---
base_model: sentence-transformers/multi-qa-MiniLM-L6-cos-v1
datasets: []
language: []
library_name: sentence-transformers
metrics:
- pearson_cosine
- spearman_cosine
- pearson_manhattan
- spearman_manhattan
- pearson_euclidean
- spearman_euclidean
- pearson_dot
- spearman_dot
- pearson_max
- spearman_max
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:3192024
- loss:CosineSimilarityLoss
widget:
- source_sentence: Must have experience in interdisciplinary collaboration
sentences:
- Nurse Coordinator specializing in advanced heart failure programs at The Queen's
Health System. Skilled in patient care coordination, clinical assessments, and
interdisciplinary collaboration. Experienced in managing complex health cases
and ensuring compliance with healthcare regulations. Proficient in utilizing advanced
medical technologies and technologies to enhance patient outcomes. Strong background
in nonprofit healthcare environments, contributing to optimal health and wellness
initiatives.
- Administrative Assistant in the judiciary with experience at the Minnesota Judicial
Branch and Mayo Clinic. Skilled in managing administrative tasks, coordinating
schedules, and supporting judicial processes. Proficient in office software and
communication tools. Previous roles include bank teller positions, enhancing customer
service and financial transactions. Strong organizational skills and attention
to detail, contributing to efficient operations in high-pressure environments.
- Area Manager in facilities services with expertise in managing public parks, campgrounds,
and recreational facilities. Skilled in operational management, team leadership,
and customer service. Proven track record in enhancing service delivery and operational
efficiency. Previous roles include Management Team and Accounts Payable Manager,
demonstrating versatility across various industries. Strong background in office
management and office operations, contributing to a well-rounded understanding
of facility management practices.
- source_sentence: Must have a customer service orientation
sentences:
- Research Assistant in biotechnology with expertise in Molecular Biology, Protein
Expression, Purification, and Crystallization. Currently employed at Seagen, contributing
to innovative cancer treatments. Holds a B.S. in Biochemistry and minors in Chemistry
and Spanish. Previous experience includes roles as a Manufacturing Technician
at AGC Biologics and undergraduate research at NG Lab and Mueller Lab, focusing
on recombinant human proteins and protein processing. Proficient in leading project
cooperation and public speaking.
- Instructional Developer with a Master's in Human Resource Development, specializing
in learning solutions across various media platforms. Experienced in storyboarding,
animation, videography, and post-production. Proven track record in e-learning
design and development, team leadership, and creative problem-solving. Currently
employed at The University of Texas Health Science Center at Houston, focusing
on enhancing organizational value through tailored corporate learning. Previous
roles include Learning Consultant at Strategic Ascent and Assistant Manager at
Cicis Pizza. Strong background in healthcare and professional training industries.
- Human Resource professional with expertise in hiring, compliance, benefits, and
compensation within the hospitality and semiconductor industries. Currently a
Talent Acquisition Specialist at MKS Instruments, skilled in relationship building
and attention to detail. Previous roles include Recruitment Manager at Block by
Block and Talent Acquisition Specialist at Manpower. Proficient in advanced computer
skills and a customer service orientation. Experienced in staffing management
and recruitment strategies, with a strong focus on enhancing workforce capabilities
and fostering client relationships.
- source_sentence: Must be proficient in graphic design software
sentences:
- Senior Software Engineer with expertise in developing innovative solutions for
the aviation and defense industries. Currently at Delta Flight Products, specializing
in aircraft cabin interiors and avionics. Proficient in backend ETL processes,
REST API development, and software development life cycle. Previous experience
includes roles at Cisco, Thales, Safran, and FatPipe Networks, focusing on enhancing
operational efficiency and user experience. Holds multiple patents for web application
design and deployment. Strong background in collaborating with cross-functional
teams to deliver high-quality software solutions.
- Client Advisor in financial services with a strong background in luxury goods
and retail. Currently at Louis Vuitton, specializing in client relationship management
and personalized service. Previously worked at Salvatore Ferragano, enhancing
client engagement and driving sales. Experienced in marketing management from
SkPros, focusing on brand strategy and market analysis. Proficient in leveraging
data to inform decision-making and improve client experiences.
