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@@ -5,6 +5,1158 @@ tags:
5
  - feature-extraction
6
  - sentence-similarity
7
  - transformers
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8
  language: pl
9
  license: apache-2.0
10
  widget:
 
5
  - feature-extraction
6
  - sentence-similarity
7
  - transformers
8
+ - mteb
9
+ model-index:
10
+ - name: mmlw-e5-large
11
+ results:
12
+ - task:
13
+ type: Clustering
14
+ dataset:
15
+ type: PL-MTEB/8tags-clustering
16
+ name: MTEB 8TagsClustering
17
+ config: default
18
+ split: test
19
+ revision: None
20
+ metrics:
21
+ - type: v_measure
22
+ value: 30.623921415441725
23
+ - task:
24
+ type: Classification
25
+ dataset:
26
+ type: PL-MTEB/allegro-reviews
27
+ name: MTEB AllegroReviews
28
+ config: default
29
+ split: test
30
+ revision: None
31
+ metrics:
32
+ - type: accuracy
33
+ value: 37.683896620278325
34
+ - type: f1
35
+ value: 34.19193027014284
36
+ - task:
37
+ type: Retrieval
38
+ dataset:
39
+ type: arguana-pl
40
+ name: MTEB ArguAna-PL
41
+ config: default
42
+ split: test
43
+ revision: None
44
+ metrics:
45
+ - type: map_at_1
46
+ value: 38.407000000000004
47
+ - type: map_at_10
48
+ value: 55.147
49
+ - type: map_at_100
50
+ value: 55.757
51
+ - type: map_at_1000
52
+ value: 55.761
53
+ - type: map_at_3
54
+ value: 51.268
55
+ - type: map_at_5
56
+ value: 53.696999999999996
57
+ - type: mrr_at_1
58
+ value: 40.043
59
+ - type: mrr_at_10
60
+ value: 55.840999999999994
61
+ - type: mrr_at_100
62
+ value: 56.459
63
+ - type: mrr_at_1000
64
+ value: 56.462999999999994
65
+ - type: mrr_at_3
66
+ value: 52.074
67
+ - type: mrr_at_5
68
+ value: 54.364999999999995
69
+ - type: ndcg_at_1
70
+ value: 38.407000000000004
71
+ - type: ndcg_at_10
72
+ value: 63.248000000000005
73
+ - type: ndcg_at_100
74
+ value: 65.717
75
+ - type: ndcg_at_1000
76
+ value: 65.79
77
+ - type: ndcg_at_3
78
+ value: 55.403999999999996
79
+ - type: ndcg_at_5
80
+ value: 59.760000000000005
81
+ - type: precision_at_1
82
+ value: 38.407000000000004
83
+ - type: precision_at_10
84
+ value: 8.862
85
+ - type: precision_at_100
86
+ value: 0.991
87
+ - type: precision_at_1000
88
+ value: 0.1
89
+ - type: precision_at_3
90
+ value: 22.451
91
+ - type: precision_at_5
92
+ value: 15.576
93
+ - type: recall_at_1
94
+ value: 38.407000000000004
95
+ - type: recall_at_10
96
+ value: 88.62
97
+ - type: recall_at_100
98
+ value: 99.075
99
+ - type: recall_at_1000
100
+ value: 99.57300000000001
101
+ - type: recall_at_3
102
+ value: 67.354
103
+ - type: recall_at_5
104
+ value: 77.881
105
+ - task:
106
+ type: Classification
107
+ dataset:
108
+ type: PL-MTEB/cbd
109
+ name: MTEB CBD
110
+ config: default
111
+ split: test
112
+ revision: None
113
+ metrics:
114
+ - type: accuracy
115
+ value: 66.14999999999999
116
+ - type: ap
117
+ value: 21.69513674684204
118
+ - type: f1
119
+ value: 56.48142830893528
120
+ - task:
121
+ type: PairClassification
122
+ dataset:
123
+ type: PL-MTEB/cdsce-pairclassification
124
+ name: MTEB CDSC-E
125
+ config: default
126
+ split: test
127
+ revision: None
128
+ metrics:
129
+ - type: cos_sim_accuracy
130
+ value: 89.4
131
+ - type: cos_sim_ap
132
+ value: 76.83228768203222
133
+ - type: cos_sim_f1
134
+ value: 65.3658536585366
135
+ - type: cos_sim_precision
136
+ value: 60.909090909090914
137
+ - type: cos_sim_recall
138
+ value: 70.52631578947368
139
