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  1. checkpoint-1600/1_Pooling/config.json +10 -0
  2. checkpoint-1600/README.md +747 -0
  3. checkpoint-1600/model.safetensors +3 -0
  4. checkpoint-1600/modules.json +20 -0
  5. checkpoint-1600/optimizer.pt +3 -0
  6. checkpoint-1600/rng_state.pth +3 -0
  7. checkpoint-1600/scaler.pt +3 -0
  8. checkpoint-1600/scheduler.pt +3 -0
  9. checkpoint-1600/tokenizer.json +0 -0
  10. checkpoint-1600/trainer_state.json +513 -0
  11. checkpoint-1600/training_args.bin +3 -0
  12. checkpoint-1600/vocab.txt +0 -0
  13. checkpoint-1800/model.safetensors +3 -0
  14. checkpoint-1800/optimizer.pt +3 -0
  15. checkpoint-2000/1_Pooling/config.json +10 -0
  16. checkpoint-2000/config.json +31 -0
  17. checkpoint-2000/config_sentence_transformers.json +10 -0
  18. checkpoint-2000/model.safetensors +3 -0
  19. checkpoint-2000/modules.json +20 -0
  20. checkpoint-2000/optimizer.pt +3 -0
  21. checkpoint-2000/scaler.pt +3 -0
  22. checkpoint-2000/sentence_bert_config.json +4 -0
  23. checkpoint-2000/special_tokens_map.json +37 -0
  24. checkpoint-2000/tokenizer.json +0 -0
  25. checkpoint-2000/tokenizer_config.json +58 -0
  26. checkpoint-2000/trainer_state.json +631 -0
  27. checkpoint-2200/config_sentence_transformers.json +10 -0
  28. checkpoint-2200/model.safetensors +3 -0
  29. checkpoint-2200/optimizer.pt +3 -0
  30. checkpoint-2200/sentence_bert_config.json +4 -0
  31. checkpoint-2240/model.safetensors +3 -0
  32. checkpoint-2240/optimizer.pt +3 -0
  33. checkpoint-2240/rng_state.pth +3 -0
  34. checkpoint-2240/scaler.pt +3 -0
  35. checkpoint-2240/scheduler.pt +3 -0
  36. checkpoint-2240/training_args.bin +3 -0
  37. eval/Information-Retrieval_evaluation_full_en_results.csv +12 -0
checkpoint-1600/1_Pooling/config.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
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+ {
2
+ "word_embedding_dimension": 1024,
3
+ "pooling_mode_cls_token": true,
4
+ "pooling_mode_mean_tokens": false,
5
+ "pooling_mode_max_tokens": false,
6
+ "pooling_mode_mean_sqrt_len_tokens": false,
7
+ "pooling_mode_weightedmean_tokens": false,
8
+ "pooling_mode_lasttoken": false,
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+ "include_prompt": true
10
+ }
checkpoint-1600/README.md ADDED
@@ -0,0 +1,747 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - sentence-transformers
4
+ - sentence-similarity
5
+ - feature-extraction
6
+ - generated_from_trainer
7
+ - dataset_size:114699
8
+ - loss:CachedGISTEmbedLoss
9
+ base_model: BAAI/bge-large-en-v1.5
10
+ widget:
11
+ - source_sentence: 'Bus drivers, including those operating in various sectors like
12
+ public transit, intercity, private, or school services, need strong driving skills,
13
+ knowledge of traffic laws, and the ability to operate safely in diverse conditions.
14
+ Additionally, effective communication skills and the ability to handle passenger
15
+ inquiries and emergencies are crucial.
16
+
17
+ [''bus driver'', ''intercity bus driver'', ''private bus operator'', ''transit
18
+ bus driver'', ''public service vehicle operator'', ''passenger driver'', ''international
19
+ bus driver'', ''public bus operator'', ''touristic bus driver'', ''coach driver'',
20
+ ''private coach driver'', ''public bus driver'', ''bus operator'', ''driver of
21
+ bus'', ''bus driving operator'', ''schoolbus driver'']'
22
+ sentences:
23
+ - 'The skill of determining shreds sizes percentage in cigarettes is primarily required
24
+ by tobacco processing technicians and quality control specialists in the cigarette
25
+ manufacturing industry, who ensure that the tobacco shreds meet specific size
26
+ and quality standards for consistent product performance.
27
+
28
+ [''determine shreds sizes percentage in cigarettes'', ''determine shreds sizes
29
+ percentage in cigarettes'', ''determine the shreds sizes percentage of cigarettes'',
30
+ ''determine shreds size percentages in cigarettes'', ''agree shreds sizes percentage
31
+ in cigarettes'', ''determine the shreds sizes percentage in cigarettes'', ''confirm
32
+ shreds sizes percentage in cigarettes'', ''sort shreds sizes percentage in cigarettes'']'
33
+ - 'Job roles such as curriculum developers, educational consultants, and instructional
34
+ designers require skills like analyzing, evaluating, and scrutinizing curriculums
35
+ to improve educational outcomes. For legislative programmes, roles including policy
36
+ analysts, legislative aides, and compliance officers use skills to test, evaluate,
37
+ and scrutinize legislative processes to ensure effective and efficient policy
38
+ implementation.
