:
@@ -847,65 +847,65 @@ model-index:
847
  revision: None
848
  metrics:
849
  - type: map_at_1
850
- value: 16.525000000000002
851
  - type: map_at_10
852
- value: 23.435
853
  - type: map_at_100
854
- value: 24.535999999999998
855
  - type: map_at_1000
856
- value: 24.672
857
  - type: map_at_3
858
- value: 21.095
859
  - type: map_at_5
860
- value: 22.308
861
  - type: mrr_at_1
862
  value: 19.993
863
  - type: mrr_at_10
864
- value: 27.096999999999998
865
  - type: mrr_at_100
866
- value: 28.036
867
  - type: mrr_at_1000
868
- value: 28.119
869
  - type: mrr_at_3
870
- value: 24.971
871
  - type: mrr_at_5
872
- value: 26.062
873
  - type: ndcg_at_1
874
  value: 19.993
875
  - type: ndcg_at_10
876
- value: 28.002
877
  - type: ndcg_at_100
878
- value: 33.288000000000004
879
  - type: ndcg_at_1000
880
- value: 36.416
881
  - type: ndcg_at_3
882
- value: 23.768
883
  - type: ndcg_at_5
884
- value: 25.579
885
  - type: precision_at_1
886
  value: 19.993
887
  - type: precision_at_10
888
- value: 5.196
889
  - type: precision_at_100
890
- value: 0.922
891
  - type: precision_at_1000
892
- value: 0.136
893
  - type: precision_at_3
894
- value: 11.241
895
  - type: precision_at_5
896
- value: 8.176
897
  - type: recall_at_1
898
- value: 16.525000000000002
899
  - type: recall_at_10
900
- value: 38.082
901
  - type: recall_at_100
902
- value: 61.866
903
  - type: recall_at_1000
904
- value: 84.20100000000001
905
  - type: recall_at_3
906
- value: 26.228
907
  - type: recall_at_5
908
- value: 30.86
909
  - task:
910
  type: Retrieval
911
  dataset:
@@ -916,65 +916,65 @@ model-index:
916
  revision: None
917
  metrics:
918
  - type: map_at_1
919
- value: 25.480999999999998
920
  - type: map_at_10
921
- value: 34.319
922
  - type: map_at_100
923
- value: 35.54
924
  - type: map_at_1000
925
- value: 35.648
926
  - type: map_at_3
927
- value: 31.533
928
  - type: map_at_5
929
- value: 33.058
930
  - type: mrr_at_1
931
- value: 29.851
932
  - type: mrr_at_10
933
- value: 38.243
934
  - type: mrr_at_100
935
- value: 39.172000000000004
936
  - type: mrr_at_1000
937
- value: 39.235
938
  - type: mrr_at_3
939
- value: 35.697
940
  - type: mrr_at_5
941
- value: 37.147000000000006
942
  - type: ndcg_at_1
943
- value: 29.851
944
  - type: ndcg_at_10
945
- value: 39.653
946
  - type: ndcg_at_100
947
- value: 45.065
948
  - type: ndcg_at_1000
949
- value: 47.477999999999994
950
  - type: ndcg_at_3
951
- value: 34.481
952
  - type: ndcg_at_5
953
- value: 36.870999999999995
954
  - type: precision_at_1
955
- value: 29.851
956
  - type: precision_at_10
957
- value: 6.679
958
  - type: precision_at_100
959
- value: 1.053
960
  - type: precision_at_1000
961
  value: 0.13699999999999998
962
  - type: precision_at_3
963
- value: 15.485
964
  - type: precision_at_5
965
- value: 10.989
966
  - type: recall_at_1
967
- value: 25.480999999999998
968
  - type: recall_at_10
969
- value: 52.032000000000004
970
  - type: recall_at_100
971
- value: 75.193
972
  - type: recall_at_1000
973
- value: 91.958
974
  - type: recall_at_3
975
- value: 38.089
976
  - type: recall_at_5
977
- value: 43.947
978
  - task:
979
  type: Retrieval
980
  dataset:
@@ -985,65 +985,65 @@ model-index:
985
  revision: None
986
  metrics:
987
  - type: map_at_1
988
- value: 25.148
989
  - type: map_at_10
990
- value: 33.007
991
  - type: map_at_100
992
- value: 34.602
993
  - type: map_at_1000
994
- value: 34.809
995
  - type: map_at_3
996
- value: 30.014000000000003
997
  - type: map_at_5
998
- value: 31.728
999
  - type: mrr_at_1
1000
- value: 29.842000000000002
1001
  - type: mrr_at_10
1002
- value: 37.318
1003
  - type: mrr_at_100
1004
- value: 38.353
1005
  - type: mrr_at_1000
1006
- value: 38.41
1007
  - type: mrr_at_3
1008
- value: 34.75
1009
  - type: mrr_at_5
1010
- value: 36.163000000000004
1011
  - type: ndcg_at_1
1012
- value: 29.842000000000002
1013
  - type: ndcg_at_10
1014
- value: 38.462
1015
  - type: ndcg_at_100
1016
- value: 44.86
1017
  - type: ndcg_at_1000
1018
- value: 47.375
1019
  - type: ndcg_at_3
1020
- value: 33.614
1021
  - type: ndcg_at_5
1022
- value: 36.032
1023
  - type: precision_at_1
1024
- value: 29.842000000000002
1025
  - type: precision_at_10
1026
- value: 7.332
1027
  - type: precision_at_100
1028
- value: 1.52
1029
  - type: precision_at_1000
1030
- value: 0.23900000000000002
1031
  - type: precision_at_3
1032
- value: 15.547
1033
  - type: precision_at_5
1034
- value: 11.423
1035
  - type: recall_at_1
1036
- value: 25.148
1037
  - type: recall_at_10
1038
- value: 48.894
1039
  - type: recall_at_100
1040
- value: 77.845
1041
  - type: recall_at_1000
1042
- value: 93.74900000000001
1043
  - type: recall_at_3
1044
- value: 35.17
1045
  - type: recall_at_5
1046
- value: 41.734
1047
  - task:
1048
  type: Retrieval
1049
  dataset:
@@ -1054,65 +1054,65 @@ model-index:
1054
  revision: None
1055
  metrics:
1056
  - type: map_at_1
1057
- value: 17.723
1058
  - type: map_at_10
1059
- value: 25.586
1060
  - type: map_at_100
1061
- value: 26.648
1062
  - type: map_at_1000
1063
- value: 26.755000000000003
1064
  - type: map_at_3
1065
- value: 22.634999999999998
1066
  - type: map_at_5
1067
- value: 24.481
1068
  - type: mrr_at_1
1069
- value: 19.039
1070
  - type: mrr_at_10
1071
- value: 27.315
1072
  - type: mrr_at_100
1073
- value: 28.237000000000002
1074
  - type: mrr_at_1000
1075
- value: 28.32
1076
  - type: mrr_at_3
1077
- value: 24.368000000000002
1078
  - type: mrr_at_5
1079
- value: 26.198
1080
  - type: ndcg_at_1
1081
- value: 19.039
1082
  - type: ndcg_at_10
1083
- value: 30.511
1084
  - type: ndcg_at_100
1085
- value: 35.808
1086
  - type: ndcg_at_1000
1087
- value: 38.56
1088
  - type: ndcg_at_3
1089
- value: 24.762999999999998
1090
  - type: ndcg_at_5
1091
- value: 27.923
1092
  - type: precision_at_1
1093
- value: 19.039
1094
  - type: precision_at_10
1095
- value: 5.083
1096
  - type: precision_at_100
1097
- value: 0.839
1098
  - type: precision_at_1000
1099
- value: 0.11800000000000001
1100
  - type: precision_at_3
1101
- value: 10.659
1102
  - type: precision_at_5
1103
- value: 8.244
1104
  - type: recall_at_1
1105
- value: 17.723
1106
  - type: recall_at_10
1107
- value: 44.051
1108
  - type: recall_at_100
1109
- value: 68.659
1110
  - type: recall_at_1000
1111
- value: 89.164
1112
  - type: recall_at_3
1113
- value: 28.709
1114
  - type: recall_at_5
1115
- value: 36.331
1116
  - task:
1117
  type: Retrieval
1118
  dataset:
@@ -1123,65 +1123,65 @@ model-index:
1123
  revision: None
1124
  metrics:
1125
  - type: map_at_1
1126
- value: 13.669999999999998
1127
  - type: map_at_10
1128
- value: 23.46
1129
  - type: map_at_100
1130
- value: 25.304
1131
  - type: map_at_1000
1132
- value: 25.497999999999998
1133
  - type: map_at_3
1134
- value: 19.702
1135
  - type: map_at_5
1136
- value: 21.642
1137
  - type: mrr_at_1
1138
- value: 31.269999999999996
1139
  - type: mrr_at_10
1140
- value: 43.264
1141
  - type: mrr_at_100
1142
- value: 44.1
1143
  - type: mrr_at_1000
1144
- value: 44.134
1145
  - type: mrr_at_3
1146
- value: 40.011
1147
  - type: mrr_at_5
1148
- value: 42.079
1149
  - type: ndcg_at_1
1150
- value: 31.269999999999996
1151
  - type: ndcg_at_10
1152
- value: 32.385000000000005
1153
  - type: ndcg_at_100
1154
- value: 39.282000000000004
1155
  - type: ndcg_at_1000
1156
- value: 42.628
1157
  - type: ndcg_at_3
1158
- value: 26.942
1159
  - type: ndcg_at_5
1160
- value: 28.832
1161
  - type: precision_at_1
1162
- value: 31.269999999999996
1163
  - type: precision_at_10
1164
- value: 10.123999999999999
1165
  - type: precision_at_100
1166
- value: 1.748
1167
  - type: precision_at_1000
1168
- value: 0.23700000000000002
1169
  - type: precision_at_3
1170
- value: 20.282
1171
  - type: precision_at_5
1172
- value: 15.479000000000001
1173
  - type: recall_at_1
1174
- value: 13.669999999999998
1175
  - type: recall_at_10
1176
- value: 38.078
1177
  - type: recall_at_100
1178
- value: 61.651
1179
  - type: recall_at_1000
1180
- value: 80.279
1181
  - type: recall_at_3
1182
- value: 24.438
1183
  - type: recall_at_5
1184
- value: 30.244
1185
  - task:
1186
  type: Retrieval
1187
  dataset:
@@ -1192,65 +1192,65 @@ model-index:
1192
  revision: None
1193
  metrics:
1194
  - type: map_at_1
1195
- value: 9.103
1196
  - type: map_at_10
1197
- value: 19.238
1198
  - type: map_at_100
1199
- value: 26.451999999999998
1200
  - type: map_at_1000
1201
- value: 27.987000000000002
1202
  - type: map_at_3
1203
- value: 14.069999999999999
1204
  - type: map_at_5
1205
- value: 16.434
1206
  - type: mrr_at_1
1207
- value: 67.5
1208
  - type: mrr_at_10
1209
- value: 75.64800000000001
1210
  - type: mrr_at_100
1211
- value: 75.847
1212
  - type: mrr_at_1000
1213
- value: 75.85499999999999
1214
  - type: mrr_at_3
1215
- value: 73.833
1216
  - type: mrr_at_5
1217
- value: 74.933
1218
  - type: ndcg_at_1
1219
- value: 55.625
1220
  - type: ndcg_at_10
1221
- value: 40.505
1222
  - type: ndcg_at_100
1223
- value: 44.505
1224
  - type: ndcg_at_1000
1225
- value: 52.005
1226
  - type: ndcg_at_3
1227
- value: 45.841
1228
  - type: ndcg_at_5
1229
- value: 42.945
1230
  - type: precision_at_1
1231
- value: 67.5
1232
  - type: precision_at_10
1233
- value: 31.6
1234
  - type: precision_at_100
1235
- value: 9.83
1236
  - type: precision_at_1000
1237
- value: 1.9619999999999997
1238
  - type: precision_at_3
1239
- value: 49.083
1240
  - type: precision_at_5
1241
- value: 41.15
1242
  - type: recall_at_1
1243
- value: 9.103
1244
  - type: recall_at_10
1245
- value: 24.6
1246
  - type: recall_at_100
1247
- value: 50.075
1248
  - type: recall_at_1000
1249
- value: 73.516
1250
  - type: recall_at_3
1251
- value: 15.35
1252
  - type: recall_at_5
1253
- value: 19.217000000000002
1254
  - task:
1255
  type: Classification
1256
  dataset:
@@ -1261,9 +1261,9 @@ model-index:
1261
  revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
1262
  metrics:
1263
  - type: accuracy
1264
- value: 50.595
1265
  - type: f1
1266
- value: 45.43005573726517
1267
  - task:
1268
  type: Retrieval
1269
  dataset:
@@ -1274,65 +1274,65 @@ model-index:
1274
  revision: None
1275
  metrics:
1276
  - type: map_at_1
1277
- value: 76.08200000000001
1278
  - type: map_at_10
1279
- value: 83.697
1280
  - type: map_at_100
1281
- value: 83.891
1282
  - type: map_at_1000
1283
- value: 83.905
1284
  - type: map_at_3
1285
- value: 82.69
1286
  - type: map_at_5
1287
- value: 83.35900000000001
1288
  - type: mrr_at_1
1289
- value: 82.148
1290
  - type: mrr_at_10
1291
- value: 88.727
1292
  - type: mrr_at_100
1293
- value: 88.787
1294
  - type: mrr_at_1000
1295
- value: 88.788
1296
  - type: mrr_at_3
1297
- value: 88.054
1298
  - type: mrr_at_5
1299
- value: 88.547