+ - type: dot_accuracy
140
+ value: 84.1
141
+ - type: dot_ap
142
+ value: 57.26072201751864
143
+ - type: dot_f1
144
+ value: 62.75395033860045
145
+ - type: dot_precision
146
+ value: 54.9407114624506
147
+ - type: dot_recall
148
+ value: 73.15789473684211
149
+ - type: euclidean_accuracy
150
+ value: 89.4
151
+ - type: euclidean_ap
152
+ value: 76.59095263388942
153
+ - type: euclidean_f1
154
+ value: 65.21739130434783
155
+ - type: euclidean_precision
156
+ value: 60.26785714285714
157
+ - type: euclidean_recall
158
+ value: 71.05263157894737
159
+ - type: manhattan_accuracy
160
+ value: 89.4
161
+ - type: manhattan_ap
162
+ value: 76.58825999753456
163
+ - type: manhattan_f1
164
+ value: 64.72019464720195
165
+ - type: manhattan_precision
166
+ value: 60.18099547511312
167
+ - type: manhattan_recall
168
+ value: 70.0
169
+ - type: max_accuracy
170
+ value: 89.4
171
+ - type: max_ap
172
+ value: 76.83228768203222
173
+ - type: max_f1
174
+ value: 65.3658536585366
175
+ - task:
176
+ type: STS
177
+ dataset:
178
+ type: PL-MTEB/cdscr-sts
179
+ name: MTEB CDSC-R
180
+ config: default
181
+ split: test
182
+ revision: None
183
+ metrics:
184
+ - type: cos_sim_pearson
185
+ value: 93.73949495291659
186
+ - type: cos_sim_spearman
187
+ value: 93.50397366192922
188
+ - type: euclidean_pearson
189
+ value: 92.47498888987636
190
+ - type: euclidean_spearman
191
+ value: 93.39315936230747
192
+ - type: manhattan_pearson
193
+ value: 92.47250250777654
194
+ - type: manhattan_spearman
195
+ value: 93.36739690549109
196
+ - task:
197
+ type: Retrieval
198
+ dataset:
199
+ type: dbpedia-pl
200
+ name: MTEB DBPedia-PL
201
+ config: default
202
+ split: test
203
+ revision: None
204
+ metrics:
205
+ - type: map_at_1
206
+ value: 8.434
207
+ - type: map_at_10
208
+ value: 18.424
209
+ - type: map_at_100
210
+ value: 26.428
211
+ - type: map_at_1000
212
+ value: 28.002
213
+ - type: map_at_3
214
+ value: 13.502
215
+ - type: map_at_5
216
+ value: 15.577
217
+ - type: mrr_at_1
218
+ value: 63.0
219
+ - type: mrr_at_10
220
+ value: 72.714
221
+ - type: mrr_at_100
222
+ value: 73.021
223
+ - type: mrr_at_1000
224
+ value: 73.028
225
+ - type: mrr_at_3
226
+ value: 70.75
227
+ - type: mrr_at_5
228
+ value: 72.3
229
+ - type: ndcg_at_1
230
+ value: 52.75
231
+ - type: ndcg_at_10
232
+ value: 39.839999999999996
233
+ - type: ndcg_at_100
234
+ value: 44.989000000000004
235
+ - type: ndcg_at_1000
236
+ value: 52.532999999999994
237
+ - type: ndcg_at_3
238
+ value: 45.198
239
+ - type: ndcg_at_5
240
+ value: 42.015
241
+ - type: precision_at_1
242
+ value: 63.0
243
+ - type: precision_at_10
244
+ value: 31.05
245
+ - type: precision_at_100
246
+ value: 10.26
247
+ - type: precision_at_1000
248
+ value: 1.9879999999999998
249
+ - type: precision_at_3
250
+ value: 48.25
251
+ - type: precision_at_5
252
+ value: 40.45
253
+ - type: recall_at_1
254
+ value: 8.434
255
+ - type: recall_at_10
256
+ value: 24.004
257
+ - type: recall_at_100
258
+ value: 51.428
259
+ - type: recall_at_1000
260
+ value: 75.712
261
+ - type: recall_at_3
262
+ value: 15.015
263
+ - type: recall_at_5
264
+ value: 18.282999999999998
265
+ - task:
266
+ type: Retrieval
267
+ dataset:
268
+ type: fiqa-pl
269
+ name: MTEB FiQA-PL
270
+ config: default
271
+ split: test
272
+ revision: None
273
+ metrics:
274
+ - type: map_at_1
275
+ value: 19.088
276
+ - type: map_at_10
277
+ value: 31.818
