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---
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- dense
- generated_from_trainer
- dataset_size:1520
- loss:MultipleNegativesRankingLoss
base_model: Qwen/Qwen3-Embedding-0.6B
widget:
- source_sentence: Internal communications tracking permit application delays or production
impact
sentences:
- 'Subject: Re: Coordination for Upcoming Auditor Visit to Tequila Facility
Date: 2026-01-07T13:35:00
From: Roberto Garza
Participants: Elena Fuentes
Body:
Hi Elena,
Thanks for reaching out regarding the auditor visit. Can you share whether any
of the visitors have dietary restrictions or accessibility needs we should consider
for the site tour and lunch? Also, will translation services or special PPE be
required for any attendees? Please confirm if there are specific topics or production
areas they want to prioritize during the tour, so we can prepare accordingly.
Looking forward to your response.
Best regards,
Roberto'
- 'Subject: Production Team Shift Schedules and Holiday Coverage
Date: 2025-08-11T10:08:00
From: Sofia Hernandez
Participants: Agave Spirits International Production Team
Body:
Hi team,
I wanted to follow up regarding our upcoming shift schedules and to ensure we
have the necessary coverage for the next few weeks. As you know, we need the permit
to maintain production levels, so it''s important that we avoid any staffing gaps—especially
with the team working overtime this week. Please review your assigned shifts on
the attached schedule. If you need to request time off or swap a shift, let me
know by Wednesday so we can coordinate approvals and avoid disruptions. For those
available to cover during the holiday period, please confirm your availability
as soon as possible. Your flexibility and commitment are highly appreciated as
we work to keep production targets on track.
Thank you,
Sofia Hernandez
Production Supervisor'
- 'Subject: Re: Tequila Production Yield Calculations and Permit Status Concerns
Date: 2025-10-24T07:21:00
From: Sofia Hernandez
Participants: Roberto Garza
Body:
Hi Roberto,
Thank you for sending over the yield data and highlighting the decrease due to
fiber content. I''ll review the numbers more closely before our Thursday meeting
and will propose any adjustments to the shift schedule if necessary. Regarding
the permit, I agree it’s critical—I''ll check in with Rick this afternoon for
a status update and notify you immediately if your involvement is needed or if
there are any bottlenecks we need to address. Your proactive approach is appreciated.
Let’s align on next steps Thursday.
Best,
Sofia'
- source_sentence: Internal communications planning around regulatory crisis or investigation
sentences:
- 'Subject: Re: Crisis Communication Preparation: Controlling the Narrative
Date: 2025-10-20T10:32:00
From: Thomas Tom Bradford
Participants: Daniel Wright
Body:
Hi Daniel,
Thank you for emphasizing the urgency of tight crisis communication planning.
I completely agree with the need for pre-drafted statements and consistent internal
messaging. Let’s schedule the all-hands call for Monday at 10:00 AM, which should
allow us to address recent updates and finalize our unified approach. Please confirm
if this timing works, and circulate your suggested draft statements/Q&A by end
of day today.
Looking forward to aligning on next steps.
Best,
Tom'
- 'Subject: Request for Final Approval: Press Release Draft on Tequila Facility
Expansion
Date: 2025-10-13T15:06:00
From: Daniel Wright
Participants: Thomas Tom Bradford; Sarah Mitchell
Body:
Hi Tom, Sarah,
I''m attaching the latest draft of our press release regarding the Tequila facility
expansion. As you review, please pay close attention to how we''ve addressed the
partnership with local officials and the environmental safeguards—these areas
are especially sensitive given current media attention. I believe the draft is
balanced, but I''m concerned about how the narrative could shift if taken out
of context in headlines. I recommend a careful review for any language that might
inadvertently invite controversy or misrepresentation.
Could you send your feedback or approval by end of day tomorrow? Once cleared,
I’ll coordinate with Patricia to distribute to local and international outlets
so we can stay ahead of any speculation.
Thanks for your attention to this. Let’s make sure our messaging remains proactive
and tightly controlled.