1300
  - type: ndcg_at_1
1301
- value: 82.148
1302
  - type: ndcg_at_10
1303
- value: 87.274
1304
  - type: ndcg_at_100
1305
- value: 87.957
1306
  - type: ndcg_at_1000
1307
- value: 88.203
1308
  - type: ndcg_at_3
1309
- value: 85.744
1310
  - type: ndcg_at_5
1311
- value: 86.664
1312
  - type: precision_at_1
1313
- value: 82.148
1314
  - type: precision_at_10
1315
- value: 10.315000000000001
1316
  - type: precision_at_100
1317
- value: 1.086
1318
  - type: precision_at_1000
1319
- value: 0.11299999999999999
1320
  - type: precision_at_3
1321
- value: 32.458
1322
  - type: precision_at_5
1323
- value: 20.09
1324
  - type: recall_at_1
1325
- value: 76.08200000000001
1326
  - type: recall_at_10
1327
- value: 93.408
1328
  - type: recall_at_100
1329
- value: 96.11
1330
  - type: recall_at_1000
1331
- value: 97.626
1332
  - type: recall_at_3
1333
- value: 89.172
1334
  - type: recall_at_5
1335
- value: 91.604
1336
  - task:
1337
  type: Retrieval
1338
  dataset:
@@ -1343,65 +1343,65 @@ model-index:
1343
  revision: None
1344
  metrics:
1345
  - type: map_at_1
1346
- value: 19.377
1347
  - type: map_at_10
1348
- value: 31.785000000000004
1349
  - type: map_at_100
1350
- value: 33.511
1351
  - type: map_at_1000
1352
- value: 33.713
1353
  - type: map_at_3
1354
- value: 27.811999999999998
1355
  - type: map_at_5
1356
- value: 30.148000000000003
1357
  - type: mrr_at_1
1358
- value: 38.426
1359
  - type: mrr_at_10
1360
- value: 47.233000000000004
1361
  - type: mrr_at_100
1362
- value: 47.980000000000004
1363
  - type: mrr_at_1000
1364
- value: 48.022
1365
  - type: mrr_at_3
1366
- value: 44.856
1367
  - type: mrr_at_5
1368
- value: 46.322
1369
  - type: ndcg_at_1
1370
- value: 38.426
1371
  - type: ndcg_at_10
1372
- value: 39.326
1373
  - type: ndcg_at_100
1374
- value: 45.769999999999996
1375
  - type: ndcg_at_1000
1376
- value: 49.131
1377
  - type: ndcg_at_3
1378
- value: 36.1
1379
  - type: ndcg_at_5
1380
- value: 37.271
1381
  - type: precision_at_1
1382
- value: 38.426
1383
  - type: precision_at_10
1384
- value: 11.126999999999999
1385
  - type: precision_at_100
1386
- value: 1.7870000000000001
1387
  - type: precision_at_1000
1388
- value: 0.23700000000000002
1389
  - type: precision_at_3
1390
  value: 24.587999999999997
1391
  - type: precision_at_5
1392
- value: 18.21
1393
  - type: recall_at_1
1394
- value: 19.377
1395
  - type: recall_at_10
1396
- value: 45.484
1397
  - type: recall_at_100
1398
- value: 69.968
1399
  - type: recall_at_1000
1400
- value: 90.30799999999999
1401
  - type: recall_at_3
1402
- value: 32.72
1403
  - type: recall_at_5
1404
- value: 38.856
1405
  - task:
1406
  type: Retrieval
1407
  dataset:
@@ -1412,65 +1412,65 @@ model-index:
1412
  revision: None
1413
  metrics:
1414
  - type: map_at_1
1415
- value: 37.475
1416
  - type: map_at_10
1417
- value: 58.662000000000006
1418
  - type: map_at_100
1419
- value: 59.561
1420
  - type: map_at_1000
1421
- value: 59.626999999999995
1422
  - type: map_at_3
1423
- value: 55.496
1424
  - type: map_at_5
1425
- value: 57.464000000000006
1426
  - type: mrr_at_1
1427
- value: 74.949
1428
  - type: mrr_at_10
1429
- value: 80.976
1430
  - type: mrr_at_100
1431
- value: 81.215
1432
  - type: mrr_at_1000
1433
- value: 81.22399999999999
1434
  - type: mrr_at_3
1435
- value: 79.892
1436
  - type: mrr_at_5
1437
- value: 80.57
1438
  - type: ndcg_at_1
1439
- value: 74.949
1440
  - type: ndcg_at_10
1441
- value: 66.93599999999999
1442
  - type: ndcg_at_100
1443
- value: 70.137
1444
  - type: ndcg_at_1000
1445
- value: 71.452
1446
  - type: ndcg_at_3
1447
- value: 62.319
1448
  - type: ndcg_at_5
1449
- value: 64.866
1450
  - type: precision_at_1
1451
- value: 74.949
1452
  - type: precision_at_10
1453
- value: 13.988999999999999
1454
  - type: precision_at_100
1455
- value: 1.6500000000000001
1456
  - type: precision_at_1000
1457
- value: 0.182
1458
  - type: precision_at_3
1459
- value: 39.806000000000004
1460
  - type: precision_at_5
1461
- value: 25.899
1462
  - type: recall_at_1
1463
- value: 37.475
1464
  - type: recall_at_10
1465
- value: 69.946
1466
  - type: recall_at_100
1467
- value: 82.478
1468
  - type: recall_at_1000
1469
- value: 91.202
1470
  - type: recall_at_3
1471
- value: 59.709999999999994
1472
  - type: recall_at_5
1473
- value: 64.747
1474
  - task:
1475
  type: Classification
1476
  dataset:
@@ -1481,11 +1481,11 @@ model-index:
1481
  revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
1482
  metrics:
1483
  - type: accuracy
1484
- value: 89.2272
1485
  - type: ap
1486
- value: 84.69017509523854
1487
  - type: f1
1488
- value: 89.20673182133066
1489
  - task:
1490
  type: Retrieval
1491
  dataset:
@@ -1496,65 +1496,65 @@ model-index:
1496
  revision: None
1497
  metrics:
1498
  - type: map_at_1
1499
- value: 21.471999999999998
1500
  - type: map_at_10
1501
- value: 33.287
1502
  - type: map_at_100
1503
- value: 34.486
1504
  - type: map_at_1000
1505
- value: 34.536
1506
  - type: map_at_3
1507
- value: 29.520999999999997
1508
  - type: map_at_5
1509
- value: 31.647
1510
  - type: mrr_at_1
1511
- value: 22.076999999999998
1512
  - type: mrr_at_10
1513
- value: 33.902
1514
  - type: mrr_at_100
1515
- value: 35.037
1516
  - type: mrr_at_1000
1517
- value: 35.081
1518
  - type: mrr_at_3
1519
- value: 30.174
1520
  - type: mrr_at_5
1521
- value: 32.302
1522
  - type: ndcg_at_1
1523
- value: 22.092
1524
  - type: ndcg_at_10
1525
- value: 40.073
1526
  - type: ndcg_at_100
1527
- value: 45.82
1528
  - type: ndcg_at_1000
1529
- value: 47.097
1530
  - type: ndcg_at_3
1531
- value: 32.364
1532
  - type: ndcg_at_5
1533
- value: 36.179
1534
  - type: precision_at_1
1535
- value: 22.092
1536
  - type: precision_at_10
1537
- value: 6.36
1538
  - type: precision_at_100
1539
- value: 0.924
1540
  - type: precision_at_1000
1541
  value: 0.10300000000000001
1542
  - type: precision_at_3
1543
- value: 13.806
1544
  - type: precision_at_5
1545
- value: 10.223
1546
  - type: recall_at_1
1547
- value: 21.471999999999998
1548
  - type: recall_at_10
1549
- value: 60.971
1550
  - type: recall_at_100
1551
- value: 87.518
1552
  - type: recall_at_1000
1553
- value: 97.333
1554
  - type: recall_at_3
1555
- value: 39.961999999999996
1556
  - type: recall_at_5
1557
- value: 49.126
1558
  - task:
1559
  type: Classification
1560
  dataset:
@@ -1565,9 +1565,9 @@ model-index:
1565
  revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
1566
  metrics:
1567
  - type: accuracy
1568
- value: 94.44596443228454
1569
  - type: f1
1570
- value: 94.19326360848854
1571
  - task:
1572
  type: Classification
1573
  dataset:
@@ -1578,9 +1578,9 @@ model-index:
1578
  revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1579
  metrics:
1580
  - type: accuracy
1581
- value: 75.7934336525308
1582
  - type: f1
1583
- value: 57.619082395865604
1584
  - task:
1585
  type: Classification
1586
  dataset:
@@ -1591,9 +1591,9 @@ model-index:
1591
  revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
1592
  metrics:
1593
  - type: accuracy
1594
- value: 74.70410221923336
1595
  - type: f1
1596
- value: 72.82854233810865
1597
  - task:
1598
  type: Classification
1599
  dataset:
@@ -1604,9 +1604,9 @@ model-index:
1604
  revision: 7d571f92784cd94a019292a1f45445077d0ef634
1605
  metrics:
1606
  - type: accuracy
1607
- value: 78.61802286482852
1608
  - type: f1
1609
- value: 78.76695988384789
1610
  - task:
1611
  type: Clustering
1612
  dataset:
@@ -1617,7 +1617,7 @@ model-index:
1617
  revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
1618
  metrics:
1619
  - type: v_measure
1620
- value: 34.212621347614174
1621
  - task:
1622
  type: Clustering
1623
  dataset:
@@ -1628,7 +1628,7 @@ model-index:
1628
  revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
1629
  metrics:
1630
  - type: v_measure
1631
- value: 31.899728392028948
1632
  - task:
1633
  type: Reranking
1634
  dataset:
@@ -1639,9 +1639,9 @@ model-index:
1639
  revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
1640
  metrics:
1641
  - type: map
1642
- value: 32.190245086632466
1643
  - type: mrr
1644
- value: 33.424442963159876
1645
  - task:
1646
  type: Retrieval
1647
  dataset:
@@ -1652,65 +1652,65 @@ model-index:
1652
  revision: None
1653
  metrics:
1654
  - type: map_at_1
1655
- value: 6.141
1656
  - type: map_at_10
1657
- value: 13.558
1658
  - type: map_at_100
1659
- value: 17.238
1660
  - type: map_at_1000
1661
- value: 18.727
1662
  - type: map_at_3
1663
- value: 9.803
1664
  - type: map_at_5
1665
- value: 11.517
1666
  - type: mrr_at_1
1667
- value: 46.129999999999995
1668
  - type: mrr_at_10
1669
- value: 54.876999999999995
1670
  - type: mrr_at_100
1671
- value: 55.428999999999995
1672
  - type: mrr_at_1000
1673
- value: 55.47
1674
  - type: mrr_at_3
1675
- value: 52.993
1676
  - type: mrr_at_5
1677
- value: 54.107000000000006
1678
  - type: ndcg_at_1
1679
- value: 43.963
1680
  - type: ndcg_at_10
1681
- value: 35.72
1682
  - type: ndcg_at_100
1683
- value: 32.792
1684
  - type: ndcg_at_1000
1685
- value: 41.52
1686
  - type: ndcg_at_3
1687
- value: 40.929
1688
  - type: ndcg_at_5
1689
- value: 38.664
1690
  - type: precision_at_1
1691
- value: 45.82
1692
  - type: precision_at_10
1693
- value: 26.625
1694
  - type: precision_at_100
1695
- value: 8.387
1696
  - type: precision_at_1000
1697
  value: 2.131
1698
  - type: precision_at_3
1699
- value: 38.39
1700
  - type: precision_at_5
1701
- value: 33.56
1702
  - type: recall_at_1
1703
- value: 6.141
1704
  - type: recall_at_10
1705
- value: 17.598
1706
  - type: recall_at_100
1707
- value: 33.619
1708
  - type: recall_at_1000
1709
- value: 64.455
1710
  - type: recall_at_3
1711
- value: 10.667
1712
  - type: recall_at_5
1713
- value: 13.492999999999999
1714
  - task:
1715
  type: Retrieval
1716
  dataset:
@@ -1721,65 +1721,65 @@ model-index:
1721
  revision: None
1722
  metrics:
1723
  - type: map_at_1
1724
- value: 26.019
1725
  - type: map_at_10
1726
- value: 40.644999999999996
1727
  - type: map_at_100
1728
- value: 41.870000000000005
1729
  - type: map_at_1000
1730
- value: 41.904
1731
  - type: map_at_3
1732
- value: 36.28
1733
  - type: map_at_5
1734
- value: 38.830999999999996
1735
  - type: mrr_at_1
1736
- value: 29.664
1737
  - type: mrr_at_10
1738
- value: 43.168
1739
  - type: mrr_at_100
1740
- value: 44.126
1741
  - type: mrr_at_1000
1742
- value: 44.151
1743
  - type: mrr_at_3
1744
- value: 39.484
1745
  - type: mrr_at_5
1746
- value: 41.702
1747
  - type: ndcg_at_1
1748
- value: 29.635
1749
  - type: ndcg_at_10
1750
- value: 48.284
1751
  - type: ndcg_at_100
1752
- value: 53.522999999999996
1753
  - type: ndcg_at_1000
1754
- value: 54.344
1755
  - type: ndcg_at_3
1756
- value: 40.048
1757
