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tags:
- sentence-transformers
- cross-encoder
- reranker
- generated_from_trainer
- dataset_size:120000
- loss:BinaryCrossEntropyLoss
base_model: cross-encoder/ms-marco-MiniLM-L6-v2
pipeline_tag: text-ranking
library_name: sentence-transformers
---
# CrossEncoder based on cross-encoder/ms-marco-MiniLM-L6-v2
This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [cross-encoder/ms-marco-MiniLM-L6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2) using the [sentence-transformers](https://www.SBERT.net) library. It computes scores for pairs of texts, which can be used for text reranking and semantic search.
## Model Details
### Model Description
- **Model Type:** Cross Encoder
- **Base model:** [cross-encoder/ms-marco-MiniLM-L6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2) <!-- at revision c5ee24cb16019beea0893ab7796b1df96625c6b8 -->
- **Maximum Sequence Length:** 256 tokens
- **Number of Output Labels:** 1 label
- **Supported Modality:** Text
<!-- - **Training Dataset:** Unknown -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Documentation:** [Cross Encoder Documentation](https://www.sbert.net/docs/cross_encoder/usage/usage.html)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/sentence-transformers)
- **Hugging Face:** [Cross Encoders on Hugging Face](https://huggingface.co/models?library=sentence-transformers&other=cross-encoder)
### Full Model Architecture
```
CrossEncoder(
(0): Transformer({'transformer_task': 'sequence-classification', 'modality_config': {'text': {'method': 'forward', 'method_output_name': 'logits'}}, 'module_output_name': 'scores', 'architecture': 'BertForSequenceClassification'})
)
```
## 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 CrossEncoder
# Download from the 🤗 Hub
model = CrossEncoder("cross_encoder_model_id")
# Get scores for pairs of inputs
pairs = [
['Job Title: Customer Support Specialist. Required Seniority: Junior. Industry: FinTech. Must-Have Skills: Ticketing, Documentation, Root Cause Analysis, Communication. Nice-to-Have Skills: Troubleshooting. Job Description: We are hiring a Customer Support Specialist to support teams in FinTech.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.', 'Candidate Role: Customer Support Specialist. Seniority Level: Senior. Years of Experience: 9. Industry Experience: Retail. Education: High School. Skills: Ticketing, Documentation, Communication, Root Cause Analysis, SLA, Escalations, Troubleshooting, Intercom. Professional Summary: Customer Support Specialist with 9 years of experience in Retail.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.'],
['Job Title: Junior Accountant. Required Seniority: Senior. Industry: Travel. Must-Have Skills: Valuation, Forecasting, Variance Analysis, KPIs. Nice-to-Have Skills: Budgeting. Job Description: We are hiring a Junior Accountant to support teams in Travel.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.', 'Candidate Role: Financial Analyst. Seniority Level: Junior. Years of Experience: 2. Industry Experience: E-commerce. Education: MBA. Skills: Variance Analysis, KPIs, Reporting, Budgeting, Accounting, Valuation. Professional Summary: Financial Analyst with 2 years of experience in E-commerce.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.'],
['Job Title: Sales Representative. Required Seniority: Senior. Industry: Cybersecurity. Must-Have Skills: Prospecting, Account Management, Pipeline Management, Closing. Nice-to-Have Skills: Negotiation. Job Description: We are hiring a Sales Representative to support teams in Cybersecurity.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.', 'Candidate Role: Sales Representative. Seniority Level: Mid. Years of Experience: 6. Industry Experience: SaaS. Education: High School. Skills: CRM, Negotiation, Prospecting, Pipeline Management, Discovery Calls, Closing, Account Management, Lead Generation. Professional Summary: Sales Representative with 6 years of experience in SaaS.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.'],
['Job Title: Sales Representative. Required Seniority: Mid. Industry: E-commerce. Must-Have Skills: Prospecting, Negotiation, Outbound Outreach. Nice-to-Have Skills: CRM. Job Description: We are hiring a Sales Representative to support teams in E-commerce.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.', 'Candidate Role: Sales Representative. Seniority Level: Mid. Years of Experience: 5. Industry Experience: E-commerce. Education: High School. Skills: Outbound Outreach, Closing, Forecasting, Negotiation, Pipeline Management, Prospecting, Lead Generation. Professional Summary: Sales Representative with 5 years of experience in E-commerce.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.'],
['Job Title: Program Coordinator. Required Seniority: Senior. Industry: Retail. Must-Have Skills: Reporting, Risk Management, Process Improvement, Timeline Management, KPIs. Nice-to-Have Skills: Stakeholder Communication. Job Description: We are hiring a Program Coordinator to support teams in Retail.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.', 'Candidate Role: Program Coordinator. Seniority Level: Senior. Years of Experience: 11. Industry Experience: FinTech. Education: BA. Skills: Risk Management, Project Planning, KPIs, Jira, Reporting, Timeline Management, Asana, Process Improvement. Professional Summary: Program Coordinator with 11 years of experience in FinTech.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.'],
]
scores = model.predict(pairs)
print(scores)
# [-0.3621 4.0586 -0.2727 -0.2522 -0.4119]
# Or rank different texts based on similarity to a single text
ranks = model.rank(
'Job Title: Customer Support Specialist. Required Seniority: Junior. Industry: FinTech. Must-Have Skills: Ticketing, Documentation, Root Cause Analysis, Communication. Nice-to-Have Skills: Troubleshooting. Job Description: We are hiring a Customer Support Specialist to support teams in FinTech.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.',
[
'Candidate Role: Customer Support Specialist. Seniority Level: Senior. Years of Experience: 9. Industry Experience: Retail. Education: High School. Skills: Ticketing, Documentation, Communication, Root Cause Analysis, SLA, Escalations, Troubleshooting, Intercom. Professional Summary: Customer Support Specialist with 9 years of experience in Retail.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.',
'Candidate Role: Financial Analyst. Seniority Level: Junior. Years of Experience: 2. Industry Experience: E-commerce. Education: MBA. Skills: Variance Analysis, KPIs, Reporting, Budgeting, Accounting, Valuation. Professional Summary: Financial Analyst with 2 years of experience in E-commerce.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.',
'Candidate Role: Sales Representative. Seniority Level: Mid. Years of Experience: 6. Industry Experience: SaaS. Education: High School. Skills: CRM, Negotiation, Prospecting, Pipeline Management, Discovery Calls, Closing, Account Management, Lead Generation. Professional Summary: Sales Representative with 6 years of experience in SaaS.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.',
'Candidate Role: Sales Representative. Seniority Level: Mid. Years of Experience: 5. Industry Experience: E-commerce. Education: High School. Skills: Outbound Outreach, Closing, Forecasting, Negotiation, Pipeline Management, Prospecting, Lead Generation. Professional Summary: Sales Representative with 5 years of experience in E-commerce.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.',
'Candidate Role: Program Coordinator. Seniority Level: Senior. Years of Experience: 11. Industry Experience: FinTech. Education: BA. Skills: Risk Management, Project Planning, KPIs, Jira, Reporting, Timeline Management, Asana, Process Improvement. Professional Summary: Program Coordinator with 11 years of experience in FinTech.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.',
]
)
# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]
```
<!--
### 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.*
-->
<!--
## 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: 120,000 training samples
* Columns: <code>job_text</code>, <code>resume_text</code>, and <code>label</code>
* Approximate statistics based on the first 100 samples:
| | job_text | resume_text | label |
|:---------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:---------------------------------------------------------------|
| type | string | string | float |
| modality | text | text | |
| details | <ul><li>min: 117 tokens</li><li>mean: 125.18 tokens</li><li>max: 136 tokens</li></ul> | <ul><li>min: 92 tokens</li><li>mean: 101.44 tokens</li><li>max: 112 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.45</li><li>max: 1.0</li></ul> |
* Samples:
| job_text | resume_text | label |
|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
| <code>Job Title: Technical Support Specialist. Required Seniority: Junior. Industry: FinTech. Must-Have Skills: Escalations, SLA, Documentation, Communication, Intercom. Nice-to-Have Skills: Ticketing. Job Description: We are hiring a Technical Support Specialist to support teams in FinTech.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.</code> | <code>Candidate Role: Customer Success Associate. Seniority Level: Mid. Years of Experience: 2. Industry Experience: E-commerce. Education: BA. Skills: Intercom, SLA, Customer Satisfaction, Documentation, Root Cause Analysis, Communication, Ticketing. Professional Summary: Customer Success Associate with 2 years of experience in E-commerce.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.</code> | <code>1.0</code> |
| <code>Job Title: FP&A Analyst. Required Seniority: Junior. Industry: Logistics. Must-Have Skills: Forecasting, KPIs, Reporting, Accounting. Nice-to-Have Skills: Financial Modeling. Job Description: We are hiring a FP&A Analyst to support teams in Logistics.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.</code> | <code>Candidate Role: Financial Analyst. Seniority Level: Senior. Years of Experience: 7. Industry Experience: E-commerce. Education: High School. Skills: Excel, Accounting, Cash Flow, Reporting, Variance Analysis, Financial Modeling, Valuation, Forecasting. Professional Summary: Financial Analyst with 7 years of experience in E-commerce.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.</code> | <code>1.0</code> |
| <code>Job Title: Content Marketer. Required Seniority: Senior. Industry: Travel. Must-Have Skills: SEO, Copywriting, Meta Ads, Email Marketing, Google Ads. Nice-to-Have Skills: Content Marketing. Job Description: We are hiring a Content Marketer to support teams in Travel.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.</code> | <code>Candidate Role: Content Marketer. Seniority Level: Junior. Years of Experience: 0. Industry Experience: Retail. Education: MSc. Skills: Copywriting, Conversion Optimization, Landing Pages, Content Marketing, Google Ads, Meta Ads, A/B Testing, SEO. Professional Summary: Content Marketer with 0 years of experience in Retail.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.</code> | <code>0.0</code> |
* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/cross_encoder/losses.html#binarycrossentropyloss) with these parameters:
```json
{
"activation_fn": "torch.nn.modules.linear.Identity",
"pos_weight": null
}
```
### Evaluation Dataset
#### Unnamed Dataset
* Size: 15,000 evaluation samples
* Columns: <code>job_text</code>, <code>resume_text</code>, and <code>label</code>
* Approximate statistics based on the first 100 samples:
| | job_text | resume_text | label |
|:---------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------|
| type | string | string | float |
| modality | text | text | |
| details | <ul><li>min: 116 tokens</li><li>mean: 125.31 tokens</li><li>max: 134 tokens</li></ul> | <ul><li>min: 91 tokens</li><li>mean: 100.88 tokens</li><li>max: 111 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.4</li><li>max: 1.0</li></ul> |
* Samples:
| job_text | resume_text | label |
|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
| <code>Job Title: Customer Support Specialist. Required Seniority: Junior. Industry: FinTech. Must-Have Skills: Ticketing, Documentation, Root Cause Analysis, Communication. Nice-to-Have Skills: Troubleshooting. Job Description: We are hiring a Customer Support Specialist to support teams in FinTech.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.</code> | <code>Candidate Role: Customer Support Specialist. Seniority Level: Senior. Years of Experience: 9. Industry Experience: Retail. Education: High School. Skills: Ticketing, Documentation, Communication, Root Cause Analysis, SLA, Escalations, Troubleshooting, Intercom. Professional Summary: Customer Support Specialist with 9 years of experience in Retail.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.</code> | <code>0.0</code> |
| <code>Job Title: Junior Accountant. Required Seniority: Senior. Industry: Travel. Must-Have Skills: Valuation, Forecasting, Variance Analysis, KPIs. Nice-to-Have Skills: Budgeting. Job Description: We are hiring a Junior Accountant to support teams in Travel.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.</code> | <code>Candidate Role: Financial Analyst. Seniority Level: Junior. Years of Experience: 2. Industry Experience: E-commerce. Education: MBA. Skills: Variance Analysis, KPIs, Reporting, Budgeting, Accounting, Valuation. Professional Summary: Financial Analyst with 2 years of experience in E-commerce.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.</code> | <code>1.0</code> |
| <code>Job Title: Sales Representative. Required Seniority: Senior. Industry: Cybersecurity. Must-Have Skills: Prospecting, Account Management, Pipeline Management, Closing. Nice-to-Have Skills: Negotiation. Job Description: We are hiring a Sales Representative to support teams in Cybersecurity.. Responsibilities: Deliver high-quality work aligned with goals and timelines; Collaborate with stakeholders and communicate progress clearly; Improve processes and contribute to measurable outcomes. Requirements: Relevant experience and ability to learn quickly; Strong communication and ownership mindset; Comfort working with tools, data, and cross-functional teams.</code> | <code>Candidate Role: Sales Representative. Seniority Level: Mid. Years of Experience: 6. Industry Experience: SaaS. Education: High School. Skills: CRM, Negotiation, Prospecting, Pipeline Management, Discovery Calls, Closing, Account Management, Lead Generation. Professional Summary: Sales Representative with 6 years of experience in SaaS.. Experience Highlights: Delivered results using structured workflows and clear communication; Collaborated with stakeholders to define needs and execute tasks; Maintained reporting and documentation to support team performance.</code> | <code>0.0</code> |
* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/cross_encoder/losses.html#binarycrossentropyloss) with these parameters:
```json
{
"activation_fn": "torch.nn.modules.linear.Identity",
"pos_weight": null
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `per_device_train_batch_size`: 32
- `num_train_epochs`: 2
- `learning_rate`: 2e-05
- `warmup_steps`: 0.1
- `weight_decay`: 0.01
- `fp16`: True
- `auto_find_batch_size`: True
- `per_device_eval_batch_size`: 32
- `eval_accumulation_steps`: 4
- `load_best_model_at_end`: True
- `data_seed`: 42
- `dataloader_num_workers`: 2
- `dataloader_persistent_workers`: True
#### All Hyperparameters
<details><summary>Click to expand</summary>
- `per_device_train_batch_size`: 32
- `num_train_epochs`: 2
- `max_steps`: -1
- `learning_rate`: 2e-05
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: None
- `warmup_steps`: 0.1
- `optim`: adamw_torch_fused
- `optim_args`: None
- `weight_decay`: 0.01
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `optim_target_modules`: None
- `gradient_accumulation_steps`: 1
- `average_tokens_across_devices`: True
- `max_grad_norm`: 1.0
- `label_smoothing_factor`: 0.0
- `bf16`: False
- `fp16`: True
- `bf16_full_eval`: False
- `fp16_full_eval`: False
- `tf32`: None
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `use_liger_kernel`: False
- `liger_kernel_config`: None
- `use_cache`: False
- `neftune_noise_alpha`: None
- `torch_empty_cache_steps`: None
- `auto_find_batch_size`: True
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `include_num_input_tokens_seen`: no
- `log_level`: passive
- `log_level_replica`: warning
- `disable_tqdm`: False
- `project`: huggingface
- `trackio_space_id`: None
- `trackio_bucket_id`: None
- `trackio_static_space_id`: None
- `per_device_eval_batch_size`: 32
- `prediction_loss_only`: True
- `eval_on_start`: False
- `eval_do_concat_batches`: True
- `eval_use_gather_object`: False
- `eval_accumulation_steps`: 4
- `include_for_metrics`: []
- `batch_eval_metrics`: False
- `save_only_model`: False
- `save_on_each_node`: False
- `enable_jit_checkpoint`: False
- `push_to_hub`: False
- `hub_private_repo`: None
- `hub_model_id`: None
- `hub_strategy`: every_save
- `hub_always_push`: False
- `hub_revision`: None
- `load_best_model_at_end`: True
- `ignore_data_skip`: False
- `restore_callback_states_from_checkpoint`: False
- `full_determinism`: False
- `seed`: 42
- `data_seed`: 42
- `use_cpu`: 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
- `dataloader_drop_last`: False
- `dataloader_num_workers`: 2
- `dataloader_pin_memory`: True
- `dataloader_persistent_workers`: True
- `dataloader_prefetch_factor`: None
- `remove_unused_columns`: True
- `label_names`: None
- `train_sampling_strategy`: random
- `length_column_name`: length
- `ddp_find_unused_parameters`: None
- `ddp_bucket_cap_mb`: None
- `ddp_broadcast_buffers`: False
- `ddp_static_graph`: None
- `ddp_backend`: None
- `ddp_timeout`: 1800
- `fsdp`: None
- `fsdp_config`: None
- `deepspeed`: None
- `debug`: []
- `skip_memory_metrics`: True
- `do_predict`: False
- `resume_from_checkpoint`: None
- `warmup_ratio`: None
- `local_rank`: -1
- `prompts`: None
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: proportional
- `router_mapping`: {}
- `learning_rate_mapping`: {}
</details>
### Training Logs
| Epoch | Step | Training Loss | Validation Loss |
|:-------:|:--------:|:-------------:|:---------------:|
| 0.0003 | 1 | 1.1285 | - |
| 0.0267 | 100 | 0.9878 | - |
| 0.0533 | 200 | 0.7241 | - |
| 0.08 | 300 | 0.6373 | - |
| 0.1067 | 400 | 0.5818 | - |
| 0.1333 | 500 | 0.5057 | - |
| 0.16 | 600 | 0.4458 | - |
| 0.1867 | 700 | 0.4322 | - |
| 0.2133 | 800 | 0.3922 | - |
| 0.24 | 900 | 0.3820 | - |
| 0.2667 | 1000 | 0.3756 | 0.3510 |
| 0.2933 | 1100 | 0.3824 | - |
| 0.32 | 1200 | 0.3423 | - |
| 0.3467 | 1300 | 0.3432 | - |
| 0.3733 | 1400 | 0.3643 | - |
| 0.4 | 1500 | 0.3589 | - |
| 0.4267 | 1600 | 0.3619 | - |
| 0.4533 | 1700 | 0.3572 | - |
| 0.48 | 1800 | 0.3604 | - |
| 0.5067 | 1900 | 0.3362 | - |
| 0.5333 | 2000 | 0.3453 | 0.3266 |
| 0.56 | 2100 | 0.3397 | - |
| 0.5867 | 2200 | 0.3627 | - |
| 0.6133 | 2300 | 0.3620 | - |
| 0.64 | 2400 | 0.3257 | - |
| 0.6667 | 2500 | 0.3533 | - |
| 0.6933 | 2600 | 0.3408 | - |
| 0.72 | 2700 | 0.3269 | - |
| 0.7467 | 2800 | 0.3446 | - |
| 0.7733 | 2900 | 0.3380 | - |
| 0.8 | 3000 | 0.3529 | 0.3219 |
| 0.8267 | 3100 | 0.3423 | - |
| 0.8533 | 3200 | 0.3213 | - |
| 0.88 | 3300 | 0.3529 | - |
| 0.9067 | 3400 | 0.3523 | - |
| 0.9333 | 3500 | 0.3403 | - |
| 0.96 | 3600 | 0.3344 | - |
| 0.9867 | 3700 | 0.3503 | - |
| 1.0133 | 3800 | 0.3468 | - |
| 1.04 | 3900 | 0.3213 | - |
| 1.0667 | 4000 | 0.3421 | 0.3219 |
| 1.0933 | 4100 | 0.3465 | - |
| 1.12 | 4200 | 0.3227 | - |
| 1.1467 | 4300 | 0.3392 | - |
| 1.1733 | 4400 | 0.3268 | - |
| 1.2 | 4500 | 0.3257 | - |
| 1.2267 | 4600 | 0.3328 | - |
| 1.2533 | 4700 | 0.3453 | - |
| 1.28 | 4800 | 0.3377 | - |
| 1.3067 | 4900 | 0.3268 | - |
| 1.3333 | 5000 | 0.3402 | 0.3160 |
| 1.3600 | 5100 | 0.3420 | - |
| 1.3867 | 5200 | 0.3129 | - |
| 1.4133 | 5300 | 0.3434 | - |
| 1.44 | 5400 | 0.3416 | - |
| 1.4667 | 5500 | 0.3468 | - |
| 1.4933 | 5600 | 0.3231 | - |
| 1.52 | 5700 | 0.3163 | - |
| 1.5467 | 5800 | 0.3165 | - |
| 1.5733 | 5900 | 0.3356 | - |
| 1.6 | 6000 | 0.3245 | 0.3128 |
| 1.6267 | 6100 | 0.3204 | - |
| 1.6533 | 6200 | 0.3091 | - |
| 1.6800 | 6300 | 0.3355 | - |
| 1.7067 | 6400 | 0.3318 | - |
| 1.7333 | 6500 | 0.3407 | - |
| 1.76 | 6600 | 0.3303 | - |
| 1.7867 | 6700 | 0.3145 | - |
| 1.8133 | 6800 | 0.3388 | - |
| 1.8400 | 6900 | 0.3334 | - |
| 1.8667 | 7000 | 0.3249 | 0.3131 |
| 1.8933 | 7100 | 0.3379 | - |
| 1.92 | 7200 | 0.3195 | - |
| 1.9467 | 7300 | 0.3294 | - |
| 1.9733 | 7400 | 0.3312 | - |
| **2.0** | **7500** | **0.3255** | **0.3127** |
* The bold row denotes the saved checkpoint.
### Training Time
- **Training**: 9.4 minutes
### Framework Versions
- Python: 3.12.13
- Sentence Transformers: 5.6.0
- Transformers: 5.13.1
- PyTorch: 2.11.0+cu128
- Accelerate: 1.14.0
- Datasets: 4.0.0
- Tokenizers: 0.22.2
## Additional Resources
- [Training and Finetuning Reranker Models with Sentence Transformers](https://huggingface.co/blog/train-reranker): the end-to-end guide for training or finetuning Cross Encoder (reranker) models.
- [Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/multimodal-sentence-transformers): use text, image, audio, and video reranker models through the same API.
- [Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/train-multimodal-sentence-transformers): training multimodal Cross Encoders.
## 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",
}
```
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