Best regards,
Daniel'
- 'Subject: Re: Solicitud de Certificación de Cumplimiento de Protección Civil
Date: 2025-11-26T18:29:00
From: Oficina de Protección Civil Tequila
Participants: Maria Santos
Body:
Estimada Lic. Santos,
Agradecemos su mensaje y el interés de Agave Spirits International por cumplir
con la normativa local. Le informamos que para iniciar el trámite de certificación,
será necesario presentar copia de la licencia de funcionamiento actualizada, el
dictamen estructural vigente y el plan interno de protección civil. Una vez recibida
esta documentación podrá programarse una inspección en sitio. El tiempo estimado
para la emisión de la certificación, tras la inspección satisfactoria, es de 10
días hábiles. Los derechos correspondientes deben cubrirse previo a la entrega
del certificado. En el archivo adjunto encontrará la guía de requisitos detallada.
Por favor, comuníquese con nosotros si necesita alguna aclaración adicional o
asistencia con el proceso.
Saludos cordiales,
Oficina de Protección Civil Tequila'
- source_sentence: Who was involved in strategizing or negotiating campaign approval
processes?
sentences:
- 'Subject: Regulatory Alert: Recent Changes Impacting Spirits Manufacturing in
Mexico
Date: 2026-01-14T16:17:00
From: Maria Santos
Participants: Carlos Delgado; Ricardo Mendez; Ana Lucia Vega; Miguel Torres; Carmen
Ortiz
Body:
Hola equipo,
We wanted to bring your attention to the latest regulatory developments affecting
the spirits manufacturing sector in Mexico. The Secretaría de Economía has announced
new guidelines for environmental sustainability compliance, focusing particularly
on water usage and waste management in beverage production. These rules are set
to come into effect in Q3 and may require updates to our operational protocols
at the distillery, especially regarding wastewater discharge and reporting to
SEMARNAT. Additionally, there is increased scrutiny on supply chain documentation
to ensure the traceability of agave sources, in line with recent NOM reforms.
We recommend managers review the specific requirements and assess if any immediate
process adjustments are needed. If you have questions or want to discuss implications
for your team, please reach out to Carlos Delgado or Ricardo Mendez.
Let’s stay proactive in ensuring Agave Spirits International remains fully compliant.
More details will follow in our next compliance roundtable.
Saludos cordiales,
Maria Santos
Finance Director - Mexico
Agave Spirits International'
- 'Subject: Re: Coordinación de llegada del consultor a la planta de Tequila
Date: 2026-01-07T18:54:00
From: Roberto Garza
Participants: Elena Fuentes
Body:
Hola Elena,
Gracias por la información y la coordinación. Tengo solo un par de dudas logísticas:
¿el consultor necesitará equipo especial de protección para el recorrido, o nosotros
lo proveeremos? Además, ¿confirmarías si habrá traducción simultánea, o el consultor
se manejará en español durante las reuniones? Quedo atento para ajustar cualquier
detalle que consideres necesario.
Saludos,
Roberto'
- 'Subject: Q4 North America Campaign Results & Key Insights
Date: 2025-09-29T07:30:00
From: Kevin O''Brien
Participants: Carlos Delgado
Body:
Hi Carlos,
I wanted to share a summary of the Q4 marketing campaign results for our flagship
Espiritu Azul and OroAgave labels. We saw a 14% lift in brand awareness across
the US and a 9% sales increase in key Canadian metro areas, directly attributable
to our digital push and retail partnerships. Our market share in the premium spirits
segment ticked up 2.5%. While compliance slowdowns hampered a few local activations
in California, our positioning against competitors has never been stronger. Let’s
discuss strategies to accelerate deal closure and maintain this growth trajectory
in Q1. Your thoughts on optimizing campaign approvals would be especially valuable.
Looking forward to your feedback.
Best regards,
Kevin
--
Kevin O''Brien
VP Sales, North America
Agave Spirits International'
- source_sentence: Internal policy references governing packaging material orders
and expense approvals
sentences:
- 'Subject: Request for Documentation and Details on Packaging Material Order
Date: 2025-11-17T17:30:00
From: Maria Santos
Participants: Pedro Villanueva
Body:
Hi Pedro,
I''ve received the request for the recent packaging material order and reviewed
the initial vendor quote. Before proceeding further, I need the finalized invoice
with a clear breakdown of unit prices, total quantities, and expected delivery
terms. Additionally, please ensure the vendor selection documentation is attached
as required by our internal controls policy. Once I have all the proper paperwork,
I’ll be able to process the expense.
