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README.md CHANGED
@@ -5,56 +5,64 @@ tags:
5
  - feature-extraction
6
  - dense
7
  - generated_from_trainer
8
- - dataset_size:355
9
  - loss:MultipleNegativesRankingLoss
10
- - dataset_size:966
11
  base_model: sentence-transformers/LaBSE
12
  widget:
13
- - source_sentence: 'de dus su chos kyi yi ge ’di’i byin rlabs kyis| ’dre gdon gnod
14
- byed thod [=thams cad] der cing ’bros bar ’gyuro [=’gyur ro]| '
15
  sentences:
16
- - 'tüüni xöinü-dü xoyor-düγar daγačni kumüni oroon- cüsüün-yer γol dürkü: '
17
- - 'tüüni caqta nomin zarliq uni aidisted-yer čüdkür ada xoro üüdüqči [=üyiledüqči]
18
- xamoq ülüdüqtn zütüxüdi boloxü: '
19
- - 'tüüni caqtü nomin zarliq ene ürügeǰileküü mön bö: '
20
- - source_sentence: 'slar yang lnga brgya’i dus kyi tha ma la| sangyas [=sangs rgyas]
21
- bstan pa mar grib dus| '
 
 
 
 
22
  sentences:
23
- - tere küböüni čü xoyino yeke ǰin ösȫd toyin bolǰi yāran kičēküi tuürbiqsan-yēr
24
- dayini daruqsani olun üyiledbei ilaγün tögüsün üleqsen-dü Ānanda ayiladxabai
25
- - 'xairani [=xarin] basa ecüs tabün züüni caqta bürxani šaǰin urü buraxa caq: '
26
- - 'basan tere caqtu xorin tabun ǰeva burxad nigen tālal kigēd nigen egešiq-yēr
27
- caqlaši ügei nasutuyin suduriyin ayimaq öüni nomloboi:: '
28
- - source_sentence: 'lnga ba lo [=lam] la ’gro ba’i mi mthong|| '
 
 
 
 
 
 
 
 
29
  sentences:
30
- - 'om namo bhaγavade abarimida āyur ǰnyā na sübinixči da de čo ra za ya da ta
31
- ga da ya arhade samyaq sam buddha ya: daday ta: om pünei pünei mahā pünei abarimida pünei
32
- abarimida pünei ǰnyā na sam bha ro pa čide: om sarvā sam sakā ra pa ri šuddhe
33
- dharma de ga ga na samud ga de sva bha vā bišüddhe mahā na ya pari vā re sva
34
- hā:: '
35
- - 'tabudaγar zam-dü yoboqsan ulü üzüqdkü: '
36
- - 'ken caqlaši ügei nasutuyin suduriyin ayimaq öüni üzüqtü bičikü buyu üzüqtü bičiülkülē:
37
- tere tamuyin amitan kigēd adoüsuni töröl oron kigēd erligiyin yertüncü-kezē
38
- čü ülü törön: '
39
- - source_sentence: 'bdun pa rgyal khosyi [=khams kyi] khang ba rnos [=rnams] stong
40
- par ’gyur| '
 
 
 
 
41
  sentences:
42
- - 'eseren kiged inü xürüqsti [=xormusta] tergütüün xamq amitani tüsütü baiγulxi
43
- müün bö: '
44
- - 'doladuγr oran nutugin bišing-nüγüd xosorxi-dü boloxi: '
45
- - ' om namo bhaγavade abarimida āyur ǰnyā na sübinixči da {de} čo rā zā ya: da
46
- ta ka da ya: arhde (=arhade) samyaq sam buddha ya dadya ta: om pünei pünei mahā
47
- pünei abarimida pünei abari{mi}da pünei ǰnyā na sam bha ro pa či de: om sarvā
48
- sam sakā ra pa ri šuddhe dharma de ga ga na samud ga de: sva bhā va bišüddhe
49
- mahā na ya pari vā re sva hā:: '
50
- - source_sentence: 'dge slong tshul khrims nyos [=nyon mongs] pa’i dus| '
51
  sentences:
52
- - 'geleng šaqšabad buraxa caq müü sanan sedkeldü sanaxin caq: '
53
- - 'tögünčilen boluqsad bodhi mahāsadv-noγoudtu oγōto xadangγadxaxuyin dēdü-bēr kedüi
54
- činēn oγōto xadangγadxaqsan inu: ilaγun tögüsüqsen maši γayixamšiq sayibēr oduqsan
55
- maši γayixamšiq: '
56
- - 'ilaγun tögüsün üleqsen šravasdi balγasun-du ilaγuqči xan küböüni ceceqliq itegel
57
- ügei-dü idē ögüqčiyin bükün tālaxui xorōdu: '
58
  pipeline_tag: sentence-similarity
59
  library_name: sentence-transformers
60
  ---
@@ -110,9 +118,9 @@ from sentence_transformers import SentenceTransformer
110
  model = SentenceTransformer("sentence_transformers_model_id")
111
  # Run inference
112
  sentences = [
113
- 'dge slong tshul khrims nyos [=nyon mongs] pa’i dus| ',
114
- 'geleng šaqšabad buraxa caq müü sanan sedkeldü sanaxin caq: ',
115
- 'tögünčilen boluqsad bodhi mahāsadv-noγoudtu oγōto xadangγadxaxuyin dēdü-bēr kedüi činēn oγōto xadangγadxaqsan inu: ilaγun tögüsüqsen maši γayixamšiq sayibēr oduqsan maši γayixamšiq: ',
116
  ]
117
  embeddings = model.encode(sentences)
118
  print(embeddings.shape)
@@ -166,19 +174,19 @@ You can finetune this model on your own dataset.
166
 