- Weld Process Specialist at Airgas with expertise in industrial automation and
chemicals. Skilled in Resistance weld gun calibration, schedule database management,
and asset locating matrix creation. Previous experience as a Welding Engineer
at R&E Automated, providing support in automation systems for manufacturing applications.
Proficient in DCEN and various welding techniques, including Fanuc and Motoman.
Background includes roles in drafting and welding, enhancing fabrication efficiency
and quality. Strong foundation in mechanical design and engineering principles,
with a focus on improving performance and performance in manufacturing environments.
- source_sentence: Must have experience in pharmaceutical marketing
sentences:
- Brand Influencer specializing in Black Literary, Culture, and Lifestyle. Certified
UrbanAg with over 20 years of experience in urban agriculture consulting and retail
operations. Currently supervises community gardens at Chicago Botanic Garden,
educating residents on organic growing methods and addressing nutrition, food
security, and healthy lifestyle options. Previously served as president of Af-Am
Bookstore, demonstrating entrepreneurial skills and community engagement. Expertise
in marketing and advertising, with a focus on enhancing community engagement and
promoting sustainable practices.
- Experienced Studio Manager and Executive Producer in media production, specializing
in immersive entertainment and virtual environments. Proficient in business planning,
team building, fundraising, and management. Co-founder of Dirty Secret, focusing
on brand activation and custom worlds. Previous roles at Wevr involved production
coordination and project management, with a strong background in arts and design.
Holds a degree from California State University-Los Angeles.
- Owner and CEO of Cake N Wings, a catering company specializing in food and travel
PR. Experienced in public relations across health, technology, and entertainment
sectors. Proven track record in developing innovative urban cuisine and enhancing
customer experiences. Previous roles include account executive at Development
Counsellors International and public relations manager at Creole Restaurant. Skilled
in brand development, event management, and community engagement.
- source_sentence: Must have experience in software development
sentences:
- Multi-skilled Business Analytics professional with a Master’s in Business Analytics
and a dual MBA. Experienced in data analytics, predictive modeling, and project
management within the health and wellness sector. Proficient in extracting, summarizing,
and analyzing claims databases and healthcare analytics. Skilled in statistical
analysis, database management, and data visualization. Previous roles include
Business Analytics Advisor at Cigna Healthcare and Informatics Senior Specialist
at Cigna Healthcare. Strong leadership and project management abilities, with
a solid foundation in healthcare economics and outcomes observational research.
Familiar with Base SAS 9.2, SAS EG, SAS EM, SAS JMP, Tableau, and Oracle Crystal
Ball.
- Assistant Vice President in commercial real estate financing with a strong background
in banking. Experienced in business banking and branch management, having held
roles as Assistant Vice President and Business Banking Officer. Proven track record
in business development and branch operations within a large independent bank.
Skilled in building client relationships and driving financial growth. Holds expertise
in managing diverse teams and enhancing operational efficiency. Previous experience
includes branch management across multiple branches, demonstrating a commitment
to community engagement and financial wellness.
- CEO of IMPROVLearning, specializing in e-learning and driver education. Founded
and managed multiple ventures in training, healthcare, and real estate. Proven
track record of expanding product offerings and achieving recognition on the Inc
500/5000 list. Active board member of the LA Chapter of the Entrepreneur Organization,
contributing to the growth of over 3 million students. Experienced in venture
capital and entrepreneurship, with a focus on innovative training solutions and
community engagement. Active member of various organizations, including the Entrepreneurs'
Organization and the Los Angeles County Business Federation.
