metadata
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:20
- loss:MatryoshkaLoss
- loss:MultipleNegativesRankingLoss
base_model: Snowflake/snowflake-arctic-embed-l
widget:
- source_sentence: >-
What initiatives were implemented in the past year to improve
communication between departments?
sentences:
- >-
with other departments. In the past year, we conducted monthly
departmental meetings and
established communication channels to facilitate information sharing and
problem-solving.
Fare Collection and Fee Structure
- >-
Our fare collection system ensures fair and consistent fee collection
from passengers. The current fee
structure is as follows:
Regular fare: $2.50
Senior citizens and students: $1.50
Children under 5 years old: Free
Fee collection is primarily done through electronic payment methods,
such as smart cards and
mobile payment apps. Drivers are responsible for ensuring correct fare
collection and providing
receipts upon request.
Route Information and Rules
Our transportation department operates multiple routes within the city.
Route information, including
maps, schedules, and stops, is available on our website and at
designated information centers.
- >-
Our drivers are responsible for operating vehicles safely, following
traffic rules and regulations. They
are required to hold a valid driver's license and maintain a clean
driving record. In the past year, our
drivers completed over 2,000 hours of driving training to enhance their
skills and knowledge.
Route Planning and Optimization
Efficient route planning is essential for timely transportation
services. Our department utilizes
advanced routing software to optimize routes and minimize travel time.
In the past year, we reduced
our average route duration by 15% through effective route planning and
optimization strategies.
Customer Service
- source_sentence: >-
What is the primary focus of the Transportation Department as outlined in
the manual?
sentences:
- >-
for familiarizing themselves with the latest version of the manual.
Conclusion
Thank you for reviewing the Transportation Department Policy Manual.
Your commitment to safety,
customer service, and compliance plays a crucial role in our
department's success. If you have any
questions or need further information, please reach out to your
supervisor or the department
manager. Your dedication and professionalism are appreciated.
- >-
department. It provides guidelines to ensure safe, efficient, and
customer-focused transportation
services. Please read this manual carefully and consult with your
supervisor or the department
manager if you have any questions or need further clarification.
Department Overview
The Transportation Department plays a critical role in providing
reliable transportation services to
our customers. Our department consists of 50 drivers, 10 dispatchers,
and 5 maintenance
technicians. In the past year, we transported over 500,000 passengers
across various routes, ensuring
their safety and satisfaction.
Safety and Vehicle Maintenance
Safety is our top priority. All vehicles undergo regular inspections and
maintenance to ensure they
- >-
department. It provides guidelines to ensure safe, efficient, and
customer-focused transportation
services. Please read this manual carefully and consult with your
supervisor or the department
manager if you have any questions or need further clarification.
Department Overview
The Transportation Department plays a critical role in providing
reliable transportation services to
our customers. Our department consists of 50 drivers, 10 dispatchers,
and 5 maintenance
technicians. In the past year, we transported over 500,000 passengers
across various routes, ensuring
their safety and satisfaction.
Safety and Vehicle Maintenance
Safety is our top priority. All vehicles undergo regular inspections and
maintenance to ensure they
- source_sentence: >-
How often were departmental meetings conducted to address information
sharing and problem-solving?
sentences:
- >-
with other departments. In the past year, we conducted monthly
departmental meetings and
established communication channels to facilitate information sharing and
problem-solving.
Fare Collection and Fee Structure
- >-
Compliance with local, state, and federal regulations is crucial. Our
drivers are required to maintain
up-to-date knowledge of transportation laws and regulations. In the past
year, we conducted 20
compliance audits to ensure adherence to regulatory requirements.
Training and Development
Continuous training and development are vital for our department's
success. In the past year, our
drivers completed over 100 hours of professional development training,
focusing on defensive
driving, customer service, and emergency preparedness.
Communication and Collaboration
Effective communication and collaboration are essential within the
Transportation Department and
- >-
are in optimal condition. In the past year, we conducted 500 vehicle
inspections, identifying and
addressing any maintenance issues promptly. Our drivers are required to
conduct pre-trip and post-
trip inspections to ensure the safety of the vehicles and passengers.
Driver Responsibilities
- source_sentence: >-
How can passengers access route information and schedules for the
transportation department?
sentences:
- >-
Our fare collection system ensures fair and consistent fee collection
from passengers. The current fee
structure is as follows:
Regular fare: $2.50
Senior citizens and students: $1.50
Children under 5 years old: Free
Fee collection is primarily done through electronic payment methods,
such as smart cards and
mobile payment apps. Drivers are responsible for ensuring correct fare
collection and providing
receipts upon request.
Route Information and Rules
Our transportation department operates multiple routes within the city.
Route information, including
maps, schedules, and stops, is available on our website and at
designated information centers.