39
+
40
+ [''analyse curriculum'', ''test legislative programmes'', ''evaluate legislative
41
+ programmes'', ''evaluate curriculum'', ''test curriculum'', ''investigate curriculum'',
42
+ ''scrutinise curriculum'', ''analyze curriculum'', ''scrutinise legislative processes'',
43
+ ''investigate legislative programmes'']'
44
+ - 'Job roles such as customer service representatives, flight attendants, and hotel
45
+ concierges require a strong focus on passengers or customers, ensuring their needs
46
+ and comfort are prioritized to provide excellent service and support.
47
+
48
+ [''focus on passengers'', ''prioritise passengers'', ''ensure passenger prioritisation'',
49
+ ''make passengers a priority'', ''maintain a focus on passengers'', ''ensure passengers
50
+ are the priority focus'', ''ensure passengers are prioritised'', ''attend to passengers'',
51
+ ''ensure a focus on passengers'']'
52
+ - source_sentence: 'A medical laboratory assistant, or any of its synonyms such as
53
+ a biomedical laboratory assistant, requires strong attention to detail, proficiency
54
+ in using laboratory equipment, and a foundational understanding of medical science.
55
+ Additionally, skills in sample handling, data recording, and basic research methodologies
56
+ are crucial for roles like a clinical research assistant or an assistant in medical
57
+ laboratory.
58
+
59
+ [''medical laboratory assistant'', ''medical laboratory research assistant'',
60
+ ''biomedical laboratory assistant'', ''clinical research assistant'', ''assistant
61
+ in medical laboratory'', ''biomedical laboratory research assistant'', ''assistant
62
+ clinical researcher'', ''medical lab assistant'', ''assistant in biomedical laboratory'']'
63
+ sentences:
64
+ - 'Job roles such as automotive mechanics, fleet managers, and vehicle technicians
65
+ require skills to ensure vehicle operability and regular maintenance, which involves
66
+ diagnosing and repairing issues to keep vehicles roadworthy and operational.
67
+
68
+ [''ensure vehicle operability'', ''keep vehicle roadworthy'', ''keep vehicle operational'',
69
+ ''ensure operability of the vehicle'', ''ensure vehicle remains operational'',
70
+ ''ensure maintenance of vehicle'', ''ensure regular vehicle maintenance'', ''ensure
71
+ operation of the vehicle'', ''ensure operability'']'
72
+ - 'The skill of classroom management is primarily required by teachers and educators
73
+ at all levels, from kindergarten to higher education, to ensure a productive,
74
+ safe, and organized learning environment. It involves maintaining discipline,
75
+ organizing space and materials, and facilitating effective instruction, roles
76
+ that are crucial for teaching assistants and substitute teachers as well.
77
+
78
+ [''perform classroom management'', ''performing classroom management'', ''conduct
79
+ classroom management'', ''practice classroom management'', ''carry out classroom
80
+ management'', ''implement classroom management'', ''performs classroom management'']'
81
+ - 'Job roles requiring expertise in stem cells, including embryonic and adult stem
82
+ cells, typically include stem cell researchers, regenerative medicine scientists,
83
+ and biomedical engineers who focus on the development and application of stem
84
+ cell technologies for therapeutic purposes. Additionally, clinical researchers
85
+ and medical practitioners in specialized fields such as oncology and hematology
86
+ may utilize knowledge of stem cells for treatment and research purposes.
87
+
88
+ [''stem cells'', ''undifferentiated biological cells'', ''embryonic stem cells'',
89
+ ''development of stem cells'', ''stem cell'', ''adult stem cells'', ''stem cells'']'
90
+ - source_sentence: 'For roles such as ''physiotherapist'', ''neuromusculoskeletal
91
+ physiotherapist'', ''osteopath'', and ''chiropractor'', the skills needed include
92
+ a deep understanding of human anatomy and physiology, strong diagnostic skills,
93
+ and the ability to apply manual therapy techniques to treat musculoskeletal issues.
94
+ Additionally, effective communication skills are crucial for explaining treatments
95
+ and exercises to patients, while adaptability and problem-solving skills are essential
96
+ for tailoring treatments to individual patient needs.
97
+
98
+ [''physiotherapist'', ''neuromusculoskeletal physiotherapist'', ''osteopath'',
99
+ ''eurythmy therapist'', ''respiratory therapist'', ''remedial physiotherapist'',
100
+ ''physiotherapist manager'', ''occupational therapist'', ''neurological physiotherapist'',
101
+ ''occupational physiotherapist'', ''bobath physiotherapist'', ''neuromuscular
102
+ physiotherapist'', ''manipulative physiotherapist'', ''hydrotherapist'', ''rehabilitation
103
+ therapist'', ''masseuse'', ''health promotion worker'', ''cardiovascular physiotherapist'',
104
+ ''respiratory physiotherapist'', ''chiropractor'', ''sports physiotherapist'',
105
+ ''chiropractic therapist'', ''neurodevelopmental physiotherapist'', ''physical
106
+ therapist'', ''health and well-being therapist'', ''business physiotherapist'']'
107
+ sentences:
108
+ - 'Job roles that require skills in dealing with emergency care situations include
109
+ emergency medical technicians (EMTs), paramedics, and emergency room nurses or
110
+ doctors, all of whom must quickly and effectively manage critical health situations
111
+ to save lives.