model-index:
- name: SentenceTransformer based on sentence-transformers/multi-qa-MiniLM-L6-cos-v1
results:
- task:
type: semantic-similarity
name: Semantic Similarity
dataset:
name: validation
type: validation
metrics:
- type: pearson_cosine
value: 0.9594453206302572
name: Pearson Cosine
- type: spearman_cosine
value: 0.860568334150162
name: Spearman Cosine
- type: pearson_manhattan
value: 0.9436690128729379
name: Pearson Manhattan
- type: spearman_manhattan
value: 0.8604275677997159
name: Spearman Manhattan
- type: pearson_euclidean
value: 0.9443183012069103
name: Pearson Euclidean
- type: spearman_euclidean
value: 0.8605683342374743
name: Spearman Euclidean
- type: pearson_dot
value: 0.9594453207129489
name: Pearson Dot
- type: spearman_dot
value: 0.8605683341225518
name: Spearman Dot
- type: pearson_max
value: 0.9594453207129489
name: Pearson Max
- type: spearman_max
value: 0.8605683342374743
name: Spearman Max
---
# SentenceTransformer based on sentence-transformers/multi-qa-MiniLM-L6-cos-v1
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/multi-qa-MiniLM-L6-cos-v1](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1). It maps sentences & paragraphs to a 384-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:** [sentence-transformers/multi-qa-MiniLM-L6-cos-v1](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1)
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 384 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': False}) with Transformer model: BertModel
(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})
(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("sentence_transformers_model_id")
# Run inference
sentences = [
'Must have experience in software development',
"CEO of IMPROVLearning, specializing in e-learning and driver education. Founded and managed multiple ventures in training, healthcare, and real estate. Proven track record of expanding product offerings and achieving recognition on the Inc 500/5000 list. Active board member of the LA Chapter of the Entrepreneur Organization, contributing to the growth of over 3 million students. Experienced in venture capital and entrepreneurship, with a focus on innovative training solutions and community engagement. Active member of various organizations, including the Entrepreneurs' Organization and the Los Angeles County Business Federation.",
'Multi-skilled Business Analytics professional with a Master’s in Business Analytics and a dual MBA. Experienced in data analytics, predictive modeling, and project management within the health and wellness sector. Proficient in extracting, summarizing, and analyzing claims databases and healthcare analytics. Skilled in statistical analysis, database management, and data visualization. Previous roles include Business Analytics Advisor at Cigna Healthcare and Informatics Senior Specialist at Cigna Healthcare. Strong leadership and project management abilities, with a solid foundation in healthcare economics and outcomes observational research. Familiar with Base SAS 9.2, SAS EG, SAS EM, SAS JMP, Tableau, and Oracle Crystal Ball.',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 384]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
```
## Evaluation
### Metrics
#### Semantic Similarity
* Dataset: `validation`
* Evaluated with [EmbeddingSimilarityEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
| Metric | Value |
|:-------------------|:-----------|
| pearson_cosine | 0.9594 |
| spearman_cosine | 0.8606 |
| pearson_manhattan | 0.9437 |
| spearman_manhattan | 0.8604 |
| pearson_euclidean | 0.9443 |
| spearman_euclidean | 0.8606 |
| pearson_dot | 0.9594 |
| spearman_dot | 0.8606 |
| pearson_max | 0.9594 |
| **spearman_max** | **0.8606** |
## Training Details
### Training Dataset
#### Unnamed Dataset
* Size: 3,192,024 training samples
* Columns: sentence_0, sentence_1, and label
* Approximate statistics based on the first 1000 samples:
| | sentence_0 | sentence_1 | label |
|:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:--------------------------------------------------------------|
| type | string | string | float |
| details | - min: 6 tokens
- mean: 9.15 tokens
- max: 17 tokens
| - min: 53 tokens
- mean: 93.6 tokens
- max: 150 tokens
| - min: 0.0
- mean: 0.5
- max: 1.0
|
* Samples:
| sentence_0 | sentence_1 | label |
|:----------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
| Must have experience in software development | Executive Assistant with a strong background in real estate and financial services. Experienced in managing executive schedules, coordinating communications, and supporting investment banking operations. Proficient in office management software and adept at multitasking in fast-paced environments. Previous roles at Blackstone, Piper Sandler, and Broe Real Estate Group, where responsibilities included supporting high-level executives and enhancing operational efficiency. Skilled in fostering relationships and facilitating smooth transitions in fast-paced settings. | 0.0 |