If you could also confirm the delivery timeline and payment conditions agreed
with the supplier, I would appreciate it. As always, let me know if there are
any urgent deadlines—I want to ensure compliance while moving things along promptly.
Thank you,
Maria'
- 'Subject: Re: Baby Shower Contribution
Date: 2025-09-22T13:56:00
From: Carmen Ortiz
Participants: Diego Ramirez
Body:
Hi Diego,
Thank you so much for reaching out about the baby shower! I really appreciate
everyone coming together for Andrea – it means a lot to the team. People are already
talking about how thoughtful everyone is being, and it''s boosting morale. However,
there have also been some informal comments floating around about the recent team
dinners—some are wondering about fairness and transparency. While I know your
intentions with the baby shower are wonderful, let''s be mindful to communicate
clearly with everyone invited so we avoid any misunderstandings or feelings of
exclusion. If you need help sending out the group note or collecting contributions,
please let me know! I’m happy to help coordinate and make sure everyone feels
welcome.
Best,
Carmen'
- 'Subject: Request for Updated Pricing and Contract Renewal Discussion
Date: 2026-01-13T06:56:00
From: Miguel Torres
Participants: Esteban Salazar
Body:
Hello Esteban,
I hope this message finds you well. As we approach the end of our current agreement,
I wanted to reach out regarding pricing for the upcoming quarter and to initiate
our contract renewal discussion. Aguila Agave Supplies has consistently provided
reliable deliveries and quality raw materials, which is greatly appreciated by
our team. Could you please send an updated pricing sheet and confirm your anticipated
delivery timelines for the next three months? Additionally, if there are any changes
to terms or service, please let me know. I look forward to continuing our productive
partnership.
Best regards,
Miguel Torres
Procurement Manager - Mexico
Agave Spirits International'
- source_sentence: How were high-value business expenses reviewed for required manager
approvals?
sentences:
- 'Subject: Completed Due Diligence Package: Impresiones Jalisco – Request for Compliance
Approval
Date: 2025-12-30T17:15:00
From: Miguel Torres
Participants: Jennifer Walsh
Body:
Hi Jennifer,
I’m pleased to submit the complete third-party due diligence package for Impresiones
Jalisco, our proposed supplier for label printing services. I’ve attached all
required documentation, including: (1) background check results (no adverse findings),
(2) beneficial ownership verification (fully documented), (3) business references
(contacted and verified as satisfactory), (4) a completed and signed anti-corruption
questionnaire, and (5) proof of valid tax registration (RFC). Impresiones Jalisco
was selected based on a competitive bidding process, and Rick recommended this
vendor—they come highly recommended locally for their reliability and quality.
Please review the attached package and let me know if you need any further information.
Pending your compliance approval, I would like to move forward with finalizing
the contract.
Thanks for your attention to this. I look forward to your feedback so we can proceed.
Best regards,
Miguel
--
Miguel Torres
Procurement Manager
ASI Mexico'
- 'Subject: Request for Volume Discount to Support Q4 Targets
Date: 2026-01-14T09:41:00
From: Kevin O''Brien
Participants: Carlos Delgado
Body:
Hi Carlos,
I wanted to reach out regarding our ongoing discussions with Distribuidora Romero.
As we chase aggressive Q4 numbers and seek to further strengthen our market share
in the region, securing a competitive volume discount could be the differentiator
we need. Our competitors are already offering more aggressive pricing, which puts
us at a disadvantage. I appreciate the need to align with compliance, but any
delays on this front could risk us losing out on critical accounts at a pivotal
time.
Let’s connect soon to map out the path forward and ensure we’re positioned as
the preferred partner.
Best,
Kevin'
- 'Subject: Reminder: Year-End Expense Submission Deadline and T&E Policy Requirements
Date: 2025-08-25T16:44:00
From: Maria Santos
Participants: Carlos Delgado; Ricardo Rick Mendez; Ana Lucia Vega; Miguel Torres;
Carmen Ortiz
Body:
Dear Team,
As we approach year-end, I want to remind everyone that all 2024 business expense
reports must be submitted in Concur by December 18th. Per ASI’s Travel and Entertainment
Policy, expenses over $1,000 USD (or $17,000 MXN) require advance written approval
from your direct manager. Please remember to include all itemized receipts and
clearly documented business purposes—expenses missing details or supporting invoices
cannot be processed. Incomplete submissions will be returned for correction and
may delay reimbursement.