- >-
Passengers are expected to follow the rules and regulations while
utilizing our transportation
services, including:
Boarding and exiting the vehicle in an orderly manner.
Yielding seats to elderly, disabled, and pregnant passengers.
Keeping noise levels to a minimum.
Refraining from eating, drinking, or smoking onboard.
Using designated safety equipment, such as seat belts, if available.
Reporting any suspicious activity or unattended items to the driver.
Amendments to the Policy Manual
This policy manual is subject to periodic review and amendments. Any
updates or changes will be
communicated to employees through email or departmental meetings.
Employees are responsible
- >-
Passengers are expected to follow the rules and regulations while
utilizing our transportation
services, including:
Boarding and exiting the vehicle in an orderly manner.
Yielding seats to elderly, disabled, and pregnant passengers.
Keeping noise levels to a minimum.
Refraining from eating, drinking, or smoking onboard.
Using designated safety equipment, such as seat belts, if available.
Reporting any suspicious activity or unattended items to the driver.
Amendments to the Policy Manual
This policy manual is subject to periodic review and amendments. Any
updates or changes will be
communicated to employees through email or departmental meetings.
Employees are responsible
- source_sentence: >-
Who should you contact if you have questions or need further information
regarding the Transportation Department Policy Manual?
sentences:
- >-
Transportation Department Policy Manual
Table of Contents:
•
Introduction
•
Department Overview
•
Safety and Vehicle Maintenance
•
Driver Responsibilities
•
Route Planning and Optimization
•
Customer Service
•
Incident Reporting and Investigation
•
Compliance with Regulations
•
Training and Development
•
Communication and Collaboration
•
Fare Collection and Fee Structure
•
Route Information and Rules
•
Amendments to the Policy Manual
•
Conclusion
Introduction
Welcome to the Transportation Department Policy Manual! This manual
serves as a comprehensive
guide to the policies, procedures, and expectations for employees
working in the transportation
- >-
Compliance with local, state, and federal regulations is crucial. Our
drivers are required to maintain
up-to-date knowledge of transportation laws and regulations. In the past
year, we conducted 20
compliance audits to ensure adherence to regulatory requirements.
Training and Development
Continuous training and development are vital for our department's
success. In the past year, our
drivers completed over 100 hours of professional development training,
focusing on defensive
driving, customer service, and emergency preparedness.
Communication and Collaboration
Effective communication and collaboration are essential within the
Transportation Department and
- >-
for familiarizing themselves with the latest version of the manual.
Conclusion
Thank you for reviewing the Transportation Department Policy Manual.
Your commitment to safety,
customer service, and compliance plays a crucial role in our
department's success. If you have any
questions or need further information, please reach out to your
supervisor or the department
manager. Your dedication and professionalism are appreciated.
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
- cosine_accuracy@1
- cosine_accuracy@3
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@3
- cosine_precision@5
- cosine_precision@10
- cosine_recall@1
- cosine_recall@3
- cosine_recall@5
- cosine_recall@10
- cosine_ndcg@10
- cosine_mrr@10
- cosine_map@100
model-index:
- name: SentenceTransformer based on Snowflake/snowflake-arctic-embed-l
results:
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: Unknown
type: unknown
metrics:
- type: cosine_accuracy@1
value: 0.9375
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.9791666666666666
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 1
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 1
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.9375
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.32638888888888884
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.19999999999999998
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.09999999999999999
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.9375
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.9791666666666666
name: Cosine Recall@3
- type: cosine_recall@5
value: 1
name: Cosine Recall@5
- type: cosine_recall@10
value: 1
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.971848173216197
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.9625
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.9625
name: Cosine Map@100
SentenceTransformer based on Snowflake/snowflake-arctic-embed-l
This is a sentence-transformers model finetuned from Snowflake/snowflake-arctic-embed-l. 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.
