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tags:
- sentence-transformers
- cross-encoder
- reranker
- generated_from_trainer
- dataset_size:147
- loss:BinaryCrossEntropyLoss
base_model: BAAI/bge-reranker-v2-m3
pipeline_tag: text-ranking
library_name: sentence-transformers
metrics:
- accuracy
- accuracy_threshold
- f1
- f1_threshold
- precision
- recall
- average_precision
model-index:
- name: CrossEncoder based on BAAI/bge-reranker-v2-m3
results:
- task:
type: cross-encoder-classification
name: Cross Encoder Classification
dataset:
name: entity matching
type: entity-matching
metrics:
- type: accuracy
value: 1.0
name: Accuracy
- type: accuracy_threshold
value: 0.5193085670471191
name: Accuracy Threshold
- type: f1
value: 1.0
name: F1
- type: f1_threshold
value: 0.5193085670471191
name: F1 Threshold
- type: precision
value: 1.0
name: Precision
- type: recall
value: 1.0
name: Recall
- type: average_precision
value: 1.0
name: Average Precision
---
# CrossEncoder based on BAAI/bge-reranker-v2-m3
This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3) 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:** [BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3) <!-- at revision 953dc6f6f85a1b2dbfca4c34a2796e7dde08d41e -->
- **Maximum Sequence Length:** 512 tokens
- **Number of Output Labels:** 1 label
<!-- - **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)
## 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("pujithapsx/test")
# Get scores for pairs of texts
pairs = [
['Name: Sneha Reddy , First: Sneha , Middle: , Last: Reddy , Gender: F , DOB: 1991-07-11 , Spouse: , Mother: , Father: , Company: FINANCE CORP INDIA , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: HOUSE 687, BLOCK A kolkata , City: KOLKATA , State: WEST BENGAL , ZIP: 700001 , Address1: HOUSE 687, BLOCK A kolkata , City1: KOLKATA , State1: WEST BENGAL , ZIP1: 700001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9454123990 , Phone1: , Phone2: , Phone3: , Phone4: , Email: snehareddy@gmail.com , Email1: , Email2: , Email3: , Email4: ', 'Name: Swati Gupta , First: Swati , Middle: , Last: Gupta , Gender: F , DOB: 2000-09-02 , Spouse: , Mother: , Father: , Company: RETAIL GIANT LTD , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: PLOT 91, NEAR TEMPLE lucknow , City: LUCKNOW , State: UTTAR PRADESH , ZIP: 226001 , Address1: PLOT 91, NEAR TEMPLE lucknow , City1: LUCKNOW , State1: UTTAR PRADESH , ZIP1: 226001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9447112584 , Phone1: , Phone2: , Phone3: , Phone4: , Email: swatigupta@yahoo.com , Email1: , Email2: , Email3: , Email4: '],
['Name: Pradeep Kumar , First: Pradeep , Middle: , Last: Kumar , Gender: M , DOB: 1984-05-19 , Spouse: , Mother: , Father: , Company: MICROSOFT INDIA , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: 169 KONDHWA NEAR SCHOOL , City: BANGALORE , State: KARNATAKA , ZIP: 560066 , Address1: 169 KONDHWA NEAR SCHOOL , City1: BANGALORE , State1: KARNATAKA , ZIP1: 560066 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 8574585188 , Phone1: , Phone2: , Phone3: , Phone4: , Email: pradeepkumar@workmail.com , Email1: , Email2: , Email3: , Email4: ', 'Name: Kavya Sharma , First: Kavya , Middle: , Last: Sharma , Gender: F , DOB: 2002-02-20 , Spouse: , Mother: , Father: , Company: PAYTM , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: 477 LAJPAT NAGAR NEAR TEMPLE , City: MUMBAI , State: MAHARASHTRA , ZIP: 400017 , Address1: 477 LAJPAT NAGAR NEAR TEMPLE , City1: MUMBAI , State1: MAHARASHTRA , ZIP1: 400017 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 7168571579 , Phone1: , Phone2: , Phone3: , Phone4: , Email: kavyasharma@workmail.com , Email1: , Email2: , Email3: , Email4: '],