112
+
113
+ [''deal with emergency care situations'', ''deal with emergency care situation'',
114
+ ''handle emergency care situation'', ''apply knowledge in emergency care situations'',
115
+ ''handle emergency care situations'']'
116
+ - 'Job roles such as fashion designers, stylist coordinators, and jewelry designers
117
+ require the skill to distinguish and evaluate accessories, their differences,
118
+ and applications, to ensure the right aesthetic and functional fit for their designs
119
+ or clients. This skill is crucial for creating cohesive looks and enhancing the
120
+ overall visual appeal in fashion and design industries.
121
+
122
+ [''distinguish accessories'', ''evaluate accessories and their differences'',
123
+ ''evaluate accessories and their application'', ''differentiate accessories'',
124
+ ''distinguish accessories and their application'', ''distinguish differences in
125
+ accessories'']'
126
+ - 'Job roles that require expertise in curriculum objectives include educational
127
+ consultants, curriculum developers, and instructional designers, who are tasked
128
+ with creating and refining educational content and learning goals to meet specific
129
+ educational standards and student needs. Teachers and headteachers also utilize
130
+ these skills to align their teaching methods and materials with the set educational
131
+ targets and aims.
132
+
133
+ [''curriculum objectives'', ''curriculum objective'', ''curriculum goals'', ''curriculum
134
+ targets'', ''curriculum aims'', ''curricula objectives'']'
135
+ - source_sentence: 'A mine surveyor, also known as a mining surveyor or mine planning
136
+ surveyor, requires expertise in geomatics and mining engineering to accurately
137
+ map and plan mine operations, ensuring safety and efficiency. They must also possess
138
+ strong analytical skills and the ability to use specialized software for creating
139
+ detailed mine plans and maintaining accurate records.
140
+
141
+ [''mine surveyor'', ''mining surveyor'', ''mine operations surveyor'', ''mine
142
+ plan maker'', ''mine records keeper'', ''mine surveyors'', ''planner of mining
143
+ operations'', ''mine planning surveyor'']'
144
+ sentences:
145
+ - 'Job roles such as data analysts, business analysts, and financial analysts require
146
+ the skill to present reports or prepare statistical reports, as they often need
147
+ to communicate complex data insights clearly and effectively to stakeholders.
148
+
149
+ [''present reports'', ''present a report'', ''submit presentation'', ''prepare
150
+ statistical reports'']'
151
+ - 'Job roles such as Food Safety Manager, Quality Assurance Specialist, and Public
152
+ Health Inspector require the skill of developing food safety programs to ensure
153
+ compliance with regulations and maintain high standards of food safety in various
154
+ settings including manufacturing, retail, and public health sectors.
155
+
156
+ [''develop food safety programmes'', ''creating food safety programmes'', ''develop
157
+ programmes for food safety'', ''food safety programmes creating'', ''food safety
158
+ programmes developing'', ''develop food safety programs'', ''food safety programme
159
+ developing'', ''food safety programme creating'', ''create food safety programmes'',
160
+ ''create programmes for food safety'', ''developing food safety programmes'']'
161
+ - 'The skill of using a sander, whether it be a handheld, manual, automatic, or
162
+ drywall sander, is primarily required by construction workers, carpenters, and
163
+ drywall installers for tasks such as roughening and smoothing wall surfaces to
164
+ prepare them for painting or finishing.
165
+
166
+ [''use sander'', ''use handheld sander'', ''roughening of wall surfaces'', ''use
167
+ drywall sander'', ''sanding of wall surfaces'', ''using sander'', ''sander usage'',
168
+ ''use manual sander'', ''drywall sanding'', ''use automatic sander'']'
169
+ - source_sentence: 'An insulation supervisor, regardless of the specific type of insulation
170
+ material or installation area, requires strong project management skills, knowledge
171
+ of building codes and safety regulations, and expertise in insulation techniques
172
+ to oversee the installation process effectively and ensure quality standards are
173
+ met.
174
+
175
+ [''insulation supervisor'', ''supervisor of installation of insulating materials'',
176
+ ''supervisor of insulation materials installation'', ''supervisor of installation
177
+ of insulation'', ''solid wall insulation installation supervisor'', ''insulation
178
+ installers supervisor'', ''cavity wall insulation installation supervisor'', ''loft
179
+ insulation installation supervisor'']'
180
+ sentences:
181
+ - 'Job roles such as Food Safety Inspector, Public Health Officer, and Environmental
182
+ Health Specialist require the skill of taking action on food safety violations
183
+ to ensure compliance with health regulations and maintain public safety standards.
184
+
185
+ [''take action on food safety violations'', ''invoke action on food safety violations'',
186
+ ''agree action on food safety violations'', ''pursue action on food safety violations'',
187
+ ''determine action on food safety violations'']'
188
+ - 'Job roles that require skills in operating and supervising textile printing machines
189
+ include Textile Printer Operators, Printing Machine Technicians, and Textile Production
190
+ Specialists. These roles involve setting up, running, and maintaining printing
191
+ machinery to ensure high-quality textile printing.