  - type: ndcg_at_5
1758
- value: 44.329
1759
  - type: precision_at_1
1760
- value: 29.635
1761
  - type: precision_at_10
1762
- value: 8.262
1763
  - type: precision_at_100
1764
- value: 1.1159999999999999
1765
  - type: precision_at_1000
1766
  value: 0.11900000000000001
1767
  - type: precision_at_3
1768
- value: 18.54
1769
  - type: precision_at_5
1770
- value: 13.586
1771
  - type: recall_at_1
1772
- value: 26.019
1773
  - type: recall_at_10
1774
- value: 69.049
1775
  - type: recall_at_100
1776
- value: 91.89399999999999
1777
  - type: recall_at_1000
1778
- value: 98.095
1779
  - type: recall_at_3
1780
- value: 47.81
1781
  - type: recall_at_5
1782
- value: 57.645
1783
  - task:
1784
  type: Retrieval
1785
  dataset:
@@ -1790,65 +1790,65 @@ model-index:
1790
  revision: None
1791
  metrics:
1792
  - type: map_at_1
1793
- value: 70.952
1794
  - type: map_at_10
1795
- value: 84.895
1796
  - type: map_at_100
1797
- value: 85.51299999999999
1798
  - type: map_at_1000
1799
- value: 85.529
1800
  - type: map_at_3
1801
- value: 81.94500000000001
1802
  - type: map_at_5
1803
- value: 83.83500000000001
1804
  - type: mrr_at_1
1805
- value: 81.65
1806
  - type: mrr_at_10
1807
- value: 87.756
1808
  - type: mrr_at_100
1809
- value: 87.855
1810
  - type: mrr_at_1000
1811
- value: 87.856
1812
  - type: mrr_at_3
1813
- value: 86.822
1814
  - type: mrr_at_5
1815
- value: 87.473
1816
  - type: ndcg_at_1
1817
- value: 81.65
1818
  - type: ndcg_at_10
1819
- value: 88.563
1820
  - type: ndcg_at_100
1821
- value: 89.74499999999999
1822
  - type: ndcg_at_1000
1823
- value: 89.84400000000001
1824
  - type: ndcg_at_3
1825
- value: 85.782
1826
  - type: ndcg_at_5
1827
- value: 87.381
1828
  - type: precision_at_1
1829
- value: 81.65
1830
  - type: precision_at_10
1831
- value: 13.435
1832
  - type: precision_at_100
1833
- value: 1.529
1834
  - type: precision_at_1000
1835
  value: 0.157
1836
  - type: precision_at_3
1837
- value: 37.523
1838
  - type: precision_at_5
1839
- value: 24.72
1840
  - type: recall_at_1
1841
- value: 70.952
1842
  - type: recall_at_10
1843
- value: 95.521
1844
  - type: recall_at_100
1845
- value: 99.53699999999999
1846
  - type: recall_at_1000
1847
- value: 99.983
1848
  - type: recall_at_3
1849
- value: 87.559
1850
  - type: recall_at_5
1851
- value: 92.038
1852
  - task:
1853
  type: Clustering
1854
  dataset:
@@ -1859,7 +1859,7 @@ model-index:
1859
  revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
1860
  metrics:
1861
  - type: v_measure
1862
- value: 54.61973943122806
1863
  - task:
1864
  type: Clustering
1865
  dataset:
@@ -1870,7 +1870,7 @@ model-index:
1870
  revision: 282350215ef01743dc01b456c7f5241fa8937f16
1871
  metrics:
1872
  - type: v_measure
1873
- value: 60.92179806944469
1874
  - task:
1875
  type: Retrieval
1876
  dataset:
@@ -1881,65 +1881,65 @@ model-index:
1881
  revision: None
1882
  metrics:
1883
  - type: map_at_1
1884
- value: 4.993
1885
  - type: map_at_10
1886
- value: 13.175999999999998
1887
  - type: map_at_100
1888
- value: 15.689
1889
  - type: map_at_1000
1890
- value: 16.054
1891
  - type: map_at_3
1892
- value: 9.325999999999999
1893
  - type: map_at_5
1894
- value: 11.283
1895
  - type: mrr_at_1
1896
- value: 24.7
1897
  - type: mrr_at_10
1898
- value: 36.568
1899
  - type: mrr_at_100
1900
- value: 37.667
1901
  - type: mrr_at_1000
1902
- value: 37.714
1903
  - type: mrr_at_3
1904
- value: 32.933
1905
  - type: mrr_at_5
1906
- value: 34.963
1907
  - type: ndcg_at_1
1908
- value: 24.7
1909
  - type: ndcg_at_10
1910
- value: 21.839
1911
  - type: ndcg_at_100
1912
- value: 31.057000000000002
1913
  - type: ndcg_at_1000
1914
- value: 36.962
1915
  - type: ndcg_at_3
1916
- value: 20.623
1917
  - type: ndcg_at_5
1918
- value: 18.107
1919
  - type: precision_at_1
1920
- value: 24.7
1921
  - type: precision_at_10
1922
- value: 11.360000000000001
1923
  - type: precision_at_100
1924
- value: 2.4619999999999997
1925
  - type: precision_at_1000
1926
- value: 0.388
1927
  - type: precision_at_3
1928
- value: 19.267
1929
  - type: precision_at_5
1930
- value: 15.959999999999999
1931
  - type: recall_at_1
1932
- value: 4.993
1933
  - type: recall_at_10
1934
- value: 22.982
1935
  - type: recall_at_100
1936
- value: 49.97
1937
  - type: recall_at_1000
1938
- value: 78.623
1939
  - type: recall_at_3
1940
- value: 11.716999999999999
1941
  - type: recall_at_5
1942
- value: 16.172
1943
  - task:
1944
  type: STS
1945
  dataset:
@@ -1950,17 +1950,17 @@ model-index:
1950
  revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
1951
  metrics:
1952
  - type: cos_sim_pearson
1953
- value: 85.71899431421795
1954
  - type: cos_sim_spearman
1955
- value: 80.46430776062674
1956
  - type: euclidean_pearson
1957
- value: 83.02871101280735
1958
  - type: euclidean_spearman
1959
- value: 80.49525009964952
1960
  - type: manhattan_pearson
1961
- value: 82.96176477360466
1962
  - type: manhattan_spearman
1963
- value: 80.4038922852272
1964
  - task:
1965
  type: STS
1966
  dataset:
@@ -1971,17 +1971,17 @@ model-index:
1971
  revision: a0d554a64d88156834ff5ae9920b964011b16384
1972
  metrics:
1973
  - type: cos_sim_pearson
1974
- value: 85.4473643076464
1975
  - type: cos_sim_spearman
1976
- value: 76.2648833265373
1977
  - type: euclidean_pearson
1978
- value: 82.5498605585181
1979
  - type: euclidean_spearman
1980
- value: 76.06458177068038
1981
  - type: manhattan_pearson
1982
- value: 82.55572570767087
1983
  - type: manhattan_spearman
1984
- value: 76.1267237133785
1985
  - task:
1986
  type: STS
1987
  dataset:
@@ -1992,17 +1992,17 @@ model-index:
1992
  revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
1993
  metrics:
1994
  - type: cos_sim_pearson
1995
- value: 85.24858438337428
1996
  - type: cos_sim_spearman
1997
- value: 86.42907705680409
1998
  - type: euclidean_pearson
1999
- value: 85.50673274898077
2000
  - type: euclidean_spearman
2001
- value: 86.50066760759493
2002
  - type: manhattan_pearson
2003
- value: 85.38098024332331
2004
  - type: manhattan_spearman
2005
- value: 86.3179935859058
2006
  - task:
2007
  type: STS
2008
  dataset:
@@ -2013,17 +2013,17 @@ model-index:
2013
  revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
2014
  metrics:
2015
  - type: cos_sim_pearson
2016
- value: 84.97052112858252
2017
  - type: cos_sim_spearman
2018
- value: 82.97007079944963
2019
  - type: euclidean_pearson
2020
- value: 84.49118913390151
2021
  - type: euclidean_spearman
2022
- value: 82.89912124589944
2023
  - type: manhattan_pearson
2024
- value: 84.45725470158602
2025
  - type: manhattan_spearman
2026
- value: 82.89422444440467
2027
  - task:
2028
  type: STS
2029
  dataset:
@@ -2034,17 +2034,17 @@ model-index:
2034
  revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
2035
  metrics:
2036
  - type: cos_sim_pearson
2037
- value: 87.44702160696032
2038
  - type: cos_sim_spearman
2039
- value: 88.75678661413305
2040
  - type: euclidean_pearson
2041
- value: 88.22046240533754
2042
  - type: euclidean_spearman
2043
- value: 88.78103010580752
2044
  - type: manhattan_pearson
2045
- value: 88.15576644132916
2046
  - type: manhattan_spearman
2047
- value: 88.72891963379698
2048
  - task:
2049
  type: STS
2050
  dataset:
@@ -2055,17 +2055,17 @@ model-index:
2055
  revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
2056
  metrics:
2057
  - type: cos_sim_pearson
2058
- value: 83.25112584874732
2059
  - type: cos_sim_spearman
2060
- value: 85.0642487018319
2061
  - type: euclidean_pearson
2062
- value: 84.37279427321502
2063
  - type: euclidean_spearman
2064
- value: 85.074198902509
2065
  - type: manhattan_pearson
2066
- value: 84.19323050597049
2067
  - type: manhattan_spearman
2068
- value: 84.88383717319327
2069
  - task:
2070
  type: STS
2071
  dataset:
@@ -2076,17 +2076,17 @@ model-index:
2076
  revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
2077
  metrics:
2078
  - type: cos_sim_pearson
2079
- value: 88.87357291874198
2080
  - type: cos_sim_spearman
2081
- value: 89.1113081854716
2082
  - type: euclidean_pearson
2083
- value: 89.61137598923361
2084
  - type: euclidean_spearman
2085
- value: 89.13391070267475
2086
  - type: manhattan_pearson
2087
- value: 89.62382071829829
2088
  - type: manhattan_spearman
2089
- value: 89.1997962715288
2090
  - task:
2091
  type: STS
2092
  dataset:
@@ -2097,17 +2097,17 @@ model-index:
2097
  revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
2098
  metrics:
2099
  - type: cos_sim_pearson
2100
- value: 67.1205707180893
2101
  - type: cos_sim_spearman
2102
- value: 68.16260851835224
2103
  - type: euclidean_pearson
2104
- value: 68.87294373141141
2105
  - type: euclidean_spearman
2106
- value: 67.98447223948163
2107
  - type: manhattan_pearson
2108
- value: 68.98950941915248
2109
  - type: manhattan_spearman
2110
- value: 68.29388343776796
2111
  - task:
2112
  type: STS
2113
  dataset:
@@ -2118,17 +2118,17 @@ model-index:
2118
  revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
2119
  metrics:
2120
  - type: cos_sim_pearson
2121
- value: 85.9949201588004
2122
  - type: cos_sim_spearman
2123
- value: 87.31663820432567
2124
  - type: euclidean_pearson
2125
- value: 87.27979534770259
2126
  - type: euclidean_spearman
2127
- value: 87.31872069375427
2128
  - type: manhattan_pearson
2129
- value: 87.0783256942344
2130
  - type: manhattan_spearman
2131
- value: 87.16038562428714
2132
  - task:
2133
  type: Reranking
2134
  dataset:
@@ -2139,9 +2139,9 @@ model-index:
2139
  revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
2140
  metrics:
2141
  - type: map
2142
- value: 86.08173708317305
2143
  - type: mrr
2144
- value: 95.93575179359493
2145
  - task:
2146
  type: Retrieval
2147
  dataset:
@@ -2152,65 +2152,65 @@ model-index:
2152
  revision: None
2153
  metrics:
2154
  - type: map_at_1
2155
- value: 57.65
2156
  - type: map_at_10
2157
- value: 67.19000000000001
2158
  - type: map_at_100
2159
- value: 67.772
2160
  - type: map_at_1000
2161
- value: 67.805
2162
  - type: map_at_3
2163
- value: 64.14800000000001
2164
  - type: map_at_5
2165
- value: 65.745
2166
  - type: mrr_at_1
2167
- value: 60.333000000000006
2168
  - type: mrr_at_10
2169
- value: 68.158
2170
  - type: mrr_at_100
2171
- value: 68.583
2172
  - type: mrr_at_1000
2173
- value: 68.613
2174
  - type: mrr_at_3
2175
- value: 65.72200000000001
2176
  - type: mrr_at_5
2177
- value: 67.039
2178
  - type: ndcg_at_1
2179
- value: 60.333000000000006
2180
  - type: ndcg_at_10
2181
- value: 71.69200000000001
2182
  - type: ndcg_at_100
2183
- value: 74.064
2184
  - type: ndcg_at_1000
2185
- value: 74.694
2186
  - type: ndcg_at_3
2187
- value: 66.378
2188
  - type: ndcg_at_5
2189
- value: 68.73
2190
  - type: precision_at_1