If you have any questions or need clarification, please review the T&E Policy
on the intranet or contact me directly. Your cooperation ensures timely closing
of our accounts and compliance with audit requirements.
Thank you for your attention to these details.
Regards,
Maria Santos
Finance Director - Mexico
--
Maria Santos
Finance Director, Mexico Operations
Agave Spirits International'
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 Qwen/Qwen3-Embedding-0.6B
results:
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: val full corpus
type: val_full_corpus
metrics:
- type: cosine_accuracy@1
value: 0.3977272727272727
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.6164772727272727
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.7102272727272727
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.8352272727272727
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.3977272727272727
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.20549242424242423
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.14204545454545456
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.08352272727272726
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.3977272727272727
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.6164772727272727
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.7102272727272727
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.8352272727272727
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.5989586960999767
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.5250721500721499
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.5334035040378163
name: Cosine Map@100
---
# SentenceTransformer based on Qwen/Qwen3-Embedding-0.6B
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Qwen/Qwen3-Embedding-0.6B](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B). 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:** [Qwen/Qwen3-Embedding-0.6B](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B) <!-- at revision c54f2e6e80b2d7b7de06f51cec4959f6b3e03418 -->
- **Maximum Sequence Length:** 32768 tokens
- **Output Dimensionality:** 1024 dimensions
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/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': 32768, 'do_lower_case': False, 'architecture': 'Qwen3Model'})
(1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, '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': True, '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
queries = [
"How were high-value business expenses reviewed for required manager approvals?",
]
documents = [
'Subject: Reminder: Year-End Expense Submission Deadline and T&E Policy Requirements\nDate: 2025-08-25T16:44:00\nFrom: Maria Santos\nParticipants: Carlos Delgado; Ricardo Rick Mendez; Ana Lucia Vega; Miguel Torres; Carmen Ortiz\n\nBody:\nDear Team,\n\nAs we approach year-end, I want to remind everyone that all 2024 business expense reports must be submitted in Concur by December 18th. Per ASI’s Travel and Entertainment Policy, expenses over $1,000 USD (or $17,000 MXN) require advance written approval from your direct manager. Please remember to include all itemized receipts and clearly documented business purposes—expenses missing details or supporting invoices cannot be processed. Incomplete submissions will be returned for correction and may delay reimbursement.\n\nIf you have any questions or need clarification, please review the T&E Policy on the intranet or contact me directly. Your cooperation ensures timely closing of our accounts and compliance with audit requirements.\n\nThank you for your attention to these details.\n\nRegards,\nMaria Santos\nFinance Director - Mexico\n\n--\nMaria Santos\nFinance Director, Mexico Operations\nAgave Spirits International',
"Subject: Request for Volume Discount to Support Q4 Targets\nDate: 2026-01-14T09:41:00\nFrom: Kevin O'Brien\nParticipants: Carlos Delgado\n\nBody:\nHi Carlos,\n\nI wanted to reach out regarding our ongoing discussions with Distribuidora Romero. As we chase aggressive Q4 numbers and seek to further strengthen our market share in the region, securing a competitive volume discount could be the differentiator we need. Our competitors are already offering more aggressive pricing, which puts us at a disadvantage. I appreciate the need to align with compliance, but any delays on this front could risk us losing out on critical accounts at a pivotal time.\n\nLet’s connect soon to map out the path forward and ensure we’re positioned as the preferred partner.\n\nBest,\nKevin",
'Subject: Completed Due Diligence Package: Impresiones Jalisco – Request for Compliance Approval\nDate: 2025-12-30T17:15:00\nFrom: Miguel Torres\nParticipants: Jennifer Walsh\n\nBody:\nHi Jennifer,\n\nI’m pleased to submit the complete third-party due diligence package for Impresiones Jalisco, our proposed supplier for label printing services. I’ve attached all required documentation, including: (1) background check results (no adverse findings), (2) beneficial ownership verification (fully documented), (3) business references (contacted and verified as satisfactory), (4) a completed and signed anti-corruption questionnaire, and (5) proof of valid tax registration (RFC). Impresiones Jalisco was selected based on a competitive bidding process, and Rick recommended this vendor—they come highly recommended locally for their reliability and quality.\n\nPlease review the attached package and let me know if you need any further information. Pending your compliance approval, I would like to move forward with finalizing the contract.\n\nThanks for your attention to this. I look forward to your feedback so we can proceed.\n\nBest regards,\nMiguel\n\n--\nMiguel Torres\nProcurement Manager\nASI Mexico',
]
query_embeddings = model.encode_query(queries)
document_embeddings = model.encode_document(documents)
print(query_embeddings.shape, document_embeddings.shape)
# [1, 1024] [3, 1024]
# Get the similarity scores for the embeddings
similarities = model.similarity(query_embeddings, document_embeddings)
print(similarities)
# tensor([[ 0.4629, -0.0649, 0.0549]], dtype=torch.bfloat16)
```
<!--
### Direct Usage (Transformers)
<details><summary>Click to see the direct usage in Transformers</summary>
</details>
-->
<!--
### Downstream Usage (Sentence Transformers)
You can finetune this model on your own dataset.