192
+
193
+ [''tend textile printing machines'', ''activate and supervise printing machines
194
+ for textile material'', ''activate and supervise textile printing machines'',
195
+ ''tend printing machines for textile'', ''tend printing machines for textile material'',
196
+ ''care for textile printing machines'', ''operate printing machines for textile
197
+ material'', ''operate textile printing machines'']'
198
+ - 'The skill of installing insulation material is primarily required by job roles
199
+ such as insulation workers, HVAC technicians, and construction specialists, who
200
+ are responsible for improving energy efficiency and thermal comfort in buildings
201
+ by correctly fitting and fixing insulation materials in various structures.
202
+
203
+ [''install insulation material'', ''insulate structure'', ''fix insulation'',
204
+ ''insulation material installation'', ''installation of insulation material'',
205
+ ''fitting insulation'', ''insulating structure'', ''installing insulation material'',
206
+ ''fixing insulation'', ''fit insulation'']'
207
+ pipeline_tag: sentence-similarity
208
+ library_name: sentence-transformers
209
+ metrics:
210
+ - cosine_accuracy@1
211
+ - cosine_accuracy@20
212
+ - cosine_accuracy@50
213
+ - cosine_accuracy@100
214
+ - cosine_accuracy@150
215
+ - cosine_accuracy@200
216
+ - cosine_precision@1
217
+ - cosine_precision@20
218
+ - cosine_precision@50
219
+ - cosine_precision@100
220
+ - cosine_precision@150
221
+ - cosine_precision@200
222
+ - cosine_recall@1
223
+ - cosine_recall@20
224
+ - cosine_recall@50
225
+ - cosine_recall@100
226
+ - cosine_recall@150
227
+ - cosine_recall@200
228
+ - cosine_ndcg@1
229
+ - cosine_ndcg@20
230
+ - cosine_ndcg@50
231
+ - cosine_ndcg@100
232
+ - cosine_ndcg@150
233
+ - cosine_ndcg@200
234
+ - cosine_mrr@1
235
+ - cosine_mrr@20
236
+ - cosine_mrr@50
237
+ - cosine_mrr@100
238
+ - cosine_mrr@150
239
+ - cosine_mrr@200
240
+ - cosine_map@1
241
+ - cosine_map@20
242
+ - cosine_map@50
243
+ - cosine_map@100
244
+ - cosine_map@150
245
+ - cosine_map@200
246
+ - cosine_map@500
247
+ model-index:
248
+ - name: SentenceTransformer based on BAAI/bge-large-en-v1.5
249
+ results:
250
+ - task:
251
+ type: information-retrieval
252
+ name: Information Retrieval
253
+ dataset:
254
+ name: full en
255
+ type: full_en
256
+ metrics:
257
+ - type: cosine_accuracy@1
258
+ value: 0.7335526315789473
259
+ name: Cosine Accuracy@1
260
+ - type: cosine_accuracy@20
261
+ value: 1.0
262
+ name: Cosine Accuracy@20
263
+ - type: cosine_accuracy@50
264
+ value: 1.0
265
+ name: Cosine Accuracy@50
266
+ - type: cosine_accuracy@100
267
+ value: 1.0
268
+ name: Cosine Accuracy@100
269
+ - type: cosine_accuracy@150
270
+ value: 1.0
271
+ name: Cosine Accuracy@150
272
+ - type: cosine_accuracy@200
273
+ value: 1.0
274
+ name: Cosine Accuracy@200
275
+ - type: cosine_precision@1
276
+ value: 0.7335526315789473
277
+ name: Cosine Precision@1
278
+ - type: cosine_precision@20
279
+ value: 0.490296052631579
280
+ name: Cosine Precision@20
281
+ - type: cosine_precision@50
282
+ value: 0.3859868421052632
283
+ name: Cosine Precision@50
284
+ - type: cosine_precision@100
285
+ value: 0.3036184210526316
286
+ name: Cosine Precision@100
287
+ - type: cosine_precision@150
288
+ value: 0.25671052631578944
289
+ name: Cosine Precision@150
290
+ - type: cosine_precision@200
291
+ value: 0.2243421052631579
292
+ name: Cosine Precision@200
293
+ - type: cosine_recall@1
294
+ value: 0.010444132194039979
295
+ name: Cosine Recall@1
296
+ - type: cosine_recall@20
297
+ value: 0.13155047336746764
298
+ name: Cosine Recall@20
299
+ - type: cosine_recall@50
300
+ value: 0.2505336672030587
301
+ name: Cosine Recall@50
302
+ - type: cosine_recall@100
303
+ value: 0.385236752173816
304
+ name: Cosine Recall@100
305
+ - type: cosine_recall@150
306
+ value: 0.4811856092032869
307
+ name: Cosine Recall@150
308
+ - type: cosine_recall@200
309
+ value: 0.5543573441595541
310
+ name: Cosine Recall@200
311
+ - type: cosine_ndcg@1
312
+ value: 0.7335526315789473
313
+ name: Cosine Ndcg@1
314
+ - type: cosine_ndcg@20
315
+ value: 0.5307365824844119
316
+ name: Cosine Ndcg@20
317
+ - type: cosine_ndcg@50
318
+ value: 0.444220756668096
319
+ name: Cosine Ndcg@50
320
+ - type: cosine_ndcg@100
321
+ value: 0.43439492760298076
322
+ name: Cosine Ndcg@100
323
+ - type: cosine_ndcg@150
324
+ value: 0.47795065375131446
325
+ name: Cosine Ndcg@150
326
+ - type: cosine_ndcg@200
327
+ value: 0.5214067996485772
328
+ name: Cosine Ndcg@200
329
+ - type: cosine_mrr@1
330
+ value: 0.7335526315789473
331
+ name: Cosine Mrr@1
332
+ - type: cosine_mrr@20
333
+ value: 0.8432942331791015
334
+ name: Cosine Mrr@20
335
+ - type: cosine_mrr@50
336
+ value: 0.8432942331791015
337
+ name: Cosine Mrr@50
338
+ - type: cosine_mrr@100
339
+ value: 0.8432942331791015
340
+ name: Cosine Mrr@100
341
+ - type: cosine_mrr@150
