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---
language:
- en
license: apache-2.0
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:8031
- loss:MultipleNegativesRankingLoss
base_model: BAAI/bge-base-en-v1.5
widget:
- source_sentence: '11.2 In addition, Whirlpool shall reimburse Supplier for Severance
incurred by Supplier as a result of the termination of employment of Supplier
employees working on Whirlpool''s account, subject to Section 11.3 below, upon
the following events: (a) if whirlpool requires Master Services Agreement Schedule
E (Compensation) 15#$#elimination of a position due to changes in scope or volume
of work; (b) if whirlpool approves of the elimination of a position proposed by
Supplier to create savings; or (c) following the disposition or closure of a Managed
Facility unless a similar Managed Facility is added within the same geographic
proximity of the Managed Facility that was disposed of or closed. ect to Severance:
(b) Pay to Supplier the following (collectively, the "Termination Expenses"),
as and. when determined: (i) Severance (as hereinafter defined) actually incurred
by Supplier as a result of the termination of employment of employees working
on Supplier''s account, subject to. Section 11.3 below, (ii) actual expenses reasonably
incurred by Supplier as a result of such expiration or early termination including,
without limitation, termination fees paid by Supplier pursuant to equipment and
vehicle leases and software licensing agreements, (iii) unamortized transition
costs incurred by Supplier, and (iv) other fees, expenses or reimbursements for
Services to which Supplier is entitled under this Agreement through the date of
expiration or termination, as the case may be.'
sentences:
- Assignment
- MOO_Services provided
- CBRE_Redundancy Detail
- source_sentence: 'Private and Confidential Adam Miller MOo Print Limited Unit 12,
Thames Gateway Park Chequers Lane Essex RM9 6FB 2 December 2021 Our ref:MOO Print
sOc2 Dear Adam SOC 2 Engagement#$#### 1 Introduction#$#### 1.1 This letter, together
with the enclosures (the "Engagement Letter"), sets out the basis on which we
are to provide professional services to Moo Print Limited (the "Engagement").
2 Scope of Professional Services 2.1 Our role is to provide the professional services
detailed in the enclosed schedule(s) (the "Services"). By accepting these terms,
you are agreeing that they scope of the Services set out in the schedule(s) is
appropriate for your needs. We will perform the Services with reasonable skill
and care, but our duties and responsibilities shall be limited to the matters
as set out in the schedule(s). 2.2 (a) (b) reviewing (or otherwise being responsible
for) the services provided by any other professional advisers retained by you;
(c)
The fee for core services of this engagement will be between 42''50o - 55''ooo.
excluding VAT, invoiced on a monthly basis based on time spent each month. If
any additional costs or fees need to be incurred for travel, we will obtain written
approval from Moo Print Limited prior to incurring the expense. The 2.5% support
cost as stated in the terms of business section 2.1 will not apply to this engagement.
MOO Print Limited sOc2 02 December 2021 14'
sentences:
- CBRE_WCP Status Criteria
- MOO_Supply Category
- VAT_Data Protection Details
- source_sentence: '13.3 Default by Client. Each of the following shall constitute
a default by Client (an "Client Default'') under this Agreement: 13.3.1 Client
fails to make a payment when due to CBRE, and such failure continues for a period
of fifteen (15) days after written notice of such failure from CBRE; 13.3.2 Except
as set forth in the preceding clause 13.3.1, Client defaults in the performance
of or breaches any of its covenants, agreements or obligations under this Agreement
in any material respect, and such default or breach continues for fifteen (15)
days after written notice of such default or breach from CBRE, unless such default
cannot reasonably be cured within such 15-day period. in which event Client shall
have an additional thirty (30) days to cure such default, provided Client promptly
commences such cure within such 15-day period and continuously proceeds with such
cure in a diligent manner;
13.1.2 If all or substantially all of the assets of CBRE are attached, seized,
or levied upon. or come into the possession of any receiver, trustee, custodian
or assignee for the benefit of creditors, and the same is not vacated, stayed,
dismissed, set aside or otherwise remedied within thirty (30) days after the occurrence
thereof: 13.1.3 If any petition is filed by or against CBRE under the United States
Bankruptcy. Code or any similar state or federal law (and, in the case of involuntary
proceedings, CBRE fails to cause the same to be vacated. stayed or set aside within
thirty (30) days after filing). 13.2 Remedies upon CBRE Default. Upon the occurrence
and continuance of an uncured CBRF Default, Client may terminate this Agreement
and/or exercise whatever remedies that are available at law or in equity.'
