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README.md

@@ -9,35 +9,34 @@ tags:
 - sentence-similarity
 - feature-extraction
 - generated_from_trainer
-- dataset_size:1043
+- dataset_size:8408
 - loss:CosineSimilarityLoss
 widget:
-- source_sentence: vice president customer quality
+- source_sentence: president
   sentences:
-  - executive committee senior vice president corp development strategy bd&l & mergers
-    and acquisitions
-  - vice president & chief financial officer medical division
-  - vice president
-- source_sentence: chief officer of human resources
+  - assistante de banque priv e banco santander rio
+  - worldwide executive vice president corindus a siemens healthineers company
+  - soporte t cnico superior
+- source_sentence: chief business strategy officer
   sentences:
-  - chief human resources officer
-  - director healthcare investment banking
-  - consultor en desarrollo empresarial y capacitador part time
-- source_sentence: gerente general en safs de tamaño medio
+  - sub jefe
+  - analista senior recursos humanos sales staff and logistics
+  - subgerente sostenibilidad y hseq
+- source_sentence: gerente de planificación
   sentences:
-  - director ejecutivo
-  - ' president respiratory interventions operating unit'
-  - senior facilities engineering manager
-- source_sentence: chief technology and digital officer
+  - analista de soporte web
+  - director
+  - gestion calidad
+- source_sentence: global human resources leader
   sentences:
-  - vice president product international
-  - executive director digital applications
-  - senior vice president operations
-- source_sentence: vice president of accounting
+  - director manufacturing engineering
+  - quality specialist
+  - asesoramiento para comprar inmuebles en uruguay paraguay espa a y usa
+- source_sentence: commercial manager
   sentences:
-  - director of product management
-  - regional vice president of operations
-  - purchasing coordinator hv battery and powertrain
+  - jefe de turno planta envasado de vinos
+  - gerente de operaciones
+  - vice president of finance americas
 ---
 
 # SentenceTransformer based on sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
@@ -89,9 +88,9 @@ from sentence_transformers import SentenceTransformer
 model = SentenceTransformer("sentence_transformers_model_id")
 # Run inference
 sentences = [
-    'vice president of accounting',
-    'purchasing coordinator hv battery and powertrain',
-    'regional vice president of operations',
+    'commercial manager',
+    'gerente de operaciones',
+    'vice president of finance americas',
 ]
 embeddings = model.encode(sentences)
 print(embeddings.shape)
@@ -146,19 +145,19 @@ You can finetune this model on your own dataset.
 #### Unnamed Dataset
 
