---
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:1056
- loss:BatchSemiHardTripletLoss
base_model: BAAI/bge-base-en
widget:
- source_sentence: '
Name : LearnTech Innovations
Category: Educational Software, Professional Development Solutions
Department: IT Operations
Location: Tokyo, Japan
Amount: 1523.45
Card: Technology Faculty Enhancement Series
Trip Name: unknown
'
sentences:
- '
Name : OptiNet Solutions
Category: Strategic Infrastructure Consulting, Advanced Data Solutions
Department: Engineering
Location: London, UK
Amount: 1289.99
Card: Next-Gen Network Design
Trip Name: unknown
'
- '
Name : SkillsBox Academy
Category: Online Education, Employee Training Platforms
Department: Engineering
Location: Chicago, IL
Amount: 1298.5
Card: Skill Development for New Technologies
Trip Name: unknown
'
- '
Name : Yue Hua
Category: HR & Employment Services
Department: Engineering
Location: Berlin, Germany
Amount: 3567.45
Card: Talent Acquisition Enhancement
Trip Name: unknown
'
- source_sentence: '
Name : Interlink Global Solutions
Category: Training Platforms, Professional Networking Services
Department: HR
Location: San Francisco, CA
Amount: 1342.55
Card: Executive Leadership Development
Trip Name: unknown
'
sentences:
- '
Name : Quantifire Insights
Category: Predictive Analytics Solutions
Department: Marketing
Location: Zurich, Switzerland
Amount: 1275.58
Card: Customer Engagement Enhancement
Trip Name: unknown
'
- '
Name : Insight Analytics
Category: Data Services & Analytics, Employee Training & Development
Department: Marketing
Location: Berlin, Germany
Amount: 873.29
Card: Market Research Initiative
Trip Name: unknown
'
- '
Name : GlobalSafe Solutions
Category: Risk Management Consultancy, International Insurance Brokerage
Department: Finance
Location: Zurich, Switzerland
Amount: 1175.65
Card: Annual Risk Assessment
Trip Name: unknown
'
- source_sentence: '
Name : SkyScale Services
Category: Global IT Solutions, Platform Integration
Department: IT Operations
Location: Dublin, Ireland
Amount: 1492.54
Card: Annual Platform Enhancement
Trip Name: unknown
'
sentences:
- '
Name : InterGlobe Connect
Category: Financial Services, Data Connectivity
Department: Finance
Location: London, UK
Amount: 152.79
Card: Overseas Financial Operations
Trip Name: unknown
'
- '
Name : SkyElevate Group
Category: Luxury Travel Services, Corporate Event Planning
Department: Executive
Location: Dubai, UAE
Amount: 2113.47
Card: Executive Strategy Retreat
Trip Name: Board of Directors Retreat
'
- '
Name : GlobalRes Workforce Solutions
Category: Remote Work Platforms, HR Technology Vendors
Department: Engineering
Location: Barcelona, Spain
Amount: 1894.27
Card: Hybrid Work Enablement
Trip Name: unknown
'
- source_sentence: '
Name : Nimbus Networks Inc.
Category: Cloud Services, Application Hosting
Department: Research & Development
Location: Austin, TX
Amount: 1134.67
Card: NextGen Application Deployment
Trip Name: unknown
'
sentences:
- '
Name : Kaleidoscope Interactive
Category: Interactive Software Platforms, Educational Content Distribution
Department: Engineering
Location: London, UK
Amount: 1852.37
Card: Innovative Education Initiative
Trip Name: unknown
'
- '
Name : RBS
Category: Financial Services, Business Consultancy
Department: Finance
Location: Toronto, Canada
Amount: 1134.28
Card: Cross-Border Transaction Facilitation
Trip Name: unknown
'
- '
Name : HexaGuard Systems
Category: Enterprise Software Solutions, Network Infrastructure Services
Department: IT Operations
Location: Toronto, Canada
Amount: 1254.78
Card: Integrated Security Enhancement Plan
Trip Name: unknown
'
- source_sentence: '
Name : SMRT
Category: Public Transportation, Transit Services
Department: Sales
Location: Los Angeles, CA
Amount: 85.0
Card: Sales Team Travel Budget
Trip Name: unknown
'
sentences:
- '
Name : Wellness Haven
Category: Employee Health Programs, Professional Development
Department: HR
Location: Munich, Germany
Amount: 762.35
Card: Corporate Wellness Initiatives
Trip Name: unknown
'
- '
Name : Elastic Habitat Solutions
Category: Cloud Enhancement Services, Data Analytics Tools
Department: IT Operations
Location: London, UK
Amount: 1489.57
Card: Scalable Data Initiative
Trip Name: unknown
'
- '
Name : NexaCloud Technologies
Category: Implement Services, Cloud Solutions
Department: IT Operations
Location: Berlin, Germany
Amount: 1490.65
Card: Cloud Optimization Initiative
Trip Name: unknown
'
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
- cosine_accuracy
- dot_accuracy
- manhattan_accuracy
- euclidean_accuracy
- max_accuracy
model-index:
- name: SentenceTransformer based on BAAI/bge-base-en
results:
- task:
type: triplet
name: Triplet
dataset:
name: bge base en train
type: bge-base-en-train
metrics:
- type: cosine_accuracy
value: 0.9753787878787878
name: Cosine Accuracy
- type: dot_accuracy
value: 0.02462121212121212
name: Dot Accuracy
- type: manhattan_accuracy
value: 0.9753787878787878
name: Manhattan Accuracy
- type: euclidean_accuracy
value: 0.9753787878787878
name: Euclidean Accuracy
- type: max_accuracy
value: 0.9753787878787878