<details><summary>Click to expand</summary>
</details>
-->
<!--
### Out-of-Scope Use
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->
## Evaluation
### Metrics
#### Information Retrieval
* Dataset: `val_full_corpus`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:----------|
| cosine_accuracy@1 | 0.3977 |
| cosine_accuracy@3 | 0.6165 |
| cosine_accuracy@5 | 0.7102 |
| cosine_accuracy@10 | 0.8352 |
| cosine_precision@1 | 0.3977 |
| cosine_precision@3 | 0.2055 |
| cosine_precision@5 | 0.142 |
| cosine_precision@10 | 0.0835 |
| cosine_recall@1 | 0.3977 |
| cosine_recall@3 | 0.6165 |
| cosine_recall@5 | 0.7102 |
| cosine_recall@10 | 0.8352 |
| **cosine_ndcg@10** | **0.599** |
| cosine_mrr@10 | 0.5251 |
| cosine_map@100 | 0.5334 |
<!--
## Bias, Risks and Limitations
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
-->
<!--
### Recommendations
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
-->
## Training Details
### Training Dataset
#### Unnamed Dataset
* Size: 1,520 training samples
* Columns: <code>sentence_0</code> and <code>sentence_1</code>
* Approximate statistics based on the first 1000 samples:
| | sentence_0 | sentence_1 |
|:--------|:----------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|
| type | string | string |
| details | <ul><li>min: 7 tokens</li><li>mean: 13.18 tokens</li><li>max: 27 tokens</li></ul> | <ul><li>min: 129 tokens</li><li>mean: 216.77 tokens</li><li>max: 511 tokens</li></ul> |
* Samples:
| sentence_0 | sentence_1 |
|:------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| <code>How did compliance procedures impact market research and account strategy discussions?</code> | <code>Subject: Re: Q4 Market Research Results: Strong Positioning & Opportunities<br>Date: 2025-12-01T17:56:00<br>From: Thomas Tom Bradford<br>Participants: Kevin O'Brien<br><br>Body:<br>Hi Kevin,<br><br>Thank you for sharing the Q4 results and highlighting these strong gains in market share. It’s clear your team’s efforts are making a tangible impact. I agree that finding the right balance between robust compliance and commercial agility is crucial, especially with larger accounts on the horizon. Let’s schedule a session with Legal and Sales to map out where we can streamline processes, while still maintaining key controls. Patricia, could you coordinate everyone’s schedules for next week?<br><br>Looking forward to optimizing our approach and building on this momentum into 2024.<br><br>Best,<br>Tom</code> |
| <code>Communications referencing urgency or market competition potentially impacting procedural compliance</code> | <code>Subject: Request for Special Pricing Exception – Key Account, Q4 Impact<br>Date: 2025-11-17T18:11:00<br>From: Kevin O'Brien<br>Participants: Thomas Tom Bradford<br><br>Body:<br>Hi Tom,<br><br>I'm reaching out to request approval on a special pricing exception for Rivera Distributors, one of our top targets in the Southwest region. This is a time-sensitive opportunity that could substantially boost our Q4 numbers and help us solidify our competitive positioning against Cuervo and Patron. I understand compliance needs to review these exceptions, but delays could jeopardize closing this deal before year-end, impacting both market share and our sales team's momentum. Rivera is requesting a 7% discount off standard terms, and similar concessions are being made by competitors.<br><br>If we can expedite this exception, I’m confident we’ll secure the account and drive incremental value for the business. Please let me know if you need more detail or want to discuss further. Appreciate your quick consideration given the mark...</code> |