Model Details
Model Description
- Model Type: Sentence Transformer
- Base model: Snowflake/snowflake-arctic-embed-l
- Maximum Sequence Length: 512 tokens
- Output Dimensionality: 1024 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': False}) with Transformer model: BertModel
(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})
(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("deepali1021/finetuned_arctic_ft")
# Run inference
sentences = [
'Who should you contact if you have questions or need further information regarding the Transportation Department Policy Manual?',
"for familiarizing themselves with the latest version of the manual. \n \nConclusion \nThank you for reviewing the Transportation Department Policy Manual. Your commitment to safety, \ncustomer service, and compliance plays a crucial role in our department's success. If you have any \nquestions or need further information, please reach out to your supervisor or the department \nmanager. Your dedication and professionalism are appreciated.",
'Transportation Department Policy Manual \n \nTable of Contents: \n \n• \nIntroduction \n• \nDepartment Overview \n• \nSafety and Vehicle Maintenance \n• \nDriver Responsibilities \n• \nRoute Planning and Optimization \n• \nCustomer Service \n• \nIncident Reporting and Investigation \n• \nCompliance with Regulations \n• \nTraining and Development \n• \nCommunication and Collaboration \n• \nFare Collection and Fee Structure \n• \nRoute Information and Rules \n• \nAmendments to the Policy Manual \n• \nConclusion \nIntroduction \nWelcome to the Transportation Department Policy Manual! This manual serves as a comprehensive \nguide to the policies, procedures, and expectations for employees working in the transportation',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
Evaluation
Metrics
Information Retrieval
- Evaluated with
InformationRetrievalEvaluator
Metric | Value |
---|---|
cosine_accuracy@1 | 0.9375 |
cosine_accuracy@3 | 0.9792 |
cosine_accuracy@5 | 1.0 |
cosine_accuracy@10 | 1.0 |
cosine_precision@1 | 0.9375 |
cosine_precision@3 | 0.3264 |
cosine_precision@5 | 0.2 |
cosine_precision@10 | 0.1 |
cosine_recall@1 | 0.9375 |
cosine_recall@3 | 0.9792 |
cosine_recall@5 | 1.0 |
cosine_recall@10 | 1.0 |
cosine_ndcg@10 | 0.9718 |
cosine_mrr@10 | 0.9625 |
cosine_map@100 | 0.9625 |
Training Details
Training Dataset
Unnamed Dataset
- Size: 20 training samples
- Columns:
sentence_0
andsentence_1
- Approximate statistics based on the first 20 samples:
sentence_0 sentence_1 type string string details - min: 12 tokens
- mean: 16.3 tokens
- max: 21 tokens
- min: 34 tokens
- mean: 95.1 tokens
- max: 122 tokens
- Samples:
sentence_0 sentence_1 What topics are covered in the Transportation Department Policy Manual?
Transportation Department Policy Manual
Table of Contents:
•
Introduction
•
Department Overview
•
Safety and Vehicle Maintenance
•
Driver Responsibilities
•
Route Planning and Optimization
•
Customer Service
•
Incident Reporting and Investigation
•
Compliance with Regulations
•
Training and Development
•
Communication and Collaboration
•
Fare Collection and Fee Structure
•
Route Information and Rules
•
Amendments to the Policy Manual
•
Conclusion
Introduction
Welcome to the Transportation Department Policy Manual! This manual serves as a comprehensive
guide to the policies, procedures, and expectations for employees working in the transportationWhat is the purpose of the Transportation Department Policy Manual?
Transportation Department Policy Manual
Table of Contents:
•
Introduction
•
Department Overview
•
Safety and Vehicle Maintenance
•
Driver Responsibilities
•
Route Planning and Optimization
•
Customer Service
•
Incident Reporting and Investigation
•
Compliance with Regulations
•
Training and Development
•
Communication and Collaboration
•
Fare Collection and Fee Structure
•
Route Information and Rules
•
Amendments to the Policy Manual
•
Conclusion
Introduction
Welcome to the Transportation Department Policy Manual! This manual serves as a comprehensive
guide to the policies, procedures, and expectations for employees working in the transportationWhat is the primary focus of the Transportation Department as outlined in the manual?
department. It provides guidelines to ensure safe, efficient, and customer-focused transportation
services. Please read this manual carefully and consult with your supervisor or the department
manager if you have any questions or need further clarification.
Department Overview
The Transportation Department plays a critical role in providing reliable transportation services to
our customers. Our department consists of 50 drivers, 10 dispatchers, and 5 maintenance
technicians. In the past year, we transported over 500,000 passengers across various routes, ensuring
their safety and satisfaction.