2191
- value: 60.333000000000006
2192
  - type: precision_at_10
2193
- value: 9.533
2194
  - type: precision_at_100
2195
- value: 1.08
2196
  - type: precision_at_1000
2197
  value: 0.11299999999999999
2198
  - type: precision_at_3
2199
- value: 25.556
2200
  - type: precision_at_5
2201
  value: 17.0
2202
  - type: recall_at_1
2203
- value: 57.65
2204
  - type: recall_at_10
2205
- value: 84.56700000000001
2206
  - type: recall_at_100
2207
- value: 95.167
2208
  - type: recall_at_1000
2209
- value: 99.667
2210
  - type: recall_at_3
2211
- value: 70.272
2212
  - type: recall_at_5
2213
- value: 76.11099999999999
2214
  - task:
2215
  type: PairClassification
2216
  dataset:
@@ -2221,51 +2221,51 @@ model-index:
2221
  revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
2222
  metrics:
2223
  - type: cos_sim_accuracy
2224
- value: 99.83663366336634
2225
  - type: cos_sim_ap
2226
- value: 96.13854487816917
2227
  - type: cos_sim_f1
2228
- value: 91.77057356608479
2229
  - type: cos_sim_precision
2230
- value: 91.54228855721394
2231
  - type: cos_sim_recall
2232
- value: 92.0
2233
  - type: dot_accuracy
2234
- value: 99.83663366336634
2235
  - type: dot_ap
2236
- value: 96.29459284844314
2237
  - type: dot_f1
2238
- value: 91.6030534351145
2239
  - type: dot_precision
2240
- value: 93.26424870466322
2241
  - type: dot_recall
2242
- value: 90.0
2243
  - type: euclidean_accuracy
2244
- value: 99.83564356435643
2245
  - type: euclidean_ap
2246
- value: 96.09957152523418
2247
  - type: euclidean_f1
2248
- value: 91.7
2249
  - type: euclidean_precision
2250
- value: 91.7
2251
  - type: euclidean_recall
2252
- value: 91.7
2253
  - type: manhattan_accuracy
2254
- value: 99.83663366336634
2255
  - type: manhattan_ap
2256
- value: 96.09579952373399
2257
  - type: manhattan_f1
2258
- value: 91.72932330827068
2259
  - type: manhattan_precision
2260
- value: 91.95979899497488
2261
  - type: manhattan_recall
2262
- value: 91.5
2263
  - type: max_accuracy
2264
- value: 99.83663366336634
2265
  - type: max_ap
2266
- value: 96.29459284844314
2267
  - type: max_f1
2268
- value: 91.77057356608479
2269
  - task:
2270
  type: Clustering
2271
  dataset:
@@ -2276,7 +2276,7 @@ model-index:
2276
  revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2277
  metrics:
2278
  - type: v_measure
2279
- value: 61.270213664772385
2280
  - task:
2281
  type: Clustering
2282
  dataset:
@@ -2287,7 +2287,7 @@ model-index:
2287
  revision: 815ca46b2622cec33ccafc3735d572c266efdb44
2288
  metrics:
2289
  - type: v_measure
2290
- value: 35.23973443659002
2291
  - task:
2292
  type: Reranking
2293
  dataset:
@@ -2298,9 +2298,9 @@ model-index:
2298
  revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
2299
  metrics:
2300
  - type: map
2301
- value: 53.40061413824656
2302
  - type: mrr
2303
- value: 54.28819444444445
2304
  - task:
2305
  type: Summarization
2306
  dataset:
@@ -2311,13 +2311,13 @@ model-index:
2311
  revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
2312
  metrics:
2313
  - type: cos_sim_pearson
2314
- value: 30.59314409717665
2315
  - type: cos_sim_spearman
2316
- value: 30.573109955748677
2317
  - type: dot_pearson
2318
- value: 30.884662900409722
2319
  - type: dot_spearman
2320
- value: 30.778591618272262
2321
  - task:
2322
  type: Retrieval
2323
  dataset:
@@ -2328,65 +2328,65 @@ model-index:
2328
  revision: None
2329
  metrics:
2330
  - type: map_at_1
2331
- value: 0.20400000000000001
2332
  - type: map_at_10
2333
- value: 1.7229999999999999
2334
  - type: map_at_100
2335
- value: 9.185
2336
  - type: map_at_1000
2337
- value: 23.019000000000002
2338
  - type: map_at_3
2339
- value: 0.596
2340
  - type: map_at_5
2341
- value: 0.9339999999999999
2342
  - type: mrr_at_1
2343
  value: 78.0
2344
  - type: mrr_at_10
2345
- value: 85.5
2346
  - type: mrr_at_100
2347
- value: 85.682
2348
  - type: mrr_at_1000
2349
- value: 85.682
2350
  - type: mrr_at_3
2351
- value: 84.0
2352
  - type: mrr_at_5
2353
- value: 85.5
2354
  - type: ndcg_at_1
2355
- value: 73.0
2356
  - type: ndcg_at_10
2357
- value: 68.28
2358
  - type: ndcg_at_100
2359
- value: 52.239000000000004
2360
  - type: ndcg_at_1000
2361
- value: 48.217
2362
  - type: ndcg_at_3
2363
- value: 72.603
2364
  - type: ndcg_at_5
2365
- value: 70.64099999999999
2366
  - type: precision_at_1
2367
  value: 78.0
2368
  - type: precision_at_10
2369
- value: 72.39999999999999
2370
  - type: precision_at_100
2371
- value: 53.459999999999994
2372
  - type: precision_at_1000
2373
- value: 21.254
2374
  - type: precision_at_3
2375
- value: 78.0
2376
  - type: precision_at_5
2377
- value: 74.8
2378
  - type: recall_at_1
2379
- value: 0.20400000000000001
2380
  - type: recall_at_10
2381
- value: 1.939
2382
  - type: recall_at_100
2383
- value: 12.831000000000001
2384
  - type: recall_at_1000
2385
- value: 45.572
2386
  - type: recall_at_3
2387
- value: 0.628
2388
  - type: recall_at_5
2389
- value: 1.004
2390
  - task:
2391
  type: Retrieval
2392
  dataset:
@@ -2397,65 +2397,65 @@ model-index:
2397
  revision: None
2398
  metrics:
2399
  - type: map_at_1
2400
- value: 1.693
2401
  - type: map_at_10
2402
- value: 7.7410000000000005
2403
  - type: map_at_100
2404
- value: 13.778000000000002
2405
  - type: map_at_1000
2406
- value: 15.328
2407
  - type: map_at_3
2408
- value: 4.361000000000001
2409
  - type: map_at_5
2410
- value: 5.534
2411
  - type: mrr_at_1
2412
- value: 20.408
2413
  - type: mrr_at_10
2414
- value: 37.008
2415
  - type: mrr_at_100
2416
- value: 38.198
2417
  - type: mrr_at_1000
2418
- value: 38.216
2419
  - type: mrr_at_3
2420
- value: 32.993
2421
  - type: mrr_at_5
2422
- value: 34.83
2423
  - type: ndcg_at_1
2424
- value: 18.367
2425
  - type: ndcg_at_10
2426
- value: 19.676
2427
  - type: ndcg_at_100
2428
- value: 33.421
2429
  - type: ndcg_at_1000
2430
- value: 45.123999999999995
2431
  - type: ndcg_at_3
2432
- value: 22.109
2433
  - type: ndcg_at_5
2434
- value: 20.166999999999998
2435
  - type: precision_at_1
2436
- value: 20.408
2437
  - type: precision_at_10
2438
- value: 17.551
2439
  - type: precision_at_100
2440
- value: 7.286
2441
  - type: precision_at_1000
2442
- value: 1.516
2443
  - type: precision_at_3
2444
- value: 23.810000000000002
2445
  - type: precision_at_5
2446
- value: 20.408
2447
  - type: recall_at_1
2448
- value: 1.693
2449
  - type: recall_at_10
2450
- value: 13.485
2451
  - type: recall_at_100
2452
- value: 46.361000000000004
2453
  - type: recall_at_1000
2454
- value: 81.997
2455
  - type: recall_at_3
2456
- value: 5.432
2457
  - type: recall_at_5
2458
- value: 7.797
2459
  - task:
2460
  type: Classification
2461
  dataset:
@@ -2466,11 +2466,11 @@ model-index:
2466
  revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
2467
  metrics:
2468
  - type: accuracy
2469
- value: 70.6774
2470
  - type: ap
2471
- value: 14.243691983984998
2472
  - type: f1
2473
- value: 54.45105895755751
2474
  - task:
2475
  type: Classification
2476
  dataset:
@@ -2481,9 +2481,9 @@ model-index:
2481
  revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
2482
  metrics:
2483
  - type: accuracy
2484
- value: 60.0509337860781
2485
  - type: f1
2486
- value: 60.424197644605236
2487
  - task:
2488
  type: Clustering
2489
  dataset:
@@ -2494,7 +2494,7 @@ model-index:
2494
  revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
2495
  metrics:
2496
  - type: v_measure
2497
- value: 49.94452711339773
2498
  - task:
2499
  type: PairClassification
2500
  dataset:
@@ -2505,51 +2505,51 @@ model-index:
2505
  revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
2506
  metrics:
2507
  - type: cos_sim_accuracy
2508
- value: 85.75430649102938
2509
  - type: cos_sim_ap
2510
- value: 73.38576407567363
2511
  - type: cos_sim_f1
2512
- value: 67.47549019607844
2513
  - type: cos_sim_precision
2514
- value: 62.99771167048055
2515
  - type: cos_sim_recall
2516
- value: 72.63852242744063
2517
  - type: dot_accuracy
2518
- value: 85.67681945520653
2519
  - type: dot_ap
2520
- value: 73.37650773516077
2521
  - type: dot_f1
2522
- value: 67.56520653937352
2523
  - type: dot_precision
2524
- value: 64.1013497513616
2525
  - type: dot_recall
2526
- value: 71.42480211081794
2527
  - type: euclidean_accuracy
2528
- value: 85.76622757346367
2529
  - type: euclidean_ap
2530
- value: 73.31834510956003
2531
  - type: euclidean_f1
2532
- value: 67.40331491712708
2533
  - type: euclidean_precision
2534
- value: 60.780156879372484
2535
  - type: euclidean_recall
2536
- value: 75.64643799472296
2537
  - type: manhattan_accuracy
2538
- value: 85.73046432616081
2539
  - type: manhattan_ap
2540
- value: 73.10120518588954
2541
  - type: manhattan_f1
2542
- value: 67.34183545886471
2543
  - type: manhattan_precision
2544
- value: 63.997148288973385
2545
  - type: manhattan_recall
2546
- value: 71.05540897097626
2547
  - type: max_accuracy
2548
- value: 85.76622757346367
2549
  - type: max_ap
2550
- value: 73.38576407567363
2551
  - type: max_f1
2552
- value: 67.56520653937352
2553
  - task:
2554
  type: PairClassification
2555
  dataset:
@@ -2560,51 +2560,51 @@ model-index:
2560
  revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
2561
  metrics:
2562
  - type: cos_sim_accuracy
2563
- value: 88.71424690495596
2564
  - type: cos_sim_ap
2565
- value: 85.42819672981983
2566
  - type: cos_sim_f1
2567
- value: 77.76150014649868
2568
  - type: cos_sim_precision
2569
- value: 74.15479184129646
2570
  - type: cos_sim_recall
2571
- value: 81.73698798891284
2572
  - type: dot_accuracy
2573
- value: 88.45810532852097
2574
  - type: dot_ap
2575
- value: 84.78667227857513
2576
  - type: dot_f1
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- value: 77.29539996305192
2578
  - type: dot_precision
2579
- value: 74.30560488740498
2580
  - type: dot_recall
2581
- value: 80.53587927317524
2582
  - type: euclidean_accuracy
2583
- value: 88.73171110334924
2584
  - type: euclidean_ap
2585
- value: 85.46052151213301
2586
  - type: euclidean_f1
2587
- value: 77.79939075861563
2588
  - type: euclidean_precision
2589
- value: 74.33200084157374
2590
  - type: euclidean_recall
2591
- value: 81.60609793655682
2592
  - type: manhattan_accuracy
2593
- value: 88.75111576823068
2594
  - type: manhattan_ap
2595
- value: 85.4412901701619
2596
  - type: manhattan_f1
2597
- value: 77.72423325488437
2598
  - type: manhattan_precision
2599
- value: 75.48799071184965
2600
  - type: manhattan_recall
2601
- value: 80.09701262704034
2602
  - type: max_accuracy
2603
- value: 88.75111576823068
2604
  - type: max_ap
2605
- value: 85.46052151213301
2606
  - type: max_f1
2607
- value: 77.79939075861563
2608
  ---
2609
  <h1 align="center">GIST small Embedding v0</h1>
2610
 