sentences:
- Governing Law
- CBRE_Termination Trigger - CBRE
- MOO_Services provided
- source_sentence: 'If termination is made by Buyer for convenience, an equitable
adjustment for completed Services and expenses and written authorized commitments
shallbe made by aqreement between termination expenses incurred by Seller, including
actual severance expenses incurred from the Agreement Term start date until Termination
and such severance expenses shall be no. greater than one week of each terminated
employee''s annual salary per year of service on Buyer''s account as documented
by Seller and pro-rated for any partial years a, unamortized transition costs
(amortized straight-line over the over the first three (3) years of the term of
the Agreement), and any actual termination fees incurred due to early termination
of vehicle and equipment leases "Termination Expenses) as Seller''s sole compensation.In
the event Buyer approves a reduction in Seller''s personnel dedicated to Buyer''s
account as part of a. savings initiative or any Seller personnel dedicated to
Buyer''s. account are terminated as a result of a reduction of Portfolio or scope
of Services, then Buyer shall review Seller''s business expenses caused by such
terminations. In the event a savings initiative (including a reduction of Portfolio
or scope of Services by Buyer), which explicitly calls out severance costs as
a part of the business case, is approved by Buyer and results in a termination
of Seller''s personnel dedicated to Buyer''s account then Buyer shall reimburse
any severance costs incurred by. Seller relating thereto; provided that Seller
shall first use best efforts to place the affected personnel in another position.Seller
shall in any event make best efforts in good faith to outplace any terminated
employees to avoid severance costs. If the termination is attributable to the
default or nonperformance of Seller and without limiting Buyer''s other rights
and remedies, Buyer shall not owe Seller any compensation after the effective
date of termination. Seller shall reimburse Buyer for any reasonable costs or
damages incurred; provided that Buyer shal have the duty to mitigate any damages.
A "default" shall mean a party''s failure to: (a) perform its duties and obligations
under the Contract Documents, or (b) observe and comply with the terms thereof. In
the event of a default by Buyer that is not cured within thirty (30) days of receipt
of notice from Seller, then Seller may terminate thisAgreement and Buyer shall
reimburse Seller for any reasonable costs or damages incurred and the Termination
Expenses. In addition, Seller will in good faith make efforts to outplace any
terminated employees to avoid severance costs. In addition, the above language
regarding reimbursement of termination expenses does not apply to any dark site
included in the SOw
### PAYMENT TERMS#$#Buyer will pay all invoices net 45 days from receipt of invoice,
based on an accurate, valid and complete invoice in acceptable format, calculated
from the latest of the (i) Invoice Date (ii) Invoice Received Date, or (ii) Goods
Received Date. Seller may invoice for charges payable under this Agreement fifteen
(15) days prior to the Services being rendered. Such invoices shall be based upon
the budget approved by the parties in advance. On a quarterly basis, Seller shall
conduct a true up of the actual expenses incurred against the budgeted amounts
invoiced to Buyer. If there is a shortfall or overpayment during such quarter,
the difference shall be reflected as a separate line item on the next invoice.
If there are multiple line item shipments on one invoice, then the last shipment
received in Buyer''s system will be the Goods Received Date. If invoice is received
on a weekend or holiday, then Invoice Received Date will be the next business
day following the holiday and/or weekend. All invoices must be submitted within..
180 calendar days of the latest of the 3 dates listed in this section to be considered
valid for payment. Buyer will not be responsible for payment of any amounts that
are not invoiced within one hundred eighty (180) days of the date that the goods
or services are supplied or provided to Buyer, and Seller hereby waives recovery
of such amounts. Any request for payment of taxes or reimbursement of taxes paid
by Seller on behalf of Buyer shall be billed within one year of the date of assignment,
transfer or conveyance to which such taxes apply. Under no circumstances shall
Buyer be responsible for any fines, interest or penalties assessed against Seller
due to Seller''s failure to pay such taxes, including as a result of Seller''s
failure to request reimbursement from Buyer.'
sentences:
- CBRE_Change in Law detail
- VAT_Arbitration Regulation
- CBRE_Redundancy Detail
- source_sentence: '(d) Names. Service Provider will not use the name of Company,
any Affiliate of Company, any Company employee or any employee of any Affiliate
of Company, or any product or service of Company or any of its Affiliates in any
press release, advertising or materials distributed to prospective or existing
customers, annual reports or any other public disclosure, except with Company''s
prior written authorization. Under no circumstances will Service Provider use
the logos or other trademarks of Company or any of its Affiliates in any such
materials or disclosures.
Service Provider Personnel shall, comply with any written instructions issued
by Company with respect to.. the use, storage and handling of the Company Materials.
Service Provider will use best efforts to protect the Company Materials from any
loss of or damage while such Company Materials are under Service Provider''s control,
which control will be deemed to begin upon receipt of the Company Materials by.
Service Provider; provided that Service Provider shall not be liable for any loss
or damage to Company. Materials to the extent such loss or damage is caused by
Service Provider''s compliance with such written. instructions.'
sentences:
- VAT_Confidentiality Remedies available
- Publicity
- CBRE_Termination Trigger - Client
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: BGE base En v1.5 Phase 5
results:
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: dim 768
type: dim_768
metrics:
- type: cosine_accuracy@1
value: 0.006274509803921568
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.023529411764705882
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.03529411764705882
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.07607843137254902
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.006274509803921568
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.007843137254901959
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.007058823529411765
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.0076078431372549014
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.006274509803921568
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.023529411764705882
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.03529411764705882
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.07607843137254902
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.034339182667857376
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.02193370681605975
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.03589435856389882
name: Cosine Map@100
---
# BGE base En v1.5 Phase 5
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5). 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-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) <!-- at revision a5beb1e3e68b9ab74eb54cfd186867f64f240e1a -->
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 768 dimensions
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
- **Language:** en
- **License:** apache-2.0
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
### Full Model Architecture
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': True}) with Transformer model: BertModel
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
(2): Normalize()
)
```
## Usage
### Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
```bash
pip install -U sentence-transformers
```
Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("RishuD7/bge-base-en-v1.5-82-keys-phase-7-exp_v1")
# Run inference
sentences = [
"(d) Names. Service Provider will not use the name of Company, any Affiliate of Company, any Company employee or any employee of any Affiliate of Company, or any product or service of Company or any of its Affiliates in any press release, advertising or materials distributed to prospective or existing customers, annual reports or any other public disclosure, except with Company's prior written authorization. Under no circumstances will Service Provider use the logos or other trademarks of Company or any of its Affiliates in any such materials or disclosures.\nService Provider Personnel shall, comply with any written instructions issued by Company with respect to.. the use, storage and handling of the Company Materials. Service Provider will use best efforts to protect the Company Materials from any loss of or damage while such Company Materials are under Service Provider's control, which control will be deemed to begin upon receipt of the Company Materials by. Service Provider; provided that Service Provider shall not be liable for any loss or damage to Company. Materials to the extent such loss or damage is caused by Service Provider's compliance with such written. instructions.",
'Publicity',
'CBRE_Termination Trigger - Client',
]
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]
```
<!--
### 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: `dim_768`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.0063 |
| cosine_accuracy@3 | 0.0235 |
| cosine_accuracy@5 | 0.0353 |
| cosine_accuracy@10 | 0.0761 |
| cosine_precision@1 | 0.0063 |
| cosine_precision@3 | 0.0078 |
| cosine_precision@5 | 0.0071 |
| cosine_precision@10 | 0.0076 |
| cosine_recall@1 | 0.0063 |
| cosine_recall@3 | 0.0235 |
| cosine_recall@5 | 0.0353 |
| cosine_recall@10 | 0.0761 |
| **cosine_ndcg@10** | **0.0343** |
| cosine_mrr@10 | 0.0219 |
| cosine_map@100 | 0.0359 |
<!--
## 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: 8,031 training samples
* Columns: <code>positive</code> and <code>anchor</code>
* Approximate statistics based on the first 1000 samples:
| | positive | anchor |
|:--------|:--------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|
| type | string | string |
| details | <ul><li>min: 170 tokens</li><li>mean: 377.79 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 8.22 tokens</li><li>max: 11 tokens</li></ul> |
* Samples:
| positive | anchor |
|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------|
| <code>In the event that the Contractor provides the Service during the incomplete period of the the service was provided 3. The Customer shall reimburse the Contractor for the expenses incurred for the purchase of spare parts, equipment and materials for the purpose of providing the Services increased by the Contractor's mark-up, the amount of which is specified in Appendix No 4 "Terms and Conditions". The purchase of spare parts, equipment and materials referred to above will take place after the Contractor's application has been accepted by the Customer. 1 Settlement for the undertaking by the Contractor Emergency interventions will take place in accordance with and the conditions indicated in Clause 4 "Terms and Conditions" 5. For the performance of additional works, the Contractor will receive the remuneration specified in the application or contract for the performance of additional works accepted by the Client.<br> Not later: within 7 (sleth) days from the date of termination of this Agre...</code> | <code>CBRE_Pricing Criteria</code> |
| <code>4.1 The Contractor, despite a written warning issued by the Contractor by registered mail, violates the provisions of the Agreement and #$#cease the infringement within 14 (fourteen) days from the date of receipt of the summons from the Contractor, unless, . due to the nature of the breach. its removal. requires a longer period and the actions to remedy the breach are taken immediately. and duly by the Contractor:. 4.4 The Contractor shall cease to perform the duties resulting from the contract in part or in part for more than 3 days. 5. The Contractor may terminate the Contract with effect from the date of written service - under pain of non-wai:noscj - a statement of termination. if:. 5.1The Customer shall not comply with the obligation to submit the seals after the deadline for the payment of the two consecutive settlement periods specified on the invoice and after the deadline of fourteen days specified by the Contractor in the. written reminder; out business activity<br>### S5 TER...</code> | <code>CBRE_Termination Trigger - Client</code> |
| <code>Works commissioned to the Contractor, which do not fall within the scope of the contract, are additionally valued as Additional Works after prior acceptance of the Contractor's offer within 30 days from the date of delivery of the duly issued invoice issued after the. completion of these works. 7. The amount of remuneration due as set out in Schedule No 4 "Terms and Conditions shall be the net amount and shall beand VAT and VAT.. 8. Any discounts, commissions and other bonuses that the Contractor receivesin connection with its global purchasing program will be retained by the Contractor and I wil not be subiect to settlement with the Principal. 9. In the event of changes in the Iaw resulting in an increase in costs related to the provision of Services on the part of the Contractor, the Customer undertakes to cover the above- mentioned costs, documented by the Contractor.<br>### S15 CONFIDENTIAL INFORMATION AND PROTECTION OF PERSONAL DATA 1.Any information obtained by the Customer or the C...</code> | <code>CBRE_WCP Status Criteria</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"
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: epoch
- `per_device_train_batch_size`: 32
- `per_device_eval_batch_size`: 16
- `gradient_accumulation_steps`: 16
- `learning_rate`: 2e-05
- `num_train_epochs`: 30
- `lr_scheduler_type`: cosine
- `warmup_ratio`: 0.1
- `tf32`: False
- `load_best_model_at_end`: True
- `optim`: adamw_torch_fused
- `batch_sampler`: no_duplicates
#### All Hyperparameters
<details><summary>Click to expand</summary>
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: epoch
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 32
- `per_device_eval_batch_size`: 16
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 16
- `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`: 30
- `max_steps`: -1
- `lr_scheduler_type`: cosine
- `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`: False
- `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`: True
- `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_fused
- `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
- `prompts`: None
- `batch_sampler`: no_duplicates
- `multi_dataset_batch_sampler`: proportional
</details>
### Training Logs
| Epoch | Step | Training Loss | dim_768_cosine_ndcg@10 |
|:----------:|:-------:|:-------------:|:----------------------:|
| 0.6375 | 10 | 2.4919 | - |
| 1.2749 | 20 | 1.576 | - |
| 1.7211 | 27 | - | 0.0285 |
| 1.1713 | 30 | 0.6111 | - |
| 1.8088 | 40 | 1.622 | - |
| 2.4462 | 50 | 0.4089 | - |
| 2.7012 | 54 | - | 0.0300 |
| 2.3426 | 60 | 0.7251 | - |
| 2.9801 | 70 | 0.864 | - |
| 3.6175 | 80 | 0.152 | - |
| 3.6813 | 81 | - | 0.0299 |
| 3.5139 | 90 | 0.7404 | - |
| 4.1514 | 100 | 0.5908 | - |
| 4.7251 | 109 | - | 0.0304 |
| 4.0478 | 110 | 0.1358 | - |
| 4.6853 | 120 | 0.7636 | - |
| 5.3227 | 130 | 0.3625 | - |
| 5.7052 | 136 | - | 0.0332 |
| 5.2191 | 140 | 0.2812 | - |
| 5.8566 | 150 | 0.6369 | - |
| 6.4940 | 160 | 0.1818 | - |
| 6.6853 | 163 | - | 0.0327 |
| 6.3904 | 170 | 0.3748 | - |
| 7.0279 | 180 | 0.5476 | - |
| 7.6653 | 190 | 0.0952 | - |
| 7.7291 | 191 | - | 0.0334 |
| 7.5618 | 200 | 0.5157 | - |
| 8.1992 | 210 | 0.4383 | - |
| **8.7092** | **218** | **-** | **0.0362** |
| 8.0956 | 220 | 0.1392 | - |
| 8.7331 | 230 | 0.5627 | - |
| 9.3705 | 240 | 0.2617 | - |
| 9.6892 | 245 | - | 0.0336 |
| 9.2669 | 250 | 0.2135 | - |
| 9.9044 | 260 | 0.5106 | - |
| 10.5418 | 270 | 0.1462 | - |
| 10.7331 | 273 | - | 0.0343 |
| 10.4382 | 280 | 0.2909 | - |
| 11.0757 | 290 | 0.4675 | - |
| 11.7131 | 300 | 0.075 | 0.0348 |
| 11.6096 | 310 | 0.4271 | - |
| 12.2470 | 320 | 0.3571 | - |
| 12.6932 | 327 | - | 0.0358 |
| 12.1434 | 330 | 0.1183 | - |
| 12.7809 | 340 | 0.4438 | - |
| 13.4183 | 350 | 0.1956 | - |
| 13.7371 | 355 | - | 0.0352 |
| 13.3147 | 360 | 0.1887 | - |
| 13.9522 | 370 | 0.4342 | - |
| 14.5896 | 380 | 0.1177 | - |
| 14.7171 | 382 | - | 0.0346 |
| 14.4861 | 390 | 0.2633 | - |
| 15.1235 | 400 | 0.4205 | - |
| 15.6972 | 409 | - | 0.0340 |
| 15.0199 | 410 | 0.0649 | - |
| 15.6574 | 420 | 0.4102 | - |
| 16.2948 | 430 | 0.3021 | - |
| 16.7410 | 437 | - | 0.0343 |
| 16.1912 | 440 | 0.1288 | - |
| 16.8287 | 450 | 0.4247 | 0.0343 |
* The bold row denotes the saved checkpoint.
### Framework Versions
- Python: 3.11.11
- Sentence Transformers: 3.3.1
- Transformers: 4.43.1
- PyTorch: 2.5.1+cu124
- Accelerate: 1.3.0
- Datasets: 2.19.1
- Tokenizers: 0.19.1
## 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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