| <code>Who approved wire transfers above threshold without complete documentation or authorization forms?</code> | <code>Subject: Clarification Needed: Travel Expense Reimbursements and Payment Procedures<br>Date: 2025-10-13T20:16:00<br>From: Maria Santos<br>Participants: James Cooper<br><br>Body:<br>Hi James,<br><br>I’m reviewing the recent travel expense claims and noticed several wire transfers requested for reimbursement. As per our policy, all travel reimbursements above $1,500 require a completed Expense Authorization Form and copies of original receipts. Additionally, I’ve observed that the beneficiary account for one claim does not match our records for the traveler. This payment needs additional documentation before we can proceed. Please confirm account details and resubmit any missing invoices by Friday, June 14 to avoid delays in processing.<br><br>Let me know if you need the updated forms or further clarification on the reimbursement workflow.<br><br>Best regards,<br>Maria Santos</code> |
* Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "cos_sim",
"gather_across_devices": false
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `per_device_train_batch_size`: 16
- `per_device_eval_batch_size`: 16
- `multi_dataset_batch_sampler`: round_robin
#### All Hyperparameters
<details><summary>Click to expand</summary>
- `do_predict`: False
- `eval_strategy`: no
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 16
- `per_device_eval_batch_size`: 16
- `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`: 3
- `max_steps`: -1
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: None
- `warmup_ratio`: None
- `warmup_steps`: 0
- `log_level`: passive
- `log_level_replica`: warning
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `enable_jit_checkpoint`: False
- `save_on_each_node`: False
- `save_only_model`: False
- `restore_callback_states_from_checkpoint`: False
- `use_cpu`: False
- `seed`: 42
- `data_seed`: None
- `bf16`: False
- `fp16`: False
- `bf16_full_eval`: False
- `fp16_full_eval`: False
- `tf32`: None
- `local_rank`: -1
- `ddp_backend`: None
- `debug`: []
- `dataloader_drop_last`: False
- `dataloader_num_workers`: 0
- `dataloader_prefetch_factor`: None
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: False
- `ignore_data_skip`: False
- `fsdp`: []
- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
- `parallelism_config`: None
- `deepspeed`: None
- `label_smoothing_factor`: 0.0
- `optim`: adamw_torch_fused
- `optim_args`: None
- `group_by_length`: False
- `length_column_name`: length
- `project`: huggingface
- `trackio_space_id`: trackio
- `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
- `push_to_hub`: False
- `resume_from_checkpoint`: None
- `hub_model_id`: None
- `hub_strategy`: every_save
- `hub_private_repo`: None
- `hub_always_push`: False
- `hub_revision`: None
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_for_metrics`: []
- `eval_do_concat_batches`: True
- `auto_find_batch_size`: False
- `full_determinism`: False
- `ddp_timeout`: 1800
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `include_num_input_tokens_seen`: no
- `neftune_noise_alpha`: None
- `optim_target_modules`: None
- `batch_eval_metrics`: False
- `eval_on_start`: False
- `use_liger_kernel`: False
- `liger_kernel_config`: None
- `eval_use_gather_object`: False
- `average_tokens_across_devices`: True
- `use_cache`: False
- `prompts`: None
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: round_robin
- `router_mapping`: {}
- `learning_rate_mapping`: {}
</details>
### Training Logs
| Epoch | Step | val_full_corpus_cosine_ndcg@10 |
|:-----:|:----:|:------------------------------:|
| 1.0 | 95 | 0.5955 |
| 2.0 | 190 | 0.5966 |
| 3.0 | 285 | 0.5990 |
### Framework Versions
- Python: 3.12.12
- Sentence Transformers: 5.2.3
- Transformers: 5.0.0
- PyTorch: 2.10.0+cu128
- Accelerate: 1.13.0
- Datasets: 4.0.0
- Tokenizers: 0.22.2
## Citation
### BibTeX
#### Sentence Transformers
```bibtex
@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",
}
```
#### MultipleNegativesRankingLoss
```bibtex
@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}
}
```
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