 
23
  revision: e8379541af4e31359cca9fbcf4b00f2671dba205
24
  metrics:
25
  - type: accuracy
26
+ value: 75.26865671641791
27
  - type: ap
28
+ value: 38.25623793370476
29
  - type: f1
30
+ value: 69.26434651320257
31
  - task:
32
  type: Classification
33
  dataset:
 
38
  revision: e2d317d38cd51312af73b3d32a06d1a08b442046
39
  metrics:
40
  - type: accuracy
41
+ value: 93.232225
42
  - type: ap
43
+ value: 89.97936072879344
44
  - type: f1
45
+ value: 93.22122653806187
46
  - task:
47
  type: Classification
48
  dataset:
 
53
  revision: 1399c76144fd37290681b995c656ef9b2e06e26d
54
  metrics:
55
  - type: accuracy
56
+ value: 49.715999999999994
57
  - type: f1
58
+ value: 49.169789920136076
59
  - task:
60
  type: Retrieval
61
  dataset:
 
66
  revision: None
67
  metrics:
68
  - type: map_at_1
69
+ value: 34.922
70
  - type: map_at_10
71
+ value: 50.524
72
  - type: map_at_100
73
+ value: 51.247
74
  - type: map_at_1000
75
+ value: 51.249
76
  - type: map_at_3
77
+ value: 45.887
78
  - type: map_at_5
79
+ value: 48.592999999999996
80
  - type: mrr_at_1
81
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82
  - type: mrr_at_10
83
+ value: 50.382000000000005
84
  - type: mrr_at_100
85
+ value: 51.104000000000006
86
  - type: mrr_at_1000
87
+ value: 51.105999999999995
88
  - type: mrr_at_3
89
+ value: 45.733000000000004
90
  - type: mrr_at_5
91
+ value: 48.428
92
  - type: ndcg_at_1
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  - type: ndcg_at_10
95
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96
  - type: ndcg_at_100
97
+ value: 62.083999999999996
98
  - type: ndcg_at_1000
99
+ value: 62.137
100
  - type: ndcg_at_3
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  - type: ndcg_at_5
103
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104
  - type: precision_at_1
105
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106
  - type: precision_at_10
107
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  - type: precision_at_100
109
+ value: 0.991
110
  - type: precision_at_1000
111
  value: 0.1
112
  - type: precision_at_3
113
+ value: 20.152
114
  - type: precision_at_5
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+ value: 14.466999999999999
116
  - type: recall_at_1
117
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  - type: recall_at_10
119
+ value: 86.48599999999999
120
  - type: recall_at_100
121
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122
  - type: recall_at_1000
123
+ value: 99.57300000000001
124
  - type: recall_at_3
125
+ value: 60.455000000000005
126
  - type: recall_at_5
127
+ value: 72.333
128
  - task:
129
  type: Clustering
130
  dataset:
 