Safety and Vehicle Maintenance
Safety is our top priority. All vehicles undergo regular inspections and maintenance to ensure they - Loss:
MatryoshkaLoss
with these parameters:{ "loss": "MultipleNegativesRankingLoss", "matryoshka_dims": [ 768, 512, 256, 128, 64 ], "matryoshka_weights": [ 1, 1, 1, 1, 1 ], "n_dims_per_step": -1 }
Training Hyperparameters
Non-Default Hyperparameters
eval_strategy
: stepsper_device_train_batch_size
: 10per_device_eval_batch_size
: 10num_train_epochs
: 10multi_dataset_batch_sampler
: round_robin
All Hyperparameters
Click to expand
overwrite_output_dir
: Falsedo_predict
: Falseeval_strategy
: stepsprediction_loss_only
: Trueper_device_train_batch_size
: 10per_device_eval_batch_size
: 10per_gpu_train_batch_size
: Noneper_gpu_eval_batch_size
: Nonegradient_accumulation_steps
: 1eval_accumulation_steps
: Nonetorch_empty_cache_steps
: Nonelearning_rate
: 5e-05weight_decay
: 0.0adam_beta1
: 0.9adam_beta2
: 0.999adam_epsilon
: 1e-08max_grad_norm
: 1num_train_epochs
: 10max_steps
: -1lr_scheduler_type
: linearlr_scheduler_kwargs
: {}warmup_ratio
: 0.0warmup_steps
: 0log_level
: passivelog_level_replica
: warninglog_on_each_node
: Truelogging_nan_inf_filter
: Truesave_safetensors
: Truesave_on_each_node
: Falsesave_only_model
: Falserestore_callback_states_from_checkpoint
: Falseno_cuda
: Falseuse_cpu
: Falseuse_mps_device
: Falseseed
: 42data_seed
: Nonejit_mode_eval
: Falseuse_ipex
: Falsebf16
: Falsefp16
: Falsefp16_opt_level
: O1half_precision_backend
: autobf16_full_eval
: Falsefp16_full_eval
: Falsetf32
: Nonelocal_rank
: 0ddp_backend
: Nonetpu_num_cores
: Nonetpu_metrics_debug
: Falsedebug
: []dataloader_drop_last
: Falsedataloader_num_workers
: 0dataloader_prefetch_factor
: Nonepast_index
: -1disable_tqdm
: Falseremove_unused_columns
: Truelabel_names
: Noneload_best_model_at_end
: Falseignore_data_skip
: Falsefsdp
: []fsdp_min_num_params
: 0fsdp_config
: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}fsdp_transformer_layer_cls_to_wrap
: Noneaccelerator_config
: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}deepspeed
: Nonelabel_smoothing_factor
: 0.0optim
: adamw_torchoptim_args
: Noneadafactor
: Falsegroup_by_length
: Falselength_column_name
: lengthddp_find_unused_parameters
: Noneddp_bucket_cap_mb
: Noneddp_broadcast_buffers
: Falsedataloader_pin_memory
: Truedataloader_persistent_workers
: Falseskip_memory_metrics
: Trueuse_legacy_prediction_loop
: Falsepush_to_hub
: Falseresume_from_checkpoint
: Nonehub_model_id
: Nonehub_strategy
: every_savehub_private_repo
: Nonehub_always_push
: Falsegradient_checkpointing
: Falsegradient_checkpointing_kwargs
: Noneinclude_inputs_for_metrics
: Falseinclude_for_metrics
: []eval_do_concat_batches
: Truefp16_backend
: autopush_to_hub_model_id
: Nonepush_to_hub_organization
: Nonemp_parameters
:auto_find_batch_size
: Falsefull_determinism
: Falsetorchdynamo
: Noneray_scope
: lastddp_timeout
: 1800torch_compile
: Falsetorch_compile_backend
: Nonetorch_compile_mode
: Nonedispatch_batches
: Nonesplit_batches
: Noneinclude_tokens_per_second
: Falseinclude_num_input_tokens_seen
: Falseneftune_noise_alpha
: Noneoptim_target_modules
: Nonebatch_eval_metrics
: Falseeval_on_start
: Falseuse_liger_kernel
: Falseeval_use_gather_object
: Falseaverage_tokens_across_devices
: Falseprompts
: Nonebatch_sampler
: batch_samplermulti_dataset_batch_sampler
: round_robin
Training Logs
Epoch | Step | cosine_ndcg@10 |
---|---|---|
1.0 | 2 | 0.8107 |
2.0 | 4 | 0.9292 |
3.0 | 6 | 0.9623 |
4.0 | 8 | 0.9712 |
5.0 | 10 | 0.9642 |
6.0 | 12 | 0.9642 |
7.0 | 14 | 0.9642 |
8.0 | 16 | 0.9642 |
9.0 | 18 | 0.9718 |
10.0 | 20 | 0.9718 |
Framework Versions
- Python: 3.11.11
- Sentence Transformers: 3.4.1
- Transformers: 4.48.3
- PyTorch: 2.5.1+cu124
- Accelerate: 1.3.0
- Datasets: 3.3.2
- 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",
}
MatryoshkaLoss
@misc{kusupati2024matryoshka,
title={Matryoshka Representation Learning},
author={Aditya Kusupati and Gantavya Bhatt and Aniket Rege and Matthew Wallingford and Aditya Sinha and Vivek Ramanujan and William Howard-Snyder and Kaifeng Chen and Sham Kakade and Prateek Jain and Ali Farhadi},
year={2024},
eprint={2205.13147},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
MultipleNegativesRankingLoss
@misc{henderson2017efficient,
title={Efficient Natural Language Response Suggestion for Smart Reply},
author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
year={2017},
eprint={1705.00652},
archivePrefix={arXiv},
primaryClass={cs.CL}
}