342
+ value: 0.8432942331791015
343
+ name: Cosine Mrr@150
344
+ - type: cosine_mrr@200
345
+ value: 0.8432942331791015
346
+ name: Cosine Mrr@200
347
+ - type: cosine_map@1
348
+ value: 0.7335526315789473
349
+ name: Cosine Map@1
350
+ - type: cosine_map@20
351
+ value: 0.33452306527426573
352
+ name: Cosine Map@20
353
+ - type: cosine_map@50
354
+ value: 0.23271390759223323
355
+ name: Cosine Map@50
356
+ - type: cosine_map@100
357
+ value: 0.2054754140681634
358
+ name: Cosine Map@100
359
+ - type: cosine_map@150
360
+ value: 0.22090883820165566
361
+ name: Cosine Map@150
362
+ - type: cosine_map@200
363
+ value: 0.23840293273961974
364
+ name: Cosine Map@200
365
+ - type: cosine_map@500
366
+ value: 0.28749543302216074
367
+ name: Cosine Map@500
368
+ ---
369
+
370
+ # SentenceTransformer based on BAAI/bge-large-en-v1.5
371
+
372
+ This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [BAAI/bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5). It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
373
+
374
+ ## Model Details
375
+
376
+ ### Model Description
377
+ - **Model Type:** Sentence Transformer
378
+ - **Base model:** [BAAI/bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) <!-- at revision d4aa6901d3a41ba39fb536a557fa166f842b0e09 -->
379
+ - **Maximum Sequence Length:** 512 tokens
380
+ - **Output Dimensionality:** 1024 dimensions
381
+ - **Similarity Function:** Cosine Similarity
382
+ <!-- - **Training Dataset:** Unknown -->
383
+ <!-- - **Language:** Unknown -->
384
+ <!-- - **License:** Unknown -->
385
+
386
+ ### Model Sources
387
+
388
+ - **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
389
+ - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
390
+ - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
391
+
392
+ ### Full Model Architecture
393
+
394
+ ```
395
+ SentenceTransformer(
396
+ (0): Transformer({'max_seq_length': 512, 'do_lower_case': True}) with Transformer model: BertModel
397
+ (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
398
+ (2): Normalize()
399
+ )
400
+ ```
401
+
402
+ ## Usage
403
+
404
+ ### Direct Usage (Sentence Transformers)
405
+
406
+ First install the Sentence Transformers library:
407
+
408
+ ```bash
409
+ pip install -U sentence-transformers
410
+ ```
411
+
412
+ Then you can load this model and run inference.
413
+ ```python
414
+ from sentence_transformers import SentenceTransformer
415
+
416
+ # Download from the 🤗 Hub
417
+ model = SentenceTransformer("sentence_transformers_model_id")
418
+ # Run inference
419
+ sentences = [
420
+ "An insulation supervisor, regardless of the specific type of insulation material or installation area, requires strong project management skills, knowledge of building codes and safety regulations, and expertise in insulation techniques to oversee the installation process effectively and ensure quality standards are met.\n['insulation supervisor', 'supervisor of installation of insulating materials', 'supervisor of insulation materials installation', 'supervisor of installation of insulation', 'solid wall insulation installation supervisor', 'insulation installers supervisor', 'cavity wall insulation installation supervisor', 'loft insulation installation supervisor']",
421
+ "The skill of installing insulation material is primarily required by job roles such as insulation workers, HVAC technicians, and construction specialists, who are responsible for improving energy efficiency and thermal comfort in buildings by correctly fitting and fixing insulation materials in various structures.\n['install insulation material', 'insulate structure', 'fix insulation', 'insulation material installation', 'installation of insulation material', 'fitting insulation', 'insulating structure', 'installing insulation material', 'fixing insulation', 'fit insulation']",
422
+ "Job roles such as Food Safety Inspector, Public Health Officer, and Environmental Health Specialist require the skill of taking action on food safety violations to ensure compliance with health regulations and maintain public safety standards.\n['take action on food safety violations', 'invoke action on food safety violations', 'agree action on food safety violations', 'pursue action on food safety violations', 'determine action on food safety violations']",
423
+ ]
424
+ embeddings = model.encode(sentences)
425
+ print(embeddings.shape)
426
+ # [3, 1024]
427
+
428
+ # Get the similarity scores for the embeddings
429
+ similarities = model.similarity(embeddings, embeddings)
430
+ print(similarities.shape)
431
+ # [3, 3]
432
+ ```
433
+
434
+ <!--
435
+ ### Direct Usage (Transformers)
436
+
437
+ <details><summary>Click to see the direct usage in Transformers</summary>
438
+
439
+ </details>
440
+ -->
441
+
442
+ <!--
443
+ ### Downstream Usage (Sentence Transformers)
444
+
445
+ You can finetune this model on your own dataset.