135
  revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
136
  metrics:
137
  - type: v_measure
138
+ value: 47.623282347623714
139
  - task:
140
  type: Clustering
141
  dataset:
 
146
  revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
147
  metrics:
148
  - type: v_measure
149
+ value: 39.86487843524932
150
  - task:
151
  type: Reranking
152
  dataset:
 
157
  revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
158
  metrics:
159
  - type: map
160
+ value: 62.3290291318171
161
  - type: mrr
162
+ value: 75.2379853141626
163
  - task:
164
  type: STS
165
  dataset:
 
170
  revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
171
  metrics:
172
  - type: cos_sim_pearson
173
+ value: 88.52002953574285
174
  - type: cos_sim_spearman
175
+ value: 86.98752423842483
176
  - type: euclidean_pearson
177
+ value: 86.89442688314197
178
  - type: euclidean_spearman
179
+ value: 86.88631711307471
180
  - type: manhattan_pearson
181
+ value: 87.03723618507175
182
  - type: manhattan_spearman
183
+ value: 86.76041062975224
184
  - task:
185
  type: Classification
186
  dataset:
 
191
  revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
192
  metrics:
193
  - type: accuracy
194
+ value: 86.64935064935065
195
  - type: f1
196
+ value: 86.61903824934998
197
  - task:
198
  type: Clustering
199
  dataset:
 
204
  revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
205
  metrics:
206
  - type: v_measure
207
+ value: 39.21904455377494
208
  - task:
209
  type: Clustering
210
  dataset:
 
215
  revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
216
  metrics:
217
  - type: v_measure
218
+ value: 35.43342755570654
219
  - task:
220
  type: Retrieval
221
  dataset:
 
226
  revision: None
227
  metrics:
228
  - type: map_at_1
229
+ value: 31.843
230
  - type: map_at_10
231
+ value: 43.379
232
  - type: map_at_100
233
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234
  - type: map_at_1000
235
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  - type: map_at_3
237
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238
  - type: map_at_5
239
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240
  - type: mrr_at_1
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242
  - type: mrr_at_10
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244
  - type: mrr_at_100
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246
  - type: mrr_at_1000
247
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  - type: mrr_at_3
249
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  - type: mrr_at_5
251
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252
  - type: ndcg_at_1
253
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254
  - type: ndcg_at_10
255
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256
  - type: ndcg_at_100
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258
  - type: ndcg_at_1000
259
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260
  - type: ndcg_at_3
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262
  - type: ndcg_at_5
263
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264
  - type: precision_at_1
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266
  - type: precision_at_10
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268
  - type: precision_at_100
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270
  - type: precision_at_1000
271
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272
  - type: precision_at_3
273
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  - type: precision_at_5
275
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276
  - type: recall_at_1
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278
  - type: recall_at_10
279
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280
  - type: recall_at_100
281
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282
  - type: recall_at_1000
283
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284
  - type: recall_at_3
285
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286
  - type: recall_at_5
287
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288
  - task:
289
  type: Retrieval
290
  dataset:
 
295
  revision: None
296
  metrics:
297
  - type: map_at_1
298
+ value: 29.321
299
  - type: map_at_10
300
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301
  - type: map_at_100
302
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303
  - type: map_at_1000
304
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305
  - type: map_at_3
306
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307
  - type: map_at_5
308
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309
  - type: mrr_at_1
310
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311
  - type: mrr_at_10
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313
  - type: mrr_at_100
314
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315
  - type: mrr_at_1000
316
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317
  - type: mrr_at_3
318
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319
  - type: mrr_at_5
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321
  - type: ndcg_at_1
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  - type: ndcg_at_10
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325
  - type: ndcg_at_100
326
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327
  - type: ndcg_at_1000
328
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329
  - type: ndcg_at_3
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331
  - type: ndcg_at_5
332
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333
  - type: precision_at_1
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  - type: precision_at_10
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  - type: precision_at_100
338
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339
  - type: precision_at_1000
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341
  - type: precision_at_3
342
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343
  - type: precision_at_5
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345
  - type: recall_at_1
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  - type: recall_at_10
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349
  - type: recall_at_100
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351
  - type: recall_at_1000
352
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353
  - type: recall_at_3
354
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355
  - type: recall_at_5
356
+ value: 47.089999999999996
357
  - task:
358
  type: Retrieval
359
  dataset:
 
364
  revision: None
365
  metrics:
366
  - type: map_at_1
367
+ value: 38.811
368
  - type: map_at_10
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370
  - type: map_at_100
371
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  - type: map_at_1000
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374
  - type: map_at_3
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  - type: map_at_5
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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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  - type: ndcg_at_10
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  - type: ndcg_at_100
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396
  - type: ndcg_at_1000
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398
  - type: ndcg_at_3
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400
  - type: ndcg_at_5
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  - type: precision_at_1
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  - type: precision_at_10
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  - type: precision_at_100
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  - type: precision_at_1000
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  - type: precision_at_3
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  - type: precision_at_5
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  - type: recall_at_1
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  - type: recall_at_10
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  - type: recall_at_100
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  - type: recall_at_1000
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  - type: recall_at_3
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424
  - type: recall_at_5
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  - task:
427
  type: Retrieval
428
  dataset:
 
433
  revision: None
434
  metrics:
435
  - type: map_at_1
436
+ value: 25.378
437
  - type: map_at_10
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439
  - type: map_at_100
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  - type: map_at_1000
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  - type: map_at_3
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  - type: map_at_5
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  - type: mrr_at_1000
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  - type: mrr_at_3
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  - type: mrr_at_5
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  - type: ndcg_at_1
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  - type: ndcg_at_1000
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  - type: precision_at_10
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  - type: precision_at_100
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477
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  - type: precision_at_3
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  - type: precision_at_5
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  - type: recall_at_1
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  - type: recall_at_10
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  - type: recall_at_100
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489
  - type: recall_at_1000
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  - type: recall_at_3
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493
  - type: recall_at_5
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495
  - task:
496
  type: Retrieval
497
  dataset:
 