167
  #### Unnamed Dataset
168
 
169
- * Size: 966 training samples
170
  * Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>label</code>
171
- * Approximate statistics based on the first 966 samples:
172
- | | sentence_0 | sentence_1 | label |
173
- |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:--------------------------------------------------------------|
174
- | type | string | string | float |
175
- | details | <ul><li>min: 7 tokens</li><li>mean: 30.95 tokens</li><li>max: 193 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 31.0 tokens</li><li>max: 201 tokens</li></ul> | <ul><li>min: 1.0</li><li>mean: 1.0</li><li>max: 1.0</li></ul> |
176
  * Samples:
177
- | sentence_0 | sentence_1 | label |
178
- |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
179
- | <code>sangyas [=sangs rgyas] bstan la dad pa’i mii\| spos dang me tog chod par bgyi\| de nas byos [=byams] ba mgon pos no [=nam] mkha’ dbyings nas gzit [=gzigs] ti\| mi rnosyi [=rnams kyi] mig nas khrag gi mchil byung ba mthong nas\| bco [=bcom] ldan ’dasyi [=’das kyi] drung du byon nas zhus pa\| </code> | <code>bürxüni šiǰindü süzüqten kümün küǰi kiged ceceq-yer takin ülüdkü teged itegel mider (~maider) [=mayidari]-yer oγotoroγon činer-ece ailedeǰi kümün-nuγüd nidan [=nidün]-ece cüsüni nilübüs [=nilbusun] γaraqsn üzed ilγün [=ilaγun] tögüsün ülüqsn derege-dü öged-dü [=ögede] bolod alitxaba [=ayildxaba] . </code> | <code>1.0</code> |
180
- | <code>rdo rje drag po dga’ ba che . </code> | <code>yeke bayasxulang-tu doqšin očir .</code> | <code>1.0</code> |
181
- | <code>stong pa nyid dga’ mchog gi blo . </code> | <code>xōsun činar tālaxui tačīngγui oyoutu .</code> | <code>1.0</code> |
182
  * Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
183
  ```json
184
  {
@@ -192,8 +200,8 @@ You can finetune this model on your own dataset.
192
  #### Non-Default Hyperparameters
193
 
194
  - `eval_strategy`: steps
195
- - `per_device_train_batch_size`: 12
196
- - `per_device_eval_batch_size`: 12
197
  - `num_train_epochs`: 40
198
  - `fp16`: True
199
  - `multi_dataset_batch_sampler`: round_robin
@@ -205,8 +213,8 @@ You can finetune this model on your own dataset.
205
  - `do_predict`: False
206
  - `eval_strategy`: steps
207
  - `prediction_loss_only`: True
208
- - `per_device_train_batch_size`: 12
209
- - `per_device_eval_batch_size`: 12
210
  - `per_gpu_train_batch_size`: None
211
  - `per_gpu_eval_batch_size`: None
212
  - `gradient_accumulation_steps`: 1
@@ -253,7 +261,7 @@ You can finetune this model on your own dataset.
253
  - `debug`: []
254
  - `dataloader_drop_last`: False
255
  - `dataloader_num_workers`: 0
256
- - `dataloader_prefetch_factor`: None
257
  - `past_index`: -1
258
  - `disable_tqdm`: False
259
  - `remove_unused_columns`: True
@@ -326,249 +334,168 @@ You can finetune this model on your own dataset.
326
 
327
  | Epoch | Step |
328
  |:-------:|:----:|
329
- | 0.375 | 3 |
330
- | 0.75 | 6 |
331
- | 1.0 | 8 |
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- | 1.125 | 9 |
333
- | 1.5 | 12 |
334
- | 1.875 | 15 |
335
- | 2.0 | 16 |
336
- | 2.25 | 18 |
337
- | 2.625 | 21 |
338
- | 3.0 | 24 |
339
- | 3.375 | 27 |
340
- | 3.75 | 30 |
341
- | 4.0 | 32 |
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- | 4.125 | 33 |
343
- | 4.5 | 36 |
344
- | 4.875 | 39 |
345
- | 5.0 | 40 |
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- | 5.25 | 42 |
347
- | 5.625 | 45 |
348
- | 6.0 | 48 |
349
- | 6.375 | 51 |
350
- | 6.75 | 54 |
351
- | 7.0 | 56 |
352
- | 7.125 | 57 |
353
- | 7.5 | 60 |
354
- | 7.875 | 63 |
355
- | 8.0 | 64 |
356
- | 8.25 | 66 |
357
- | 8.625 | 69 |
358
- | 9.0 | 72 |
359
- | 9.375 | 75 |
360
- | 9.75 | 78 |
361
- | 10.0 | 80 |
362
- | 10.125 | 81 |
363
- | 10.5 | 84 |
364
- | 10.875 | 87 |
365
- | 11.0 | 88 |
366
- | 11.25 | 90 |
367
- | 11.625 | 93 |
368
- | 12.0 | 96 |
369
- | 12.375 | 99 |
370
- | 12.75 | 102 |
371
- | 13.0 | 104 |
372
- | 13.125 | 105 |
373
- | 13.5 | 108 |
374
- | 13.875 | 111 |
375
- | 14.0 | 112 |
376
- | 14.25 | 114 |
377
- | 14.625 | 117 |
378
- | 15.0 | 120 |
379
- | 15.375 | 123 |
380
- | 15.75 | 126 |
381
- | 16.0 | 128 |
382
- | 16.125 | 129 |
383
- | 16.5 | 132 |
384
- | 16.875 | 135 |
385
- | 17.0 | 136 |
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- | 17.25 | 138 |
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- | 17.625 | 141 |
388
- | 18.0 | 144 |
389
- | 18.375 | 147 |
390
- | 18.75 | 150 |
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- | 19.0 | 152 |
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- | 19.125 | 153 |
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- | 19.5 | 156 |
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- | 19.875 | 159 |