446
+
447
+ <details><summary>Click to expand</summary>
448
+
449
+ </details>
450
+ -->
451
+
452
+ <!--
453
+ ### Out-of-Scope Use
454
+
455
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
456
+ -->
457
+
458
+ ## Evaluation
459
+
460
+ ### Metrics
461
+
462
+ #### Information Retrieval
463
+
464
+ * Dataset: `full_en`
465
+ * Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
466
+
467
+ | Metric | Value |
468
+ |:---------------------|:-----------|
469
+ | cosine_accuracy@1 | 0.7336 |
470
+ | cosine_accuracy@20 | 1.0 |
471
+ | cosine_accuracy@50 | 1.0 |
472
+ | cosine_accuracy@100 | 1.0 |
473
+ | cosine_accuracy@150 | 1.0 |
474
+ | cosine_accuracy@200 | 1.0 |
475
+ | cosine_precision@1 | 0.7336 |
476
+ | cosine_precision@20 | 0.4903 |
477
+ | cosine_precision@50 | 0.386 |
478
+ | cosine_precision@100 | 0.3036 |
479
+ | cosine_precision@150 | 0.2567 |
480
+ | cosine_precision@200 | 0.2243 |
481
+ | cosine_recall@1 | 0.0104 |
482
+ | cosine_recall@20 | 0.1316 |
483
+ | cosine_recall@50 | 0.2505 |
484
+ | cosine_recall@100 | 0.3852 |
485
+ | cosine_recall@150 | 0.4812 |
486
+ | cosine_recall@200 | 0.5544 |
487
+ | cosine_ndcg@1 | 0.7336 |
488
+ | cosine_ndcg@20 | 0.5307 |
489
+ | cosine_ndcg@50 | 0.4442 |
490
+ | cosine_ndcg@100 | 0.4344 |
491
+ | cosine_ndcg@150 | 0.478 |
492
+ | **cosine_ndcg@200** | **0.5214** |
493
+ | cosine_mrr@1 | 0.7336 |
494
+ | cosine_mrr@20 | 0.8433 |
495
+ | cosine_mrr@50 | 0.8433 |
496
+ | cosine_mrr@100 | 0.8433 |
497
+ | cosine_mrr@150 | 0.8433 |
498
+ | cosine_mrr@200 | 0.8433 |
499
+ | cosine_map@1 | 0.7336 |
500
+ | cosine_map@20 | 0.3345 |
501
+ | cosine_map@50 | 0.2327 |
502
+ | cosine_map@100 | 0.2055 |
503
+ | cosine_map@150 | 0.2209 |
504
+ | cosine_map@200 | 0.2384 |
505
+ | cosine_map@500 | 0.2875 |
506
+
507
+ <!--
508
+ ## Bias, Risks and Limitations
509
+
510
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
511
+ -->
512
+
513
+ <!--
514
+ ### Recommendations
515
+
516
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
517
+ -->
518
+
519
+ ## Training Details
520
+
521
+ ### Training Dataset
522
+
523
+ #### Unnamed Dataset
524
+
525
+ * Size: 114,699 training samples
526
+ * Columns: <code>anchor</code> and <code>positive</code>
527
+ * Approximate statistics based on the first 1000 samples:
528
+ | | anchor | positive |
529
+ |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
530
+ | type | string | string |
531
+ | details | <ul><li>min: 78 tokens</li><li>mean: 144.94 tokens</li><li>max: 354 tokens</li></ul> | <ul><li>min: 51 tokens</li><li>mean: 114.13 tokens</li><li>max: 274 tokens</li></ul> |
532
+ * Samples:
533
+ | anchor | positive |
534
+ |:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
535
+ | <code>A technical director or any of its synonyms requires a strong blend of technical expertise and leadership skills, including the ability to oversee technical operations, manage teams, and ensure the successful execution of technical projects while maintaining operational efficiency and innovation.<br>['technical director', 'technical and operations director', 'head of technical', 'director of technical arts', 'head of technical department', 'technical supervisor', 'technical manager']</code> | <code>Job roles that require promoting health and safety include occupational health and safety specialists, safety managers, and public health educators, all of whom work to ensure safe and healthy environments in workplaces and communities.<br>['promote health and safety', 'promote importance of health and safety', 'promoting health and safety', 'advertise health and safety']</code> |
536
+ | <code>A technical director or any of its synonyms requires a strong blend of technical expertise and leadership skills, including the ability to oversee technical operations, manage teams, and ensure the successful execution of technical projects while maintaining operational efficiency and innovation.<br>['technical director', 'technical and operations director', 'head of technical', 'director of technical arts', 'head of technical department', 'technical supervisor', 'technical manager']</code> | <code>Job roles that require organizing rehearsals include directors, choreographers, and conductors in theater, dance, and music ensembles, who must efficiently plan and schedule practice sessions to prepare performers for a successful final performance.<br>['organise rehearsals', 'organise rehearsal', 'organize rehearsals', 'plan rehearsals', 'arrange rehearsals', 'organising rehearsals', 'schedule rehearsals']</code> |