502
  revision: None
503
  metrics:
504
  - type: map_at_1
505
+ value: 17.326
506
  - type: map_at_10
507
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508
  - type: map_at_100
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  - type: map_at_1000
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  - type: map_at_3
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  - type: map_at_5
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  - type: mrr_at_1
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  - type: mrr_at_10
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  - type: mrr_at_100
521
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  - type: mrr_at_1000
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524
  - type: mrr_at_3
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526
  - type: mrr_at_5
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528
  - type: ndcg_at_1
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530
  - type: ndcg_at_10
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532
  - type: ndcg_at_100
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534
  - type: ndcg_at_1000
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536
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  - type: precision_at_1
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  - type: precision_at_10
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  - type: precision_at_100
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  - type: precision_at_1000
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  - type: precision_at_3
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  - type: precision_at_5
551
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  - type: recall_at_1
553
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  - type: recall_at_10
555
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556
  - type: recall_at_100
557
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  - type: recall_at_1000
559
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  - type: recall_at_3
561
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562
  - type: recall_at_5
563
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564
  - task:
565
  type: Retrieval
566
  dataset:
 
571
  revision: None
572
  metrics:
573
  - type: map_at_1
574
+ value: 29.069
575
  - type: map_at_10
576
+ value: 40.027
577
  - type: map_at_100
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  - type: map_at_1000
580
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  - type: map_at_3
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  - type: map_at_5
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  - type: mrr_at_100
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  - type: mrr_at_1000
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  - type: mrr_at_3
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  - type: mrr_at_5
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  - type: ndcg_at_1
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  - type: ndcg_at_1000
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  - type: ndcg_at_5
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  - type: precision_at_1
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  - type: precision_at_10
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  - type: precision_at_1000
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  - type: precision_at_3
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619
  - type: precision_at_5
620
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621
  - type: recall_at_1
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623
  - type: recall_at_10
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  - type: recall_at_100
626
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627
  - type: recall_at_1000
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629
  - type: recall_at_3
630
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631
  - type: recall_at_5
632
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633
  - task:
634
  type: Retrieval
635
  dataset:
 
640
  revision: None
641
  metrics:
642
  - type: map_at_1
643
+ value: 23.905
644
  - type: map_at_10
645
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  - type: map_at_100
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  - type: map_at_1000
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  - type: map_at_3
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  - type: map_at_5
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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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  - type: ndcg_at_10
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  - type: recall_at_5
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703
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709
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710
  metrics:
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  - type: map_at_1
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772
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778
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779
  metrics:
780
  - type: map_at_1
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  dataset:
 
847
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848
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  - type: map_at_10
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916
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917
  metrics:
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985
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986
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1054
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1055
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  dataset:
 
1123
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1124
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1125
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1192
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1193
  metrics:
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  - type: map_at_1
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1261
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1274
  revision: None
1275
  metrics:
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1343
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1565
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1617
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1652
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1950
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1971
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  metrics:
1973
  - type: cos_sim_pearson
1974
+ value: 85.21363088257881
1975
  - type: cos_sim_spearman
1976
+ value: 75.56589127055523
1977
  - type: euclidean_pearson
1978
+ value: 82.32868324521908
1979
  - type: euclidean_spearman
1980
+ value: 75.31928550664554
1981
  - type: manhattan_pearson
1982
+ value: 82.31332875713211
1983
  - type: manhattan_spearman
1984
+ value: 75.35376322099196
1985
  - task:
1986
  type: STS
1987
  dataset:
 
1992
  revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
1993
  metrics:
1994
  - type: cos_sim_pearson
1995
+ value: 85.09085593258487
1996
  - type: cos_sim_spearman
1997
+ value: 86.26355088415221
1998
  - type: euclidean_pearson
1999
+ value: 85.49646115361156
2000
  - type: euclidean_spearman
2001
+ value: 86.20652472228703
2002
  - type: manhattan_pearson
2003
+ value: 85.44084081123815
2004
  - type: manhattan_spearman
2005
+ value: 86.1162623448951
2006
  - task:
2007
  type: STS
2008
  dataset:
 
2013
  revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
2014
  metrics:
2015
  - type: cos_sim_pearson
2016
+ value: 84.68250248349368
2017
  - type: cos_sim_spearman
2018
+ value: 82.29883673695083
2019
  - type: euclidean_pearson
2020
+ value: 84.17633035446019
2021
  - type: euclidean_spearman
2022
+ value: 82.19990511264791
2023
  - type: manhattan_pearson
2024
+ value: 84.17408410692279
2025
  - type: manhattan_spearman
2026
+ value: 82.249873895981
2027
  - task:
2028
  type: STS
2029
  dataset:
 
2034
  revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
2035
  metrics:
2036
  - type: cos_sim_pearson
2037
+ value: 87.31878760045024
2038
  - type: cos_sim_spearman
2039
+ value: 88.7364409031183
2040
  - type: euclidean_pearson
2041
+ value: 88.230537618603
2042
  - type: euclidean_spearman
2043
+ value: 88.76484309646318
2044
  - type: manhattan_pearson
2045
+ value: 88.17689071136469
2046
  - type: manhattan_spearman
2047
+ value: 88.72809249037928
2048
  - task:
2049
  type: STS
2050
  dataset:
 
2055
  revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
2056
  metrics:
2057
  - type: cos_sim_pearson
2058
+ value: 83.41078559110638
2059
  - type: cos_sim_spearman
2060
+ value: 85.27439135411049
2061
  - type: euclidean_pearson
2062
+ value: 84.5333571592088
2063
  - type: euclidean_spearman
2064
+ value: 85.25645460575957
2065
  - type: manhattan_pearson
2066
+ value: 84.38428921610226
2067
  - type: manhattan_spearman
2068
+ value: 85.07796040798796
2069
  - task:
2070
  type: STS
2071
  dataset:
 
2076
  revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
2077
  metrics:
2078
  - type: cos_sim_pearson
2079
+ value: 88.82374132382576
2080
  - type: cos_sim_spearman
2081
+ value: 89.02101343562433
2082
  - type: euclidean_pearson
2083
+ value: 89.50729765458932
2084
  - type: euclidean_spearman
2085
+ value: 89.04184772869253
2086
  - type: manhattan_pearson
2087
+ value: 89.51737904059856
2088
  - type: manhattan_spearman
2089
+ value: 89.12925950440676
2090
  - task:
2091
  type: STS
2092
  dataset:
 
2097
  revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
2098
  metrics:
2099
  - type: cos_sim_pearson
2100
+ value: 67.56051823873482
2101
  - type: cos_sim_spearman
2102
+ value: 68.50988748185463
2103
  - type: euclidean_pearson
2104
+ value: 69.16524346147456
2105
  - type: euclidean_spearman
2106
+ value: 68.61859952449579
2107
  - type: manhattan_pearson
2108
+ value: 69.10618915706995
2109
  - type: manhattan_spearman
2110
+ value: 68.36401769459522
2111
  - task:
2112
  type: STS
2113
  dataset:
 
2118
  revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
2119
  metrics:
2120
  - type: cos_sim_pearson
2121
+ value: 85.4159693872625
2122
  - type: cos_sim_spearman
2123
+ value: 87.07819121764247
2124
  - type: euclidean_pearson
2125
+ value: 87.03013260863153
2126
  - type: euclidean_spearman
2127
+ value: 87.06547293631309
2128
  - type: manhattan_pearson
2129
+ value: 86.8129744446062
2130
  - type: manhattan_spearman
2131
+ value: 86.88494096335627
2132
  - task:
2133
  type: Reranking
2134
  dataset:
 
2139
  revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
2140
  metrics:
2141
  - type: map
2142
+ value: 86.47758088996575
2143
  - type: mrr
2144
+ value: 96.17891458577733
2145
  - task:
2146
  type: Retrieval
2147
  dataset:
 
2152
  revision: None
2153
  metrics:
2154
  - type: map_at_1
2155
+ value: 57.538999999999994
2156
  - type: map_at_10
2157
+ value: 66.562
2158
  - type: map_at_100
2159
+ value: 67.254
2160
  - type: map_at_1000
2161
+ value: 67.284
2162
  - type: map_at_3
2163
+ value: 63.722
2164
  - type: map_at_5
2165
+ value: 65.422
2166
  - type: mrr_at_1
2167
+ value: 60.0
2168
  - type: mrr_at_10
2169
+ value: 67.354
2170
  - type: mrr_at_100
2171
+ value: 67.908
2172
  - type: mrr_at_1000
2173
+ value: 67.93299999999999
2174
  - type: mrr_at_3
2175
+ value: 65.056
2176
  - type: mrr_at_5
2177
+ value: 66.43900000000001
2178
  - type: ndcg_at_1
2179
+ value: 60.0
2180
  - type: ndcg_at_10
2181
+ value: 70.858
2182
  - type: ndcg_at_100
2183
+ value: 73.67099999999999
2184
  - type: ndcg_at_1000
2185
+ value: 74.26700000000001
2186
  - type: ndcg_at_3
2187
+ value: 65.911
2188
  - type: ndcg_at_5
2189
+ value: 68.42200000000001
2190
  - type: precision_at_1
2191
+ value: 60.0
2192
  - type: precision_at_10
2193
+ value: 9.4
2194
  - type: precision_at_100
2195
+ value: 1.083
2196
  - type: precision_at_1000
2197
  value: 0.11299999999999999
2198
  - type: precision_at_3
2199
+ value: 25.444
2200
  - type: precision_at_5
2201
  value: 17.0
2202
  - type: recall_at_1
2203
+ value: 57.538999999999994
2204
  - type: recall_at_10
2205
+ value: 83.233
2206
  - type: recall_at_100
2207
+ value: 95.667
2208
  - type: recall_at_1000
2209
+ value: 100.0
2210
  - type: recall_at_3
2211
+ value: 69.883
2212
  - type: recall_at_5
2213
+ value: 76.19399999999999
2214
  - task:
2215
  type: PairClassification
2216
  dataset:
 