['Name: Priya Prasad Reddy , First: Priya , Middle: Prasad , Last: Reddy , Gender: F , DOB: 1983-07-03 , Spouse: , Mother: , Father: , Company: GLOBAL INFOTECH , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: FLAT 401, LAKE APT, 24 MAIN RD , City: LUCKNOW , State: UTTAR PRADESH , ZIP: 226001 , Address1: FLAT 401, LAKE APT, 24 MAIN RD , City1: LUCKNOW , State1: UTTAR PRADESH , ZIP1: 226001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9149203558 , Phone1: , Phone2: , Phone3: , Phone4: , Email: priyareddy@gmail.com , Email1: priya.reddy@globalinfotech.com , Email2: , Email3: , Email4: ', 'Name: Priya Reddy , First: Priya , Middle: , Last: Reddy , Gender: F , DOB: 1983-07-03 , Spouse: , Mother: , Father: , Company: GLOBAL INFOTECH PVT LTD , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: FLAT 401, LAKE APARTMENT, 24 MAIN ROAD , City: LUCKNOW , State: UTTAR PRADESH , ZIP: 226001 , Address1: FLAT 401, LAKE APARTMENT, 24 MAIN ROAD , City1: LUCKNOW , State1: UTTAR PRADESH , ZIP1: 226001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9208449460 , Phone1: , Phone2: , Phone3: , Phone4: , Email: priyareddy@gmail.com , Email1: priya.reddy@globalinfotech.com , Email2: , Email3: , Email4: '],
['Name: Divya Patel , First: Divya , Middle: , Last: Patel , Gender: F , DOB: 1985-02-01 , Spouse: , Mother: , Father: , Company: INFOSYS TECHNOLOGIES , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: 316 SECTOR 12 NEAR PARK , City: HYDERABAD , State: TELANGANA , ZIP: 500048 , Address1: 316 SECTOR 12 NEAR PARK , City1: HYDERABAD , State1: TELANGANA , ZIP1: 500048 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 8883181644 , Phone1: , Phone2: , Phone3: , Phone4: , Email: divyapatel@outlook.com , Email1: , Email2: , Email3: , Email4: ', 'Name: Nitin Rao , First: Nitin , Middle: , Last: Rao , Gender: M , DOB: 1987-12-02 , Spouse: , Mother: , Father: , Company: RELIANCE JIO , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: 612 BANJARA HILLS NEAR PARK , City: COIMBATORE , State: TAMIL NADU , ZIP: 641039 , Address1: 612 BANJARA HILLS NEAR PARK , City1: COIMBATORE , State1: TAMIL NADU , ZIP1: 641039 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9358550137 , Phone1: , Phone2: , Phone3: , Phone4: , Email: nitinrao@gmail.com , Email1: , Email2: , Email3: , Email4: '],
['Name: Rahul Iyer , First: Rahul , Middle: , Last: Iyer , Gender: M , DOB: 1980-02-25 , Spouse: , Mother: , Father: , Company: MANUFACTURING CO , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: FLAT 271, PARK APT, 32 MAIN RD , City: BANGALORE , State: KARNATAKA , ZIP: 560001 , Address1: FLAT 271, PARK APT, 32 MAIN RD , City1: BANGALORE , State1: KARNATAKA , ZIP1: 560001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9162959284 , Phone1: , Phone2: , Phone3: , Phone4: , Email: rahuliyer@gmail.com , Email1: rahul.iyer@manufacturingco.com , Email2: , Email3: , Email4: ', 'Name: Rahul Iyer , First: Rahul , Middle: , Last: Iyer , Gender: M , DOB: 1980-02-25 , Spouse: , Mother: , Father: , Company: MANUFACTURING CO PVT LTD , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: FLAT 271, PARK APT, 32 MAIN RD , City: BANGALORE , State: KARNATAKA , ZIP: 560001 , Address1: FLAT 271, PARK APT, 32 MAIN RD , City1: BANGALORE , State1: KARNATAKA , ZIP1: 560001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9162959284 , Phone1: , Phone2: , Phone3: , Phone4: , Email: rahuliyer@gmail.com , Email1: rahul.iyer@manufacturingco.com , Email2: , Email3: , Email4: '],
]
scores = model.predict(pairs)
print(scores.shape)
# (5,)
# Or rank different texts based on similarity to a single text
ranks = model.rank(
'Name: Sneha Reddy , First: Sneha , Middle: , Last: Reddy , Gender: F , DOB: 1991-07-11 , Spouse: , Mother: , Father: , Company: FINANCE CORP INDIA , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: HOUSE 687, BLOCK A kolkata , City: KOLKATA , State: WEST BENGAL , ZIP: 700001 , Address1: HOUSE 687, BLOCK A kolkata , City1: KOLKATA , State1: WEST BENGAL , ZIP1: 700001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9454123990 , Phone1: , Phone2: , Phone3: , Phone4: , Email: snehareddy@gmail.com , Email1: , Email2: , Email3: , Email4: ',
[
'Name: Swati Gupta , First: Swati , Middle: , Last: Gupta , Gender: F , DOB: 2000-09-02 , Spouse: , Mother: , Father: , Company: RETAIL GIANT LTD , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: PLOT 91, NEAR TEMPLE lucknow , City: LUCKNOW , State: UTTAR PRADESH , ZIP: 226001 , Address1: PLOT 91, NEAR TEMPLE lucknow , City1: LUCKNOW , State1: UTTAR PRADESH , ZIP1: 226001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9447112584 , Phone1: , Phone2: , Phone3: , Phone4: , Email: swatigupta@yahoo.com , Email1: , Email2: , Email3: , Email4: ',
'Name: Kavya Sharma , First: Kavya , Middle: , Last: Sharma , Gender: F , DOB: 2002-02-20 , Spouse: , Mother: , Father: , Company: PAYTM , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: 477 LAJPAT NAGAR NEAR TEMPLE , City: MUMBAI , State: MAHARASHTRA , ZIP: 400017 , Address1: 477 LAJPAT NAGAR NEAR TEMPLE , City1: MUMBAI , State1: MAHARASHTRA , ZIP1: 400017 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 7168571579 , Phone1: , Phone2: , Phone3: , Phone4: , Email: kavyasharma@workmail.com , Email1: , Email2: , Email3: , Email4: ',
'Name: Priya Reddy , First: Priya , Middle: , Last: Reddy , Gender: F , DOB: 1983-07-03 , Spouse: , Mother: , Father: , Company: GLOBAL INFOTECH PVT LTD , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: FLAT 401, LAKE APARTMENT, 24 MAIN ROAD , City: LUCKNOW , State: UTTAR PRADESH , ZIP: 226001 , Address1: FLAT 401, LAKE APARTMENT, 24 MAIN ROAD , City1: LUCKNOW , State1: UTTAR PRADESH , ZIP1: 226001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9208449460 , Phone1: , Phone2: , Phone3: , Phone4: , Email: priyareddy@gmail.com , Email1: priya.reddy@globalinfotech.com , Email2: , Email3: , Email4: ',
'Name: Nitin Rao , First: Nitin , Middle: , Last: Rao , Gender: M , DOB: 1987-12-02 , Spouse: , Mother: , Father: , Company: RELIANCE JIO , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: 612 BANJARA HILLS NEAR PARK , City: COIMBATORE , State: TAMIL NADU , ZIP: 641039 , Address1: 612 BANJARA HILLS NEAR PARK , City1: COIMBATORE , State1: TAMIL NADU , ZIP1: 641039 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9358550137 , Phone1: , Phone2: , Phone3: , Phone4: , Email: nitinrao@gmail.com , Email1: , Email2: , Email3: , Email4: ',
'Name: Rahul Iyer , First: Rahul , Middle: , Last: Iyer , Gender: M , DOB: 1980-02-25 , Spouse: , Mother: , Father: , Company: MANUFACTURING CO PVT LTD , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: FLAT 271, PARK APT, 32 MAIN RD , City: BANGALORE , State: KARNATAKA , ZIP: 560001 , Address1: FLAT 271, PARK APT, 32 MAIN RD , City1: BANGALORE , State1: KARNATAKA , ZIP1: 560001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9162959284 , Phone1: , Phone2: , Phone3: , Phone4: , Email: rahuliyer@gmail.com , Email1: rahul.iyer@manufacturingco.com , Email2: , Email3: , Email4: ',
]
)
# [{'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.*
-->
## Evaluation
### Metrics
#### Cross Encoder Classification
* Dataset: `entity-matching`
* Evaluated with [<code>CrossEncoderClassificationEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderClassificationEvaluator)
| Metric | Value |
|:----------------------|:--------|
| accuracy | 1.0 |
| accuracy_threshold | 0.5193 |
| f1 | 1.0 |
| f1_threshold | 0.5193 |
| precision | 1.0 |
| recall | 1.0 |
| **average_precision** | **1.0** |
<!--
## 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: 147 training samples
* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>label</code>
* Approximate statistics based on the first 147 samples:
| | sentence1 | sentence2 | label |
|:--------|:--------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------|:------------------------------------------------|
| type | string | string | int |
| details | <ul><li>min: 620 characters</li><li>mean: 659.54 characters</li><li>max: 715 characters</li></ul> | <ul><li>min: 627 characters</li><li>mean: 662.53 characters</li><li>max: 731 characters</li></ul> | <ul><li>0: ~53.74%</li><li>1: ~46.26%</li></ul> |
* Samples:
| sentence1 | sentence2 | label |
|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------|
| <code>Name: Riya Singh , First: Riya , Middle: , Last: Singh , Gender: F , DOB: 1992-01-11 , Spouse: , Mother: , Father: , Company: EDU SERVICES , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: HOUSE 821, GALI NO 5 chennai , City: CHENNAI , State: TAMIL NADU , ZIP: 600001 , Address1: HOUSE 821, GALI NO 5 chennai , City1: CHENNAI , State1: TAMIL NADU , ZIP1: 600001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9993381017 , Phone1: , Phone2: , Phone3: , Phone4: , Email: riyasingh@gmail.com , Email1: , Email2: , Email3: , Email4: </code> | <code>Name: Sneha Rao , First: Sneha , Middle: , Last: Rao , Gender: F , DOB: 1981-04-14 , Spouse: , Mother: , Father: , Company: MANUFACTURING CO , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: PLOT 537, PHASE 2 ahmedabad , City: AHMEDABAD , State: GUJARAT , ZIP: 380001 , Address1: PLOT 537, PHASE 2 ahmedabad , City1: AHMEDABAD , State1: GUJARAT , ZIP1: 380001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9433154770 , Phone1: , Phone2: , Phone3: , Phone4: , Email: sneharao@yahoo.com , Email1: , Email2: , Email3: , Email4: </code> | <code>0</code> |
| <code>Name: Pooja Sharma , First: Pooja , Middle: , Last: Sharma , Gender: F , DOB: 1993-01-13 , Spouse: , Mother: , Father: , Company: MANUFACTURING CO , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: HOUSE 383, BLOCK A lucknow , City: LUCKNOW , State: UTTAR PRADESH , ZIP: 226001 , Address1: HOUSE 383, BLOCK A lucknow , City1: LUCKNOW , State1: UTTAR PRADESH , ZIP1: 226001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9187623171 , Phone1: , Phone2: , Phone3: , Phone4: , Email: poojasharma@gmail.com , Email1: , Email2: , Email3: , Email4: </code> | <code>Name: Meena Sharma , First: Meena , Middle: , Last: Sharma , Gender: F , DOB: 1977-05-27 , Spouse: , Mother: , Father: , Company: AUTO PARTS PVT , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: PLOT 713, PHASE 2 ahmedabad