537
+ | <code>A technical director or any of its synonyms requires a strong blend of technical expertise and leadership skills, including the ability to oversee technical operations, manage teams, and ensure the successful execution of technical projects while maintaining operational efficiency and innovation.<br>['technical director', 'technical and operations director', 'head of technical', 'director of technical arts', 'head of technical department', 'technical supervisor', 'technical manager']</code> | <code>Job roles such as Health and Safety Managers, Environmental Health Officers, and Risk Management Specialists often require the skill of negotiating health and safety issues with third parties to ensure compliance and protection standards are met across different organizations and sites.<br>['negotiate health and safety issues with third parties', 'agree with third parties on health and safety', 'negotiate issues on health and safety with third parties', 'negotiate with third parties on health and safety issues', 'negotiate health and safety matters with third parties']</code> |
538
+ * Loss: [<code>CachedGISTEmbedLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters:
539
+ ```json
540
+ {'guide': SentenceTransformer(
541
+ (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: BertModel
542
+ (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
543
+ (2): Normalize()
544
+ ), 'temperature': 0.01, 'mini_batch_size': 32, 'margin_strategy': 'absolute', 'margin': 0.0}
545
+ ```
546
+
547
+ ### Training Hyperparameters
548
+ #### Non-Default Hyperparameters
549
+
550
+ - `eval_strategy`: steps
551
+ - `per_device_train_batch_size`: 128
552
+ - `per_device_eval_batch_size`: 128
553
+ - `gradient_accumulation_steps`: 2
554
+ - `num_train_epochs`: 5
555
+ - `warmup_ratio`: 0.05
556
+ - `log_on_each_node`: False
557
+ - `fp16`: True
558
+ - `dataloader_num_workers`: 4
559
+ - `ddp_find_unused_parameters`: True
560
+ - `batch_sampler`: no_duplicates
561
+
562
+ #### All Hyperparameters
563
+ <details><summary>Click to expand</summary>
564
+
565
+ - `overwrite_output_dir`: False
566
+ - `do_predict`: False
567
+ - `eval_strategy`: steps
568
+ - `prediction_loss_only`: True
569
+ - `per_device_train_batch_size`: 128
570
+ - `per_device_eval_batch_size`: 128
571
+ - `per_gpu_train_batch_size`: None
572
+ - `per_gpu_eval_batch_size`: None
573
+ - `gradient_accumulation_steps`: 2
574
+ - `eval_accumulation_steps`: None
575
+ - `torch_empty_cache_steps`: None
576
+ - `learning_rate`: 5e-05
577
+ - `weight_decay`: 0.0
578
+ - `adam_beta1`: 0.9
579
+ - `adam_beta2`: 0.999
580
+ - `adam_epsilon`: 1e-08
581
+ - `max_grad_norm`: 1.0
582
+ - `num_train_epochs`: 5
583
+ - `max_steps`: -1
584
+ - `lr_scheduler_type`: linear
585
+ - `lr_scheduler_kwargs`: {}
586
+ - `warmup_ratio`: 0.05
587
+ - `warmup_steps`: 0
588
+ - `log_level`: passive
589
+ - `log_level_replica`: warning
590
+ - `log_on_each_node`: False
591
+ - `logging_nan_inf_filter`: True
592
+ - `save_safetensors`: True
593
+ - `save_on_each_node`: False
594
+ - `save_only_model`: False
595
+ - `restore_callback_states_from_checkpoint`: False
596
+ - `no_cuda`: False
597
+ - `use_cpu`: False
598
+ - `use_mps_device`: False
599
+ - `seed`: 42
600
+ - `data_seed`: None
601
+ - `jit_mode_eval`: False
602
+ - `use_ipex`: False
603
+ - `bf16`: False
604
+ - `fp16`: True
605
+ - `fp16_opt_level`: O1
606
+ - `half_precision_backend`: auto
607
+ - `bf16_full_eval`: False
608
+ - `fp16_full_eval`: False
609
+ - `tf32`: None
610
+ - `local_rank`: 0
611
+ - `ddp_backend`: None
612
+ - `tpu_num_cores`: None
613
+ - `tpu_metrics_debug`: False
614
+ - `debug`: []
615
+ - `dataloader_drop_last`: True
616
+ - `dataloader_num_workers`: 4
617
+ - `dataloader_prefetch_factor`: None
618
+ - `past_index`: -1
619