2221
  revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
2222
  metrics:
2223
  - type: cos_sim_accuracy
2224
+ value: 99.82574257425742
2225
  - type: cos_sim_ap
2226
+ value: 95.78722833053911
2227
  - type: cos_sim_f1
2228
+ value: 90.94650205761316
2229
  - type: cos_sim_precision
2230
+ value: 93.64406779661016
2231
  - type: cos_sim_recall
2232
+ value: 88.4
2233
  - type: dot_accuracy
2234
+ value: 99.83366336633664
2235
  - type: dot_ap
2236
+ value: 95.89733601612964
2237
  - type: dot_f1
2238
+ value: 91.41981613891727
2239
  - type: dot_precision
2240
+ value: 93.42379958246346
2241
  - type: dot_recall
2242
+ value: 89.5
2243
  - type: euclidean_accuracy
2244
+ value: 99.82574257425742
2245
  - type: euclidean_ap
2246
+ value: 95.75227035138846
2247
  - type: euclidean_f1
2248
+ value: 90.96509240246407
2249
  - type: euclidean_precision
2250
+ value: 93.45991561181435
2251
  - type: euclidean_recall
2252
+ value: 88.6
2253
  - type: manhattan_accuracy
2254
+ value: 99.82574257425742
2255
  - type: manhattan_ap
2256
+ value: 95.76278266220176
2257
  - type: manhattan_f1
2258
+ value: 91.08409321175279
2259
  - type: manhattan_precision
2260
+ value: 92.29979466119097
2261
  - type: manhattan_recall
2262
+ value: 89.9
2263
  - type: max_accuracy
2264
+ value: 99.83366336633664
2265
  - type: max_ap
2266
+ value: 95.89733601612964
2267
  - type: max_f1
2268
+ value: 91.41981613891727
2269
  - task:
2270
  type: Clustering
2271
  dataset:
 
2276
  revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2277
  metrics:
2278
  - type: v_measure
2279
+ value: 61.905425988638605
2280
  - task:
2281
  type: Clustering
2282
  dataset:
 
2287
  revision: 815ca46b2622cec33ccafc3735d572c266efdb44
2288
  metrics:
2289
  - type: v_measure
2290
+ value: 36.159589881679736
2291
  - task:
2292
  type: Reranking
2293
  dataset:
 
2298
  revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
2299
  metrics:
2300
  - type: map
2301
+ value: 53.0605499476397
2302
  - type: mrr
2303
+ value: 53.91594516594517
2304
  - task:
2305
  type: Summarization
2306
  dataset:
 
2311
  revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
2312
  metrics:
2313
  - type: cos_sim_pearson
2314
+ value: 30.202718009067
2315
  - type: cos_sim_spearman
2316
+ value: 31.136199912366987
2317
  - type: dot_pearson
2318
+ value: 30.66329011927951
2319
  - type: dot_spearman
2320
+ value: 30.107664909625107
2321
  - task:
2322
  type: Retrieval
2323
  dataset:
 
2328
  revision: None
2329
  metrics:
2330
  - type: map_at_1
2331
+ value: 0.209
2332
  - type: map_at_10
2333
+ value: 1.712
2334
  - type: map_at_100
2335
+ value: 9.464
2336
  - type: map_at_1000
2337
+ value: 23.437
2338
  - type: map_at_3
2339
+ value: 0.609
2340
  - type: map_at_5
2341
+ value: 0.9440000000000001
2342
  - type: mrr_at_1
2343
  value: 78.0
2344
  - type: mrr_at_10
2345
+ value: 86.833
2346
  - type: mrr_at_100
2347
+ value: 86.833
2348
  - type: mrr_at_1000
2349
+ value: 86.833
2350
  - type: mrr_at_3
2351
+ value: 85.333
2352
  - type: mrr_at_5
2353
+ value: 86.833
2354
  - type: ndcg_at_1
2355
+ value: 74.0
2356
  - type: ndcg_at_10
2357
+ value: 69.14
2358
  - type: ndcg_at_100
2359
+ value: 53.047999999999995
2360
  - type: ndcg_at_1000
2361
+ value: 48.577
2362
  - type: ndcg_at_3
2363
+ value: 75.592
2364
  - type: ndcg_at_5
2365
+ value: 72.509
2366
  - type: precision_at_1
2367
  value: 78.0
2368
  - type: precision_at_10
2369
+ value: 73.0
2370
  - type: precision_at_100
2371
+ value: 54.44
2372
  - type: precision_at_1000
2373
+ value: 21.326
2374
  - type: precision_at_3
2375
+ value: 80.667
2376
  - type: precision_at_5
2377
+ value: 77.2
2378
  - type: recall_at_1
2379
+ value: 0.209
2380
  - type: recall_at_10
2381
+ value: 1.932
2382
  - type: recall_at_100
2383
+ value: 13.211999999999998
2384
  - type: recall_at_1000
2385
+ value: 45.774
2386
  - type: recall_at_3
2387
+ value: 0.644
2388
  - type: recall_at_5
2389
+ value: 1.0290000000000001
2390
  - task:
2391
  type: Retrieval
2392
  dataset:
 
2397
  revision: None
2398
  metrics:
2399
  - type: map_at_1
2400
+ value: 2.609
2401
  - type: map_at_10
2402
+ value: 8.334999999999999
2403
  - type: map_at_100
2404
+ value: 14.604000000000001
2405
  - type: map_at_1000
2406
+ value: 16.177
2407
  - type: map_at_3
2408
+ value: 4.87
2409
  - type: map_at_5
2410
+ value: 6.3149999999999995
2411
  - type: mrr_at_1
2412
+ value: 32.653
2413
  - type: mrr_at_10
2414
+ value: 45.047
2415
  - type: mrr_at_100
2416
+ value: 45.808
2417
  - type: mrr_at_1000
2418
+ value: 45.808
2419
  - type: mrr_at_3
2420
+ value: 41.497
2421
  - type: mrr_at_5
2422
+ value: 43.231
2423
  - type: ndcg_at_1
2424
+ value: 30.612000000000002
2425
  - type: ndcg_at_10
2426
+ value: 21.193
2427
  - type: ndcg_at_100
2428
+ value: 34.97
2429
  - type: ndcg_at_1000
2430
+ value: 46.69
2431
  - type: ndcg_at_3
2432
+ value: 24.823
2433
  - type: ndcg_at_5
2434
+ value: 22.872999999999998
2435
  - type: precision_at_1
2436
+ value: 32.653
2437
  - type: precision_at_10
2438
+ value: 17.959
2439
  - type: precision_at_100
2440
+ value: 7.4079999999999995
2441
  - type: precision_at_1000
2442
+ value: 1.537
2443
  - type: precision_at_3
2444
+ value: 25.85
2445
  - type: precision_at_5
2446
+ value: 22.448999999999998
2447
  - type: recall_at_1
2448
+ value: 2.609
2449
  - type: recall_at_10
2450
+ value: 13.63
2451
  - type: recall_at_100
2452
+ value: 47.014
2453
  - type: recall_at_1000
2454
+ value: 83.176
2455
  - type: recall_at_3
2456
+ value: 5.925
2457
  - type: recall_at_5
2458
+ value: 8.574
2459
  - task:
2460
  type: Classification
2461
  dataset:
 
2466
  revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
2467
  metrics:
2468
  - type: accuracy
2469
+ value: 72.80239999999999
2470
  - type: ap
2471
+ value: 15.497911013214791
2472
  - type: f1
2473
+ value: 56.258411577947285
2474
  - task:
2475
  type: Classification
2476
  dataset:
 
2481
  revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
2482
  metrics:
2483
  - type: accuracy
2484
+ value: 61.00452744765139
2485
  - type: f1
2486
+ value: 61.42228624410908
2487
  - task:
2488
  type: Clustering
2489
  dataset:
 
2494
  revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
2495
  metrics:
2496
  - type: v_measure
2497
+ value: 50.00516915962345
2498
  - task:
2499
  type: PairClassification
2500
  dataset:
 
2505
  revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
2506
  metrics:
2507
  - type: cos_sim_accuracy
2508
+ value: 85.62317458425225
2509
  - type: cos_sim_ap
2510
+ value: 72.95115658063823
2511
  - type: cos_sim_f1
2512
+ value: 66.78976523344764
2513
  - type: cos_sim_precision
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2515
  - type: cos_sim_recall
2516
+ value: 66.80738786279683
2517
  - type: dot_accuracy
2518
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2519
  - type: dot_ap
2520
+ value: 73.10385271517778
2521
  - type: dot_f1
2522
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2523
  - type: dot_precision
2524
+ value: 61.74242424242424
2525
  - type: dot_recall
2526
+ value: 73.11345646437995
2527
  - type: euclidean_accuracy
2528
+ value: 85.65893783155511
2529
  - type: euclidean_ap
2530
+ value: 72.87428208473992
2531
  - type: euclidean_f1
2532
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2533
  - type: euclidean_precision
2534
+ value: 64.5910551025451
2535
  - type: euclidean_recall
2536
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2537
  - type: manhattan_accuracy
2538
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2539
  - type: manhattan_ap
2540
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2541
  - type: manhattan_f1
2542
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2543
  - type: manhattan_precision
2544
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2545
  - type: manhattan_recall
2546
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2547
  - type: max_accuracy
2548
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2549
  - type: max_ap
2550
+ value: 73.10385271517778
2551
  - type: max_f1
2552
+ value: 66.94853829427399
2553
  - task:
2554
  type: PairClassification
2555
  dataset:
 
2560
  revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
2561
  metrics:
2562
  - type: cos_sim_accuracy
2563
+ value: 88.69096130709822
2564
  - type: cos_sim_ap
2565
+ value: 85.30326978668063
2566
  - type: cos_sim_f1
2567
+ value: 77.747088683189
2568
  - type: cos_sim_precision
2569
+ value: 75.4491451753115
2570
  - type: cos_sim_recall
2571
+ value: 80.189405605174
2572
  - type: dot_accuracy
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+ value: 88.43870066363954
2574
  - type: dot_ap
2575
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2576
  - type: dot_f1
2577
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2578
  - type: dot_precision
2579
+ value: 73.93871239808828
2580
  - type: dot_recall
2581
+ value: 80.99784416384355
2582
  - type: euclidean_accuracy
2583
+ value: 88.70066363953894
2584
  - type: euclidean_ap
2585
+ value: 85.34184508966621
2586
  - type: euclidean_f1
2587
+ value: 77.76871756856931
2588
  - type: euclidean_precision
2589
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2590
  - type: euclidean_recall
2591
+ value: 80.77456113335386
2592
  - type: manhattan_accuracy
2593
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2594
  - type: manhattan_ap
2595
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2596
  - type: manhattan_f1
2597
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2598
  - type: manhattan_precision
2599
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2600
  - type: manhattan_recall
2601
+ value: 81.15183246073299
2602
  - type: max_accuracy
2603
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2604
  - type: max_ap
2605
+ value: 85.34184508966621
2606
  - type: max_f1
2607
+ value: 77.76871756856931
2608
  ---
2609
  <h1 align="center">GIST small Embedding v0</h1>
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  "position_embedding_type": "absolute",
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