name: Max Accuracy
- task:
type: triplet
name: Triplet
dataset:
name: bge base en eval
type: bge-base-en-eval
metrics:
- type: cosine_accuracy
value: 0.9813432835820896
name: Cosine Accuracy
- type: dot_accuracy
value: 0.018656716417910446
name: Dot Accuracy
- type: manhattan_accuracy
value: 0.9850746268656716
name: Manhattan Accuracy
- type: euclidean_accuracy
value: 0.9813432835820896
name: Euclidean Accuracy
- type: max_accuracy
value: 0.9850746268656716
name: Max Accuracy
---
# SentenceTransformer based on BAAI/bge-base-en
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [BAAI/bge-base-en](https://huggingface.co/BAAI/bge-base-en). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
## Model Details
### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [BAAI/bge-base-en](https://huggingface.co/BAAI/bge-base-en)
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 768 tokens
- **Similarity Function:** Cosine Similarity
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
### Full Model Architecture
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': True}) with Transformer model: BertModel
(1): Pooling({'word_embedding_dimension': 768, '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})
(2): Normalize()
)
```
## Usage
### Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
```bash
pip install -U sentence-transformers
```
Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("llazio/finetuned-bge-base-en")
# Run inference
sentences = [
'\nName : SMRT\nCategory: Public Transportation, Transit Services\nDepartment: Sales\nLocation: Los Angeles, CA\nAmount: 85.0\nCard: Sales Team Travel Budget\nTrip Name: unknown\n',
'\nName : Elastic Habitat Solutions\nCategory: Cloud Enhancement Services, Data Analytics Tools\nDepartment: IT Operations\nLocation: London, UK\nAmount: 1489.57\nCard: Scalable Data Initiative\nTrip Name: unknown\n',
'\nName : Wellness Haven\nCategory: Employee Health Programs, Professional Development\nDepartment: HR\nLocation: Munich, Germany\nAmount: 762.35\nCard: Corporate Wellness Initiatives\nTrip Name: unknown\n',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
```
## Evaluation
### Metrics
#### Triplet
* Dataset: `bge-base-en-train`
* Evaluated with [TripletEvaluator
](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
| Metric | Value |
|:-------------------|:-----------|
| cosine_accuracy | 0.9754 |
| dot_accuracy | 0.0246 |
| manhattan_accuracy | 0.9754 |
| euclidean_accuracy | 0.9754 |
| **max_accuracy** | **0.9754** |
#### Triplet
* Dataset: `bge-base-en-eval`
* Evaluated with [TripletEvaluator
](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
| Metric | Value |
|:-------------------|:-----------|
| cosine_accuracy | 0.9813 |
| dot_accuracy | 0.0187 |
| manhattan_accuracy | 0.9851 |
| euclidean_accuracy | 0.9813 |
| **max_accuracy** | **0.9851** |
## Training Details
### Training Dataset
#### Unnamed Dataset
* Size: 1,056 training samples
* Columns: sentence
and label
* Approximate statistics based on the first 1000 samples:
| | sentence | label |
|:--------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| type | string | int |
| details |
Name : Global Talent Network
Category: HR Consultancy Services, Corporate Event Organizers
Department: HR
Location: Los Angeles, CA
Amount: 1375.65
Card: Leadership Summit Coordination
Trip Name: unknown
| 0
|
|
Name : Baku
Category: Ride Sharing
Department: Sales
Location: Baku, Azerbaijan
Amount: 1247.88
Card: Client Engagement Activities
Trip Name: unknown
| 1
|
|
Name : Harris Consulting Group
Category: Business Consulting, Legal Advisory
Department: Finance
Location: Toronto, Canada
Amount: 1325.45
Card: Strategic Development Fund
Trip Name: unknown
| 2
|
* Loss: [BatchSemiHardTripletLoss
](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#batchsemihardtripletloss)
### Evaluation Dataset
#### Unnamed Dataset
* Size: 264 evaluation samples
* Columns: sentence
and label
* Approximate statistics based on the first 264 samples:
| | sentence | label |
|:--------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| type | string | int |
| details |
Name : Fernández & Co. Services
Category: Property Management, Facility Services
Department: Office Administration
Location: Madrid, Spain
Amount: 1245.67
Card: Monthly Facility Operations
Trip Name: unknown
| 18
|
|
Name : Habitat Solutions
Category: Cloud Enhancement Services, Data Analytics Tools
Department: IT Operations
Location: London, UK
Amount: 1489.57
Card: Scalable Data Initiative
Trip Name: unknown
| 13
|
|
Name : Gandalf
Category: Financial Services, Consulting
Department: Finance
Location: Singapore
Amount: 457.29
Card: Financial Advisory Services
Trip Name: unknown
| 21
|
* Loss: [BatchSemiHardTripletLoss
](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#batchsemihardtripletloss)
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: steps
- `per_device_train_batch_size`: 16
- `per_device_eval_batch_size`: 16
- `learning_rate`: 2e-05
- `num_train_epochs`: 5
- `warmup_ratio`: 0.1
- `batch_sampler`: no_duplicates
#### All Hyperparameters