+ - `disable_tqdm`: False
620
+ - `remove_unused_columns`: True
621
+ - `label_names`: None
622
+ - `load_best_model_at_end`: False
623
+ - `ignore_data_skip`: False
624
+ - `fsdp`: []
625
+ - `fsdp_min_num_params`: 0
626
+ - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
627
+ - `tp_size`: 0
628
+ - `fsdp_transformer_layer_cls_to_wrap`: None
629
+ - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
630
+ - `deepspeed`: None
631
+ - `label_smoothing_factor`: 0.0
632
+ - `optim`: adamw_torch
633
+ - `optim_args`: None
634
+ - `adafactor`: False
635
+ - `group_by_length`: False
636
+ - `length_column_name`: length
637
+ - `ddp_find_unused_parameters`: True
638
+ - `ddp_bucket_cap_mb`: None
639
+ - `ddp_broadcast_buffers`: False
640
+ - `dataloader_pin_memory`: True
641
+ - `dataloader_persistent_workers`: False
642
+ - `skip_memory_metrics`: True
643
+ - `use_legacy_prediction_loop`: False
644
+ - `push_to_hub`: False
645
+ - `resume_from_checkpoint`: None
646
+ - `hub_model_id`: None
647
+ - `hub_strategy`: every_save
648
+ - `hub_private_repo`: None
649
+ - `hub_always_push`: False
650
+ - `gradient_checkpointing`: False
651
+ - `gradient_checkpointing_kwargs`: None
652
+ - `include_inputs_for_metrics`: False
653
+ - `include_for_metrics`: []
654
+ - `eval_do_concat_batches`: True
655
+ - `fp16_backend`: auto
656
+ - `push_to_hub_model_id`: None
657
+ - `push_to_hub_organization`: None
658
+ - `mp_parameters`:
659
+ - `auto_find_batch_size`: False
660
+ - `full_determinism`: False
661
+ - `torchdynamo`: None
662
+ - `ray_scope`: last
663
+ - `ddp_timeout`: 1800
664
+ - `torch_compile`: False
665
+ - `torch_compile_backend`: None
666
+ - `torch_compile_mode`: None
667
+ - `include_tokens_per_second`: False
668
+ - `include_num_input_tokens_seen`: False
669
+ - `neftune_noise_alpha`: None
670
+ - `optim_target_modules`: None
671
+ - `batch_eval_metrics`: False
672
+ - `eval_on_start`: False
673
+ - `use_liger_kernel`: False
674
+ - `eval_use_gather_object`: False
675
+ - `average_tokens_across_devices`: False
676
+ - `prompts`: None
677
+ - `batch_sampler`: no_duplicates
678
+ - `multi_dataset_batch_sampler`: proportional
679
+
680
+ </details>
681
+
682
+ ### Training Logs
683
+ | Epoch | Step | Training Loss | full_en_cosine_ndcg@200 |
684
+ |:------:|:----:|:-------------:|:-----------------------:|
685
+ | -1 | -1 | - | 0.4795 |
686
+ | 0.0022 | 1 | 10.6462 | - |
687
+ | 0.2232 | 100 | 4.5115 | - |
688
+ | 0.4464 | 200 | 2.9237 | 0.5255 |
689
+ | 0.6696 | 300 | 2.5327 | - |
690
+ | 0.8929 | 400 | 2.3451 | 0.5305 |
691
+ | 1.1161 | 500 | 1.9882 | - |
692
+ | 1.3393 | 600 | 1.7738 | 0.5240 |
693
+ | 1.5625 | 700 | 1.7365 | - |
694
+ | 1.7857 | 800 | 1.6932 | 0.5251 |
695
+ | 2.0089 | 900 | 1.6184 | - |
696
+ | 2.2321 | 1000 | 1.285 | 0.5254 |
697
+ | 2.4554 | 1100 | 1.2651 | - |
698
+ | 2.6786 | 1200 | 1.2739 | 0.5238 |
699
+ | 2.9018 | 1300 | 1.2625 | - |
700
+ | 3.125 | 1400 | 1.0726 | 0.5251 |
701
+ | 3.3482 | 1500 | 0.9606 | - |
702
+ | 3.5714 | 1600 | 0.9594 | 0.5214 |
703
+
704
+
705
+ ### Framework Versions
706
+ - Python: 3.11.11
707
+ - Sentence Transformers: 4.1.0
708
+ - Transformers: 4.51.2
709
+ - PyTorch: 2.6.0+cu124
710
+ - Accelerate: 1.6.0
711
+ - Datasets: 3.5.0
712
+ - Tokenizers: 0.21.1
713
+
714
+ ## Citation
715
+
716
+ ### BibTeX
717
+
718
+ #### Sentence Transformers
719
+ ```bibtex
720
+ @inproceedings{reimers-2019-sentence-bert,
721
+ title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
722
+ author = "Reimers, Nils and Gurevych, Iryna",
723
+ booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
724
+ month = "11",
725
+ year = "2019",
726
+ publisher = "Association for Computational Linguistics",
727
+ url = "https://arxiv.org/abs/1908.10084",
728
+ }
729
+ ```
730
+
731
+ <!--
732
+ ## Glossary
733
+
734
+ *Clearly define terms in order to be accessible across audiences.*
735
+ -->
736
+
737
+ <!--
738
+ ## Model Card Authors
739
+
740
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
741
+ -->
742
+
743
+ <!--
744
+ ## Model Card Contact
745
+
746
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
747
+ -->
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