 
-* Size: 1,043 training samples
+* Size: 8,408 training samples
 * Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>label</code>
 * Approximate statistics based on the first 1000 samples:
-  |         | sentence_0                                                                       | sentence_1                                                                       | label                                                          |
-  |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------|
-  | type    | string                                                                           | string                                                                           | float                                                          |
-  | details | <ul><li>min: 3 tokens</li><li>mean: 6.62 tokens</li><li>max: 12 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 7.77 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.13</li><li>max: 1.0</li></ul> |
+  |         | sentence_0                                                                      | sentence_1                                                                       | label                                                          |
+  |:--------|:--------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------|
+  | type    | string                                                                          | string                                                                           | float                                                          |
+  | details | <ul><li>min: 3 tokens</li><li>mean: 6.2 tokens</li><li>max: 12 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 7.75 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.06</li><li>max: 1.0</li></ul> |
 * Samples:
-  | sentence_0                                   | sentence_1                                                                 | label            |
-  |:---------------------------------------------|:---------------------------------------------------------------------------|:-----------------|
-  | <code>vice president quality</code>          | <code>director merger & acquisition mergers and acquisitions office</code> | <code>0.0</code> |
-  | <code>chief executive officer</code>         | <code>vice president defense business unit</code>                          | <code>0.0</code> |
-  | <code>vice president customer quality</code> | <code>director major & planned gifts regions hospital foundation</code>    | <code>0.0</code> |
+  | sentence_0                              | sentence_1                                                                    | label            |
+  |:----------------------------------------|:------------------------------------------------------------------------------|:-----------------|
+  | <code>strategic planning manager</code> | <code>senior brand manager uap southern cone & personal care cdm chile</code> | <code>0.0</code> |
+  | <code>director de planificacion</code>  | <code>key account manager tiendas paris</code>                                | <code>0.0</code> |
+  | <code>gerente general</code>            | <code>analista de cobranza</code>                                             | <code>0.0</code> |
 * Loss: [<code>CosineSimilarityLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
   ```json
   {
@@ -171,7 +170,7 @@ You can finetune this model on your own dataset.
 
 - `per_device_train_batch_size`: 16
 - `per_device_eval_batch_size`: 16
-- `num_train_epochs`: 1
+- `num_train_epochs`: 50
 - `multi_dataset_batch_sampler`: round_robin
 
 #### All Hyperparameters
@@ -193,7 +192,7 @@ You can finetune this model on your own dataset.
 - `adam_beta2`: 0.999
 - `adam_epsilon`: 1e-08
 - `max_grad_norm`: 1
-- `num_train_epochs`: 1
+- `num_train_epochs`: 50
 - `max_steps`: -1
 - `lr_scheduler_type`: linear
 - `lr_scheduler_kwargs`: {}
@@ -288,6 +287,63 @@ You can finetune this model on your own dataset.
 
 </details>
 
+### Training Logs
+| Epoch   | Step  | Training Loss |
+|:-------:|:-----:|:-------------:|
+| 0.9506  | 500   | 0.0434        |
+| 1.9011  | 1000  | 0.0135        |
+| 2.8517  | 1500  | 0.0072        |
+| 3.8023  | 2000  | 0.0056        |
+| 4.7529  | 2500  | 0.0044        |
+| 5.7034  | 3000  | 0.0038        |
+| 6.6540  | 3500  | 0.0034        |
+| 7.6046  | 4000  | 0.0032        |
+| 8.5551  | 4500  | 0.0029        |
+| 9.5057  | 5000  | 0.0028        |
+| 10.4563 | 5500  | 0.0026        |
+| 11.4068 | 6000  | 0.0025        |
+| 12.3574 | 6500  | 0.0026        |
+| 13.3080 | 7000  | 0.0023        |
+| 14.2586 | 7500  | 0.0023        |
+| 15.2091 | 8000  | 0.0023        |
+| 16.1597 | 8500  | 0.0022        |
+| 17.1103 | 9000  | 0.0021        |
+| 18.0608 | 9500  | 0.0019        |
+| 19.0114 | 10000 | 0.0021        |
+| 19.9620 | 10500 | 0.0019        |
+| 20.9125 | 11000 | 0.0019        |
+| 21.8631 | 11500 | 0.0016        |
+| 22.8137 | 12000 | 0.0018        |
+| 23.7643 | 12500 | 0.0018        |
+| 24.7148 | 13000 | 0.0018        |
+| 25.6654 | 13500 | 0.0016        |
+| 26.6160 | 14000 | 0.0017        |
+| 27.5665 | 14500 | 0.0016        |
+| 28.5171 | 15000 | 0.0016        |
+| 29.4677 | 15500 | 0.0016        |
+| 30.4183 | 16000 | 0.0016        |
+| 31.3688 | 16500 | 0.0019        |
+| 32.3194 | 17000 | 0.0018        |
+| 33.2700 | 17500 | 0.0017        |
+| 34.2205 | 18000 | 0.0016        |
+| 35.1711 | 18500 | 0.0016        |
+| 36.1217 | 19000 | 0.0016        |
+| 37.0722 | 19500 | 0.0015        |
+| 38.0228 | 20000 | 0.0012        |
+| 38.9734 | 20500 | 0.0015        |
+| 39.9240 | 21000 | 0.0015        |
+| 40.8745 | 21500 | 0.0013        |
+| 41.8251 | 22000 | 0.0014        |
+| 42.7757 | 22500 | 0.0014        |
+| 43.7262 | 23000 | 0.0014        |
+| 44.6768 | 23500 | 0.0013        |
+| 45.6274 | 24000 | 0.0012        |
+| 46.5779 | 24500 | 0.0014        |
+| 47.5285 | 25000 | 0.0012        |
+| 48.4791 | 25500 | 0.0013        |
+| 49.4297 | 26000 | 0.0013        |
+
+
 ### Framework Versions
 - Python: 3.8.5
 - Sentence Transformers: 3.0.1

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:b69a4fffcc06b0364d9c0218b2133c7f68d5baaf76631b46ef8a023f61430847
 size 470682214