278
+ - type: map_at_100
279
+ value: 33.689
280
+ - type: map_at_1000
281
+ value: 33.86
282
+ - type: map_at_3
283
+ value: 27.399
284
+ - type: map_at_5
285
+ value: 29.945
286
+ - type: mrr_at_1
287
+ value: 38.117000000000004
288
+ - type: mrr_at_10
289
+ value: 47.668
290
+ - type: mrr_at_100
291
+ value: 48.428
292
+ - type: mrr_at_1000
293
+ value: 48.475
294
+ - type: mrr_at_3
295
+ value: 45.242
296
+ - type: mrr_at_5
297
+ value: 46.716
298
+ - type: ndcg_at_1
299
+ value: 38.272
300
+ - type: ndcg_at_10
301
+ value: 39.903
302
+ - type: ndcg_at_100
303
+ value: 46.661
304
+ - type: ndcg_at_1000
305
+ value: 49.625
306
+ - type: ndcg_at_3
307
+ value: 35.921
308
+ - type: ndcg_at_5
309
+ value: 37.558
310
+ - type: precision_at_1
311
+ value: 38.272
312
+ - type: precision_at_10
313
+ value: 11.358
314
+ - type: precision_at_100
315
+ value: 1.8190000000000002
316
+ - type: precision_at_1000
317
+ value: 0.23500000000000001
318
+ - type: precision_at_3
319
+ value: 24.434
320
+ - type: precision_at_5
321
+ value: 18.395
322
+ - type: recall_at_1
323
+ value: 19.088
324
+ - type: recall_at_10
325
+ value: 47.355999999999995
326
+ - type: recall_at_100
327
+ value: 72.451
328
+ - type: recall_at_1000
329
+ value: 90.257
330
+ - type: recall_at_3
331
+ value: 32.931
332
+ - type: recall_at_5
333
+ value: 39.878
334
+ - task:
335
+ type: Retrieval
336
+ dataset:
337
+ type: hotpotqa-pl
338
+ name: MTEB HotpotQA-PL
339
+ config: default
340
+ split: test
341
+ revision: None
342
+ metrics:
343
+ - type: map_at_1
344
+ value: 39.095
345
+ - type: map_at_10
346
+ value: 62.529
347
+ - type: map_at_100
348
+ value: 63.425
349
+ - type: map_at_1000
350
+ value: 63.483000000000004
351
+ - type: map_at_3
352
+ value: 58.887
353
+ - type: map_at_5
354
+ value: 61.18599999999999
355
+ - type: mrr_at_1
356
+ value: 78.123
357
+ - type: mrr_at_10
358
+ value: 84.231
359
+ - type: mrr_at_100
360
+ value: 84.408
361
+ - type: mrr_at_1000
362
+ value: 84.414
363
+ - type: mrr_at_3
364
+ value: 83.286
365
+ - type: mrr_at_5
366
+ value: 83.94
367
+ - type: ndcg_at_1
368
+ value: 78.19
369
+ - type: ndcg_at_10
370
+ value: 70.938
371
+ - type: ndcg_at_100
372
+ value: 73.992
373
+ - type: ndcg_at_1000
374
+ value: 75.1
375
+ - type: ndcg_at_3
376
+ value: 65.863
377
+ - type: ndcg_at_5
378
+ value: 68.755
379
+ - type: precision_at_1
380
+ value: 78.19
381
+ - type: precision_at_10
382
+ value: 14.949000000000002
383
+ - type: precision_at_100
384
+ value: 1.733
385
+ - type: precision_at_1000
386
+ value: 0.188
387
+ - type: precision_at_3
388
+ value: 42.381
389
+ - type: precision_at_5
390
+ value: 27.711000000000002
391
+ - type: recall_at_1
392
+ value: 39.095
393
+ - type: recall_at_10
394
+ value: 74.747
395
+ - type: recall_at_100
396
+ value: 86.631
397
+ - type: recall_at_1000
398
+ value: 93.923
399
+ - type: recall_at_3
400
+ value: 63.571999999999996
401
+ - type: recall_at_5
402
+ value: 69.27799999999999
403
+ - task:
404
+ type: Retrieval
405
+ dataset:
406
+ type: msmarco-pl
407
+ name: MTEB MSMARCO-PL
408
+ config: default
409
+ split: validation
410
+ revision: None
411
+ metrics:
412
+ - type: map_at_1
413
+ value: 19.439999999999998
414
+ - type: map_at_10
415
+ value: 30.264000000000003
416
+ - type: map_at_100
417
+ value: 31.438
418
+ - type: map_at_1000
419
+ value: 31.495
420
+ - type: map_at_3
421
+ value: 26.735