| Must have experience in overseeing service delivery for health initiatives | Director of Solution Strategy in health, wellness, and fitness, specializing in relationship building and strategy execution. Experienced in overseeing service delivery and performance management for telehealth and digital health initiatives at Blue Cross Blue Shield of Massachusetts. Proven track record in vendor lifecycle management, contract strategy, and operational leadership. Skilled in developing standardized wellness programs and enhancing client satisfaction through innovative solutions. Strong background in managing cross-functional teams and driving performance metrics in health engagement and wellness services. | 1.0 |
| Must have experience collaborating with Fortune 500 companies | Senior Sales and Business Development Manager in the energy sector, specializing in increasing profitable sales for small to large companies. Proven track record in relationship building, team management, and strategy development. Experienced in collaborating with diverse stakeholders, including Fortune 500 companies and small to large privately held companies. Previous roles include Vice President of Operations at NovaStar LP and Director of Sales at NovaStar Mortgage and Athlon Solutions. Strong communicator and team player, with a focus on customer needs and operational efficiency. | 1.0 |
* Loss: [CosineSimilarityLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
```json
{
"loss_fct": "torch.nn.modules.loss.MSELoss"
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: steps
- `per_device_train_batch_size`: 128
- `per_device_eval_batch_size`: 128
- `num_train_epochs`: 1.0
- `multi_dataset_batch_sampler`: round_robin
#### All Hyperparameters
Click to expand
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: steps
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 128
- `per_device_eval_batch_size`: 128
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 1
- `eval_accumulation_steps`: None
- `torch_empty_cache_steps`: None
- `learning_rate`: 5e-05
- `weight_decay`: 0.0
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1
- `num_train_epochs`: 1.0
- `max_steps`: -1
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: {}
- `warmup_ratio`: 0.0
- `warmup_steps`: 0
- `log_level`: passive
- `log_level_replica`: warning
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `save_safetensors`: True
- `save_on_each_node`: False
- `save_only_model`: False
- `restore_callback_states_from_checkpoint`: False
- `no_cuda`: False
- `use_cpu`: False
- `use_mps_device`: False
- `seed`: 42
- `data_seed`: None
- `jit_mode_eval`: False
- `use_ipex`: False
- `bf16`: False
- `fp16`: False
- `fp16_opt_level`: O1
- `half_precision_backend`: auto
- `bf16_full_eval`: False
- `fp16_full_eval`: False
- `tf32`: None
- `local_rank`: 0
- `ddp_backend`: None
- `tpu_num_cores`: None
- `tpu_metrics_debug`: False
- `debug`: []
- `dataloader_drop_last`: False
- `dataloader_num_workers`: 0
- `dataloader_prefetch_factor`: None
- `past_index`: -1
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: False
- `ignore_data_skip`: False
- `fsdp`: []
- `fsdp_min_num_params`: 0
- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
- `fsdp_transformer_layer_cls_to_wrap`: None
- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
- `deepspeed`: None
- `label_smoothing_factor`: 0.0
- `optim`: adamw_torch
- `optim_args`: None
- `adafactor`: False
- `group_by_length`: False
- `length_column_name`: length
- `ddp_find_unused_parameters`: None
- `ddp_bucket_cap_mb`: None
- `ddp_broadcast_buffers`: False
- `dataloader_pin_memory`: True
- `dataloader_persistent_workers`: False
- `skip_memory_metrics`: True
- `use_legacy_prediction_loop`: False
- `push_to_hub`: False
- `resume_from_checkpoint`: None
- `hub_model_id`: None
- `hub_strategy`: every_save
- `hub_private_repo`: False
- `hub_always_push`: False
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `eval_do_concat_batches`: True
- `fp16_backend`: auto
- `push_to_hub_model_id`: None
- `push_to_hub_organization`: None
- `mp_parameters`:
- `auto_find_batch_size`: False
- `full_determinism`: False
- `torchdynamo`: None
- `ray_scope`: last
- `ddp_timeout`: 1800
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `dispatch_batches`: None
- `split_batches`: None
- `include_tokens_per_second`: False
- `include_num_input_tokens_seen`: False
- `neftune_noise_alpha`: None
- `optim_target_modules`: None
- `batch_eval_metrics`: False
- `eval_on_start`: False
- `eval_use_gather_object`: False
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: round_robin