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- | 20.0 | 160 |
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- | 20.25 | 162 |
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- | 20.625 | 165 |
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- | 21.0 | 168 |
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- | 21.375 | 171 |
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- | 21.75 | 174 |
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- | 22.0 | 176 |
402
- | 22.125 | 177 |
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- | 22.5 | 180 |
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- | 22.875 | 183 |
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- | 23.0 | 184 |
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- | 23.25 | 186 |
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- | 23.625 | 189 |
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- | 24.0 | 192 |
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- | 24.375 | 195 |
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- | 24.75 | 198 |
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- | 25.0 | 200 |
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- | 25.125 | 201 |
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- | 25.5 | 204 |
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- | 25.875 | 207 |
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- | 26.0 | 208 |
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- | 26.25 | 210 |
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- | 26.625 | 213 |
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- | 27.0 | 216 |
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- | 27.375 | 219 |
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- | 27.75 | 222 |
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- | 28.0 | 224 |
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- | 28.125 | 225 |
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- | 28.5 | 228 |
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- | 28.875 | 231 |
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- | 29.0 | 232 |
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- | 29.25 | 234 |
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- | 29.625 | 237 |
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- | 30.0 | 240 |
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- | 30.375 | 243 |
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- | 30.75 | 246 |
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- | 31.0 | 248 |
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- | 31.125 | 249 |
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- | 31.5 | 252 |
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- | 31.875 | 255 |
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- | 32.0 | 256 |
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- | 32.25 | 258 |
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- | 32.625 | 261 |
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- | 33.0 | 264 |
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- | 33.375 | 267 |
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- | 33.75 | 270 |
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- | 34.0 | 272 |
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- | 34.125 | 273 |
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- | 34.5 | 276 |
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- | 34.875 | 279 |
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- | 35.0 | 280 |
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- | 35.25 | 282 |
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- | 35.625 | 285 |
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- | 36.0 | 288 |
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- | 36.375 | 291 |
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- | 36.75 | 294 |
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- | 37.0 | 296 |
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- | 37.125 | 297 |
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- | 37.5 | 300 |
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- | 37.875 | 303 |
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- | 38.0 | 304 |
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- | 38.25 | 306 |
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- | 38.625 | 309 |
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- | 39.0 | 312 |
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- | 0.1429 | 3 |
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- | 0.2857 | 6 |
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- | 0.4286 | 9 |
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- | 0.5714 | 12 |
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- | 0.7143 | 15 |
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- | 0.8571 | 18 |
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- | 1.0 | 21 |
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- | 1.1429 | 24 |
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- | 1.2857 | 27 |
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- | 1.4286 | 30 |
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- | 1.5714 | 33 |
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- | 1.7143 | 36 |
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- | 1.8571 | 39 |
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- | 2.0 | 42 |
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- | 2.1429 | 45 |
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- | 2.2857 | 48 |
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- | 2.4286 | 51 |
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- | 2.5714 | 54 |
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- | 2.7143 | 57 |
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- | 2.8571 | 60 |
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- | 3.0 | 63 |
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- | 3.1429 | 66 |
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- | 3.2857 | 69 |
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- | 3.4286 | 72 |
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- | 3.5714 | 75 |
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- | 3.7143 | 78 |
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- | 3.8571 | 81 |
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- | 4.0 | 84 |
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- | 4.1429 | 87 |
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- | 4.2857 | 90 |
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- | 4.4286 | 93 |
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- | 4.5714 | 96 |
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- | 4.7143 | 99 |
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- | 4.8571 | 102 |
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- | 5.0 | 105 |
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- | 5.1429 | 108 |
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- | 5.2857 | 111 |
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- | 5.4286 | 114 |
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- | 5.5714 | 117 |
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- | 5.7143 | 120 |
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- | 5.8571 | 123 |
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- | 6.0 | 126 |
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- | 6.1429 | 129 |
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- | 6.2857 | 132 |
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- | 6.4286 | 135 |
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- | 6.5714 | 138 |
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- | 6.7143 | 141 |
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- | 6.8571 | 144 |
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- | 7.0 | 147 |
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- | 7.1429 | 150 |
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- | 7.2857 | 153 |
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- | 7.4286 | 156 |
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- | 7.5714 | 159 |
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- | 7.7143 | 162 |
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- | 7.8571 | 165 |
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- | 8.0 | 168 |
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- | 8.1429 | 171 |
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- | 8.2857 | 174 |
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- | 8.4286 | 177 |
518
- | 8.5714 | 180 |
519
- | 8.7143 | 183 |
520
- | 8.8571 | 186 |
521
- | 9.0 | 189 |
522
- | 9.1429 | 192 |
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- | 9.2857 | 195 |
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- | 9.4286 | 198 |
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- | 9.5714 | 201 |
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- | 9.7143 | 204 |
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- | 9.8571 | 207 |
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- | 10.0 | 210 |
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- | 10.1429 | 213 |
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- | 10.2857 | 216 |
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- | 10.4286 | 219 |
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- | 10.5714 | 222 |
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- | 10.7143 | 225 |
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- | 10.8571 | 228 |
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- | 11.0 | 231 |
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- | 11.1429 | 234 |
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- | 11.2857 | 237 |
538
- | 11.4286 | 240 |
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- | 11.5714 | 243 |
540
- | 11.7143 | 246 |
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- | 11.8571 | 249 |
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- | 12.0 | 252 |
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- | 12.1429 | 255 |
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- | 12.2857 | 258 |
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- | 12.4286 | 261 |
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- | 12.5714 | 264 |
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- | 12.7143 | 267 |
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- | 12.8571 | 270 |
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- | 13.0 | 273 |
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- | 13.1429 | 276 |
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- | 13.2857 | 279 |
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- | 13.4286 | 282 |
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- | 13.5714 | 285 |
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- | 13.7143 | 288 |
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- | 13.8571 | 291 |
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- | 14.0 | 294 |
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- | 14.1429 | 297 |
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- | 14.2857 | 300 |
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- | 14.4286 | 303 |
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- | 14.5714 | 306 |
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- | 14.7143 | 309 |
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- | 14.8571 | 312 |
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- | 15.0 | 315 |
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- | 15.1429 | 318 |
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- | 15.2857 | 321 |
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- | 15.4286 | 324 |
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- | 15.5714 | 327 |
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- | 15.7143 | 330 |
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- | 15.8571 | 333 |
570
- | 16.0 | 336 |
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- | 16.1429 | 339 |
572
 
573
  </details>
574
 
@@ -576,9 +503,9 @@ You can finetune this model on your own dataset.
576
  - Python: 3.10.0
577
  - Sentence Transformers: 5.1.0
578
  - Transformers: 4.46.3
579
- - PyTorch: 2.0.1+cu118
580
  - Accelerate: 1.1.1
581
- - Datasets: 4.0.0
582
  - Tokenizers: 0.20.3
583
 
584
  ## Citation
 
5
  - feature-extraction
6
  - dense
7
  - generated_from_trainer
8
+ - dataset_size:2099
9
  - loss:MultipleNegativesRankingLoss
 
10
  base_model: sentence-transformers/LaBSE
11
  widget:
12
+ - source_sentence: 'chos shes bkra shis bkra shis ‘byung . '
 
13
  sentences:
14
+ - nom meden ölzöyitöi ölzöi- bolxu .
15
+ - ' om namo bhaγavade abarimida āyur ǰnyā na sübinixči da de čo rā zā ya da ta
16
+ ga da ya arhade samyaq sam buddha ya . daday ta . om pünei pünei mahā pünei
17
+ abarimida pünei abarimida pünei ǰnyā na sam bha ro pa čide . om sarvā sam sakā
18
+ ra pa re šuddhe dharma de ga ga na samud ga de sva bha bišüddhe mahā na ya
19
+ pari vā re sva . . '
20
+ - kā-ya vā-gī šo-ra . a-ra pa-za-nā ya de na-map . .
21
+ - source_sentence: 'spyan drangs la mchod gnas bya dgos gsungs nas dus de nyid du
22
+ btsun mo dang| blon po dang| phyi ''khor dang| nang ''khor mang pos rgyal po''i
23
+ sngar ''khor nas| '
24
  sentences:
25
+ - ere zāni belegeyin tödüi xora orun γadādu dalai toqtobui .
26
+ - ' zalaǰi takiliyin oron bolγoxu kemēn zarliq bolōd . mon daruüda xatun tüšimed
27
+ kigēd . γadādu nököd dotōdü nököd olon-yēr ilete kürēlöülen .'
28
+ - izuurtani köböün töüni šara üsüni [n]ükün buri čü tögönčilen boluqsan suüxü bui
29
+ . suüγād čü izuurtani köböün ene metü erel xangγaxü čindamani erdeniyigi olun
30
+ . üyiledkü olxu boluyu . izuurtani köböün či zurγān züyili tonilγon üyiledüqsen sayin
31
+ sayin kü . izuurtani köböün čini gebelidü orošiqson amitan tedeču xarin ülü ireqči bodhi-sadv
32
+ boluyu . kemēn zarliq bolbui . . kemēgēd ilγon tögösüqsen burxan xamuq töüdker
33
+ teyin arilγaqčidu zarliq bolboi .
34
+ - source_sentence: sangs rgyas 'od srungs la bram ze'i khye'u skar ma'i 'od ces bya
35
+ bas sems bskyed pa dang| sangs rgyas 'od srungs kyis lung bstan pa| bram ze'i
36
+ khye'u khyod tshe lo khri'i dus su zhing khams skar ma'i 'od ces bya bar| sangs
37
+ rgyas mar me mdzad ces bya bar mngon par rdzogs par sangs rgya bar 'gyur ro zhes
38
+ lung bstan nas sangs rgyas so .
39
  sentences:
40
+ - gerel sakiqči burxan-du odoni kemēkü birman köböün bodhi sedkil öüskeqsen-dü
41
+ gerel sakiqči burxan eši üzüüleqsen inu . birman köböün či tüme nasulxoi caqtu
42
+ odoni gerel kemēkü tarālanggiyin oron-du dhi-pamka-ra burxan kemēn ilerkei duusun
43
+ burxan bolxu . kemēn eši üzüülēd burxan bolboi .
44
+ - adlidxaxülā dalan yeke tüb niǰēd dusul-ēce bi tōlun čidaxu . saba-yin zokōlliyin
45
+ suduriyin ayimagiyin nigen šülügiyin buyani tōlun ülü čidaxu bui . ada-lidxaxülā
46
+ γangγan möreni xümakiyin tödüi togünčilen boluqsun dayini darün sayitur dou-suqsan
47
+ burxadtu . c[a]q arban <...> xoyor kalab boltolo xubcasun kigēd ebečin-šütüküi
48
+ em kigēd . aγoursun-noγoud-yēr sayin kündülel üyiledüqsen buyüni coqcoēce . sabayin
49
+ zokōl-liyin suduriyin ayimagi takin üyileduqsun buyan maši ülemǰi .
50
+ - tende-ēce tenggeriyin e{rke}tu xurmasta beyeyin kemǰē γurba bosxoxoi ayilidxal
51
+ ögȫd . ilγon tögüsün öleqsen ni nayiman nasuni kemǰē . öber dēre tedkiküi ekidu
52
+ xoyor inu xaraqsan-du . eke ögüülebei . nayiman nasuni kemǰē inu . lombiyin
53
+ oi šoγüyin šer<...>yin üzüür-lügē teng bilē kemēn ögüülebei .
54
+ - source_sentence: '’du shes kun gyi don spangs shing . '
55
  sentences:
56
+ - aldar ölzöi-töi sayin aldar buyan-tu . .
57
+ - busudiyin ači ülü orkixui yeke yosutai . .
58
+ - xurān medeküi xamugiyin udxa tebčin .
59
+ - source_sentence: 'sangs rgyas ‘byung ba khyod la ‘dud . '
 
 
 
 
 
60
  sentences:
61
+ - burxan bolxui čimadu sögödümüi .
62
+ - biraman ögüülebei . bi bükün-dü eldeb zobolong üzeǰi öni bolun xoyino suruqsani
63
+ tula . yeke xān sonosxui durašixü bögǖsü ödüi činēn-yēr bolxu busu .
64
+ - yeke tüšimel tere čü tenggeri-yin šütēni dergede odči eyin kemēn ayiladxabai
65
+ .
 
66
  pipeline_tag: sentence-similarity
67
  library_name: sentence-transformers
68
  ---
 
118
  model = SentenceTransformer("sentence_transformers_model_id")
119
  # Run inference
120
  sentences = [
121
+ 'sangs rgyas ‘byung ba khyod la ‘dud . ',
122
+ 'burxan bolxui čimadu sögödümüi .',
123
+ 'biraman ögüülebei . bi bükün-dü eldeb zobolong üzeǰi öni bolun xoyino suruqsani tula . yeke xān sonosxui durašixü bögǖsü ödüi činēn-yēr bolxu busu .',
124
  ]
125
  embeddings = model.encode(sentences)
126
  print(embeddings.shape)
 
174
 
175
  #### Unnamed Dataset
176
 
177
+ * Size: 2,099 training samples
178
  * Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>label</code>
179
+ * Approximate statistics based on the first 1000 samples:
180
+ | | sentence_0 | sentence_1 | label |
181
+ |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:--------------------------------------------------------------|
182
+ | type | string | string | float |
183
+ | details | <ul><li>min: 10 tokens</li><li>mean: 64.03 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 64.31 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 1.0</li><li>mean: 1.0</li><li>max: 1.0</li></ul> |
184
  * Samples:
185
+ | sentence_0 | sentence_1 | label |
186
+ |:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
187
+ | <code>gdan mthon po gsum bshams pa ’di la\| gcig la ni sangs rgyas bzhugs su gsol cig </code> | <code>γurban önder debisker beledüqsen öüni nigendüni burxani soülγan zalbari </code> | <code>1.0</code> |
188
+ | <code>rku ba spangs nas gzhan la byin pas zas skom 'phel bar 'gyur ro .</code> | <code> xolxoi tebčīd busudtu ökülē idēn undān ürgüǰikü boluyu .</code> | <code>1.0</code> |
189
+ | <code>de'i tshe bcom ldan 'das kyi smin mtshams nas 'od zer mang po bkye nas\| 'od des 'jig rten gyi khams thams cad khyab par byas nas\| mnar med pa'i sems can dmyal ba yan chad la khyab par byas so . sdug bsngal thams cad zhi bar gyur to . de nas slar dbu'i gtsug tor du nub par [(64na)] gyur to .</code> | <code>tere caqtu ilγon tögüsün ülüqseni kümöskü zabsar-ēce olon gerel sacurād . tere gerel-yēr yertünciyin xamoq orudtu tügēn . ayous tamü-ēce inaqši xamuqtu tokiülün üyiledküi . xamuq zobolong maši amurlibai . tegēd xarin ilγon tögüsün üleqsen ni oroyin usnirtu šinggebei .</code> | <code>1.0</code> |
190
  * Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
191
  ```json
192
  {
 
200
  #### Non-Default Hyperparameters
201
 
202
  - `eval_strategy`: steps
203
+ - `per_device_train_batch_size`: 32
204
+ - `per_device_eval_batch_size`: 32
205
  - `num_train_epochs`: 40
206
  - `fp16`: True
207
  - `multi_dataset_batch_sampler`: round_robin
 
213
  - `do_predict`: False
214
  - `eval_strategy`: steps
215
  - `prediction_loss_only`: True
216
+ - `per_device_train_batch_size`: 32
217
+ - `per_device_eval_batch_size`: 32
218
  - `per_gpu_train_batch_size`: None
219
  - `per_gpu_eval_batch_size`: None
220
  - `gradient_accumulation_steps`: 1
 
261
  - `debug`: []
262
  - `dataloader_drop_last`: False
263
  - `dataloader_num_workers`: 0
264
+ - `dataloader_prefetch_factor`: 2
265
  - `past_index`: -1
266
  - `disable_tqdm`: False
267
  - `remove_unused_columns`: True
 
334
 
335
  | Epoch | Step |
336
  |:-------:|:----:|
337
+ | 0.1765 | 3 |
338
+ | 0.3529 | 6 |
339
+ | 0.5294 | 9 |
340
+ | 0.7059 | 12 |
341
+ | 0.8824 | 15 |
342
+ | 1.0 | 17 |
343
+ | 1.0588 | 18 |
344
+ | 1.2353 | 21 |
345
+ | 1.4118 | 24 |
346
+ | 1.5882 | 27 |
347
+ | 1.7647 | 30 |
348
+ | 1.9412 | 33 |
349
+ | 2.0 | 34 |
350
+ | 2.1176 | 36 |
351
+ | 2.2941 | 39 |
352
+ | 2.4706 | 42 |
353
+ | 2.6471 | 45 |
354
+ | 2.8235 | 48 |
355
+ | 3.0 | 51 |
356
+ | 3.1765 | 54 |
357
+ | 3.3529 | 57 |
358
+ | 3.5294 | 60 |
359
+ | 3.7059 | 63 |
360
+ | 3.8824 | 66 |
361
+ | 4.0 | 68 |
362
+ | 4.0588 | 69 |
363
+ | 4.2353 | 72 |
364
+ | 4.4118 | 75 |
365
+ | 4.5882 | 78 |
366
+ | 4.7647 | 81 |
367
+ | 4.9412 | 84 |
368
+ | 5.0 | 85 |
369
+ | 5.1176 | 87 |
370
+ | 5.2941 | 90 |
371
+ | 5.4706 | 93 |
372
+ | 5.6471 | 96 |
373
+ | 5.8235 | 99 |
374
+ | 6.0 | 102 |
375
+ | 6.1765 | 105 |
376
+ | 6.3529 | 108 |
377
+ | 6.5294 | 111 |
378
+ | 6.7059 | 114 |
379
+ | 6.8824 | 117 |
380
+ | 7.0 | 119 |
381
+ | 7.0588 | 120 |
382
+ | 7.2353 | 123 |
383
+ | 7.4118 | 126 |
384
+ | 7.5882 | 129 |
385
+ | 7.7647 | 132 |
386
+ | 7.9412 | 135 |
387
+ | 8.0 | 136 |
388
+ | 8.1176 | 138 |
389
+ | 8.2941 | 141 |
390
+ | 8.4706 | 144 |
391
+ | 8.6471 | 147 |
392
+ | 8.8235 | 150 |
393
+ | 9.0 | 153 |
394
+ | 9.1765 | 156 |
395
+ | 9.3529 | 159 |
396
+ | 9.5294 | 162 |
397
+ | 9.7059 | 165 |
398
+ | 9.8824 | 168 |
399
+ | 10.0 | 170 |
400
+ | 10.0588 | 171 |
401
+ | 10.2353 | 174 |
402
+ | 10.4118 | 177 |
403
+ | 10.5882 | 180 |
404
+ | 10.7647 | 183 |
405
+ | 10.9412 | 186 |
406
+ | 11.0 | 187 |
407
+ | 11.1176 | 189 |
408
+ | 11.2941 | 192 |
409
+ | 11.4706 | 195 |
410
+ | 11.6471 | 198 |
411
+ | 11.8235 | 201 |
412
+ | 12.0 | 204 |
413
+ | 12.1765 | 207 |
414
+ | 12.3529 | 210 |
415
+ | 12.5294 | 213 |
416
+ | 12.7059 | 216 |
417
+ | 12.8824 | 219 |
418
+ | 13.0 | 221 |
419
+ | 13.0588 | 222 |
420
+ | 13.2353 | 225 |
421
+ | 13.4118 | 228 |
422
+ | 13.5882 | 231 |
423