422
+ - type: map_at_5
423
+ value: 28.716
424
+ - type: mrr_at_1
425
+ value: 19.914
426
+ - type: mrr_at_10
427
+ value: 30.753999999999998
428
+ - type: mrr_at_100
429
+ value: 31.877
430
+ - type: mrr_at_1000
431
+ value: 31.929000000000002
432
+ - type: mrr_at_3
433
+ value: 27.299
434
+ - type: mrr_at_5
435
+ value: 29.254
436
+ - type: ndcg_at_1
437
+ value: 20.014000000000003
438
+ - type: ndcg_at_10
439
+ value: 36.472
440
+ - type: ndcg_at_100
441
+ value: 42.231
442
+ - type: ndcg_at_1000
443
+ value: 43.744
444
+ - type: ndcg_at_3
445
+ value: 29.268
446
+ - type: ndcg_at_5
447
+ value: 32.79
448
+ - type: precision_at_1
449
+ value: 20.014000000000003
450
+ - type: precision_at_10
451
+ value: 5.814
452
+ - type: precision_at_100
453
+ value: 0.8710000000000001
454
+ - type: precision_at_1000
455
+ value: 0.1
456
+ - type: precision_at_3
457
+ value: 12.426
458
+ - type: precision_at_5
459
+ value: 9.238
460
+ - type: recall_at_1
461
+ value: 19.439999999999998
462
+ - type: recall_at_10
463
+ value: 55.535000000000004
464
+ - type: recall_at_100
465
+ value: 82.44399999999999
466
+ - type: recall_at_1000
467
+ value: 94.217
468
+ - type: recall_at_3
469
+ value: 35.963
470
+ - type: recall_at_5
471
+ value: 44.367000000000004
472
+ - task:
473
+ type: Classification
474
+ dataset:
475
+ type: mteb/amazon_massive_intent
476
+ name: MTEB MassiveIntentClassification (pl)
477
+ config: pl
478
+ split: test
479
+ revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
480
+ metrics:
481
+ - type: accuracy
482
+ value: 72.01412239408205
483
+ - type: f1
484
+ value: 70.04544187503352
485
+ - task:
486
+ type: Classification
487
+ dataset:
488
+ type: mteb/amazon_massive_scenario
489
+ name: MTEB MassiveScenarioClassification (pl)
490
+ config: pl
491
+ split: test
492
+ revision: 7d571f92784cd94a019292a1f45445077d0ef634
493
+ metrics:
494
+ - type: accuracy
495
+ value: 75.26899798251513
496
+ - type: f1
497
+ value: 75.55876166863844
498
+ - task:
499
+ type: Retrieval
500
+ dataset:
501
+ type: nfcorpus-pl
502
+ name: MTEB NFCorpus-PL
503
+ config: default
504
+ split: test
505
+ revision: None
506
+ metrics:
507
+ - type: map_at_1
508
+ value: 5.772
509
+ - type: map_at_10
510
+ value: 12.708
511
+ - type: map_at_100
512
+ value: 16.194
513
+ - type: map_at_1000
514
+ value: 17.630000000000003
515
+ - type: map_at_3
516
+ value: 9.34
517
+ - type: map_at_5
518
+ value: 10.741
519
+ - type: mrr_at_1
520
+ value: 43.344
521
+ - type: mrr_at_10
522
+ value: 53.429
523
+ - type: mrr_at_100
524
+ value: 53.88699999999999
525
+ - type: mrr_at_1000
526
+ value: 53.925
527
+ - type: mrr_at_3
528
+ value: 51.342
529
+ - type: mrr_at_5
530
+ value: 52.456
531
+ - type: ndcg_at_1
532
+ value: 41.641
533
+ - type: ndcg_at_10
534
+ value: 34.028000000000006
535
+ - type: ndcg_at_100
536
+ value: 31.613000000000003
537
+ - type: ndcg_at_1000
538
+ value: 40.428
539
+ - type: ndcg_at_3
540
+ value: 38.991
541
+ - type: ndcg_at_5
542
+ value: 36.704
543
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1149
+ value: 0.22
1150
+ - type: recall_at_10
1151
+ value: 1.934
1152
+ - type: recall_at_100
1153
+ value: 12.728
1154
+ - type: recall_at_1000
1155
+ value: 41.869
1156
+ - type: recall_at_3
1157
+ value: 0.637
1158
+ - type: recall_at_5
1159
+ value: 1.042
1160
  language: pl
1161
  license: apache-2.0
1162
  widget: