metadata

tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:212
  - loss:BatchSemiHardTripletLoss
base_model: BAAI/bge-base-en
widget:
  - source_sentence: |

      Name : TeleMart Connect
      Category: Networking Solutions, Business Communication Services
      Department: IT Operations
      Location: Geneva, Switzerland
      Amount: 1347.65
      Card: Integrated Communication Network Setup
      Trip Name: unknown
    sentences:
      - |

        Name : Midnight Brasserie
        Category: Culinary Experience, Event Catering
        Department: Marketing
        Location: Paris, France
        Amount: 456.87
        Card: Quarterly Team Building
        Trip Name: Summer Collaboration Retreat
      - |

        Name : PanEurope Consulting Group
        Category: Organizational Strategy, Executive Training
        Department: Executive
        Location: Brussels, Belgium
        Amount: 1359.5
        Card: Leadership Enhancement
        Trip Name: unknown
      - |

        Name : Stanford Graphics
        Category: Printed Materials, Corporate Identity Design
        Department: Office Administration
        Location: London, UK
        Amount: 348.79
        Card: Annual Business Stationery Restock
        Trip Name: unknown
  - source_sentence: |

      Name : Zero One
      Category: Media Production
      Department: Marketing
      Location: New York, NY
      Amount: 7500.0
      Card: Sales Operating Budget
      Trip Name: unknown
    sentences:
      - |

        Name : Connectiva Innovations
        Category: Telecommunications, Software Services
        Department: IT Operations
        Location: Lisbon, Portugal
        Amount: 1489.92
        Card: Enhanced Connectivity Solutions
        Trip Name: unknown
      - |

        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 : Serenity Solutions
        Category: Office Wellness Solutions
        Department: Office Administration
        Location: Munich, Germany
        Amount: 772.58
        Card: Ergonomic Office Enhancements
        Trip Name: unknown
  - source_sentence: |

      Name : Cosmic Enterprise Solutions
      Category: Cloud Services, Professional Networking
      Department: Executive
      Location: Zurich, Switzerland
      Amount: 1850.55
      Card: Strategic Partnership Development
      Trip Name: unknown
    sentences:
      - |

        Name : Arcsys
        Category: Software Solutions, Cloud Services
        Department: IT Operations
        Location: Berlin, Germany
        Amount: 2205.5
        Card: Integrated Infrastructure Solutions
        Trip Name: unknown
      - |

        Name : Streamline Financial Systems
        Category: Financial Management Software, Subscription Analytics
        Department: Finance
        Location: San Francisco, USA
        Amount: 1389.56
        Card: Integrated Revenue Solutions
        Trip Name: unknown
      - |

        Name : Rosetta Tech
        Category: Technology Supplies, Software Solutions
        Department: Research & Development
        Location: Hamburg, Germany
        Amount: 2129.49
        Card: Advanced Research Toolkit Acquisition
        Trip Name: unknown
  - source_sentence: |

      Name : Pardalis Digital
      Category: Data Analytics Platform, Professional Networking Service
      Department: Sales
      Location: Dublin, Ireland
      Amount: 1456.75
      Card: Sales Intelligence & Networking Platform
      Trip Name: unknown
    sentences:
      - |

        Name : Globex Regulatory Services
        Category: Professional Services, Legal Consulting
        Department: Compliance
        Location: Brussels, Belgium
        Amount: 993.47
        Card: International Compliance Alignment
        Trip Name: unknown
      - |

        Name : Globex Vitality Solutions
        Category: Wellness Program Facilitator, Corporate Subscription Services
        Department: HR
        Location: Dublin, Ireland
        Amount: 1023.47
        Card: Corporate Wellness Enhancement
        Trip Name: unknown
      - |

        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
  - source_sentence: |

      Name : FTC
      Category: Regulatory Compliance Services, Business Consulting
      Department: Legal
      Location: Toronto, Canada
      Amount: 3594.76
      Card: Annual Compliance Assessment
      Trip Name: unknown
    sentences:
      - |

        Name : Agora Services
        Category: Office Equipment Maintenance, IT Support & Maintenance
        Department: Office Administration
        Location: Berlin, Germany
        Amount: 877.29
        Card: Quarterly Equipment Evaluation
        Trip Name: unknown
      - |

        Name : Inkflow Media Solutions
        Category: Content Distribution Services, Print Media Supplies
        Department: Marketing
        Location: Amsterdam, Netherlands
        Amount: 1598.32
        Card: Print and Digital Campaign Integration
        Trip Name: unknown
      - |

        Name : Luxe Stay and Events
        Category: Hospitality Services, Event Planning
        Department: Marketing
        Location: London, UK
        Amount: 1138.75
        Card: Annual Retreat Planning
        Trip Name: Team Building Retreat
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
  - cosine_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: 0.8820754885673523
            name: Cosine Accuracy

SentenceTransformer based on BAAI/bge-base-en

This is a sentence-transformers model finetuned from 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
Maximum Sequence Length: 512 tokens
Output Dimensionality: 768 dimensions
Similarity Function: Cosine Similarity

Model Sources

Documentation: Sentence Transformers Documentation
Repository: Sentence Transformers on GitHub
Hugging Face: Sentence Transformers on Hugging Face

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:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("bge-base-en")
# Run inference
sentences = [
    '\nName : FTC\nCategory: Regulatory Compliance Services, Business Consulting\nDepartment: Legal\nLocation: Toronto, Canada\nAmount: 3594.76\nCard: Annual Compliance Assessment\nTrip Name: unknown\n',
    '\nName : Luxe Stay and Events\nCategory: Hospitality Services, Event Planning\nDepartment: Marketing\nLocation: London, UK\nAmount: 1138.75\nCard: Annual Retreat Planning\nTrip Name: Team Building Retreat\n',
    '\nName : Inkflow Media Solutions\nCategory: Content Distribution Services, Print Media Supplies\nDepartment: Marketing\nLocation: Amsterdam, Netherlands\nAmount: 1598.32\nCard: Print and Digital Campaign Integration\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

Metric	Value
cosine_accuracy	0.8821

Training Details

Training Dataset

Unnamed Dataset

Size: 212 training samples
Columns: sentence and label

Approximate statistics based on the first 212 samples:

	sentence	label
type	string	int
details	min: 33 tokens mean: 39.92 tokens max: 49 tokens	0: ~4.72% 1: ~3.30% 2: ~2.83% 3: ~5.19% 4: ~3.30% 5: ~3.77% 6: ~3.30% 7: ~2.83% 8: ~5.66% 9: ~3.30% 10: ~2.83% 11: ~2.36% 12: ~4.72% 13: ~5.19% 14: ~3.30% 15: ~3.30% 16: ~5.66% 17: ~1.42% 18: ~4.25% 19: ~3.30% 20: ~2.36% 21: ~4.72% 22: ~5.19% 23: ~3.30% 24: ~2.36% 25: ~4.25% 26: ~3.30%

Samples:

sentence	label
`Name : Defendra Systems Category: Advanced IT Solutions, Network Security Management Department: Information Security Location: Berlin, Germany Amount: 1298.75 Card: Comprehensive Network Security Enhancement Trip Name: unknown`	`0`
`Name : CypherDefense Systems Ltd. Category: IT Security Solutions, Cloud Security Technologies Department: Information Security Location: Amsterdam, Netherlands Amount: 1349.92 Card: Modernization & Protection Strategy Trip Name: unknown`	`0`
`Name : NexusGuard Solutions Category: Data Protection Tools, IT Support Services Department: Information Security Location: New York, USA Amount: 1957.85 Card: Enterprise Security Revamp Trip Name: unknown`	`0`

Loss: BatchSemiHardTripletLoss

Evaluation Dataset

Unnamed Dataset

Size: 52 evaluation samples
Columns: sentence and label

Approximate statistics based on the first 52 samples:

	sentence	label
type	string	int
details	min: 32 tokens mean: 38.83 tokens max: 44 tokens	0: ~1.92% 1: ~7.69% 2: ~5.77% 3: ~5.77% 4: ~5.77% 5: ~5.77% 6: ~7.69% 7: ~1.92% 9: ~3.85% 10: ~3.85% 12: ~7.69% 13: ~1.92% 14: ~3.85% 15: ~3.85% 16: ~1.92% 17: ~3.85% 18: ~3.85% 19: ~5.77% 20: ~7.69% 22: ~1.92% 23: ~1.92% 24: ~1.92% 25: ~1.92% 26: ~1.92%

Samples:

sentence	label
`Name : Vista Cascades Resort Category: Hospitality, Event Hosting Department: Sales Location: Orlando, FL Amount: 1823.45 Card: Annual Sales Retreat Trip Name: Q3 Strategy Session`	`1`
`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`	`2`
`Name : Luxe Stay and Events Category: Hospitality Services, Event Planning Department: Marketing Location: London, UK Amount: 1138.75 Card: Annual Retreat Planning Trip Name: Team Building Retreat`	`1`

Loss: 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

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: steps
prediction_loss_only: True
per_device_train_batch_size: 16
per_device_eval_batch_size: 16
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: 2e-05
weight_decay: 0.0
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 1.0
num_train_epochs: 5
max_steps: -1
lr_scheduler_type: linear
lr_scheduler_kwargs: {}
warmup_ratio: 0.1
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: None
hub_always_push: False
gradient_checkpointing: False
gradient_checkpointing_kwargs: None
include_inputs_for_metrics: False
include_for_metrics: []
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
use_liger_kernel: False
eval_use_gather_object: False
average_tokens_across_devices: False
prompts: None
batch_sampler: no_duplicates
multi_dataset_batch_sampler: proportional

Training Logs

Epoch	Step	bge-base-en-train_cosine_accuracy
-1	-1	0.8821

Framework Versions

Python: 3.11.8
Sentence Transformers: 3.4.1
Transformers: 4.48.2
PyTorch: 2.6.0
Accelerate: 1.3.0
Datasets: 3.2.0
Tokenizers: 0.21.0

Citation

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

BatchSemiHardTripletLoss

@misc{hermans2017defense,
    title={In Defense of the Triplet Loss for Person Re-Identification},
    author={Alexander Hermans and Lucas Beyer and Bastian Leibe},
    year={2017},
    eprint={1703.07737},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}