+ | 13.7647 | 234 |
424
+ | 13.9412 | 237 |
425
+ | 14.0 | 238 |
426
+ | 14.1176 | 240 |
427
+ | 14.2941 | 243 |
428
+ | 14.4706 | 246 |
429
+ | 14.6471 | 249 |
430
+ | 14.8235 | 252 |
431
+ | 15.0 | 255 |
432
+ | 15.1765 | 258 |
433
+ | 15.3529 | 261 |
434
+ | 15.5294 | 264 |
435
+ | 15.7059 | 267 |
436
+ | 15.8824 | 270 |
437
+ | 16.0 | 272 |
438
+ | 16.0588 | 273 |
439
+ | 16.2353 | 276 |
440
+ | 16.4118 | 279 |
441
+ | 16.5882 | 282 |
442
+ | 16.7647 | 285 |
443
+ | 16.9412 | 288 |
444
+ | 17.0 | 289 |
445
+ | 17.1176 | 291 |
446
+ | 17.2941 | 294 |
447
+ | 17.4706 | 297 |
448
+ | 17.6471 | 300 |
449
+ | 17.8235 | 303 |
450
+ | 18.0 | 306 |
451
+ | 18.1765 | 309 |
452
+ | 18.3529 | 312 |
453
+ | 18.5294 | 315 |
454
+ | 18.7059 | 318 |
455
+ | 18.8824 | 321 |
456
+ | 19.0 | 323 |
457
+ | 19.0588 | 324 |
458
+ | 19.2353 | 327 |
459
+ | 19.4118 | 330 |
460
+ | 19.5882 | 333 |
461
+ | 19.7647 | 336 |
462
+ | 19.9412 | 339 |
463
+ | 20.0 | 340 |
464
+ | 20.1176 | 342 |
465
+ | 20.2941 | 345 |
466
+ | 20.4706 | 348 |
467
+ | 20.6471 | 351 |
468
+ | 20.8235 | 354 |
469
+ | 21.0 | 357 |
470
+ | 21.1765 | 360 |
471
+ | 21.3529 | 363 |
472
+ | 21.5294 | 366 |
473
+ | 21.7059 | 369 |
474
+ | 21.8824 | 372 |
475
+ | 22.0 | 374 |
476
+ | 22.0588 | 375 |
477
+ | 22.2353 | 378 |
478
+ | 22.4118 | 381 |
479
+ | 22.5882 | 384 |
480
+ | 22.7647 | 387 |
481
+ | 22.9412 | 390 |
482
+ | 23.0 | 391 |
483
+ | 23.1176 | 393 |
484
+ | 23.2941 | 396 |
485
+ | 23.4706 | 399 |
486
+ | 23.6471 | 402 |
487
+ | 23.8235 | 405 |
488
+ | 24.0 | 408 |
489
+ | 24.1765 | 411 |
490
+ | 24.3529 | 414 |
491
+ | 24.5294 | 417 |
492
+ | 24.7059 | 420 |
493
+ | 24.8824 | 423 |
494
+ | 25.0 | 425 |
495
+ | 25.0588 | 426 |
496
+ | 25.2353 | 429 |
497
+ | 25.4118 | 432 |
498
+ | 25.5882 | 435 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
499
 
500
  </details>
501
 
 
503
  - Python: 3.10.0
504
  - Sentence Transformers: 5.1.0
505
  - Transformers: 4.46.3
506
+ - PyTorch: 1.12.1+cu113
507
  - Accelerate: 1.1.1
508
+ - Datasets: 4.4.1
509
  - Tokenizers: 0.20.3
510
 
511
  ## Citation
config_sentence_transformers.json CHANGED
@@ -2,7 +2,7 @@
2
  "__version__": {
3
  "sentence_transformers": "5.1.0",
4
  "transformers": "4.46.3",
5
- "pytorch": "2.0.1+cu118"
6
  },
7
  "model_type": "SentenceTransformer",
8
  "prompts": {
 
2
  "__version__": {
3
  "sentence_transformers": "5.1.0",
4
  "transformers": "4.46.3",
5
+ "pytorch": "1.12.1+cu113"
6
  },
7
  "model_type": "SentenceTransformer",
8
  "prompts": {
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:601855f6b95ae4ad3a6dd301acbfe1f931ad35d0c3046b8e2d199995e28d50d3
3
  size 1883730160
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:23b6e8e2461f0e8528f77126ef5b3df5f1b3b5d00c2f788e233da28fb5d70aa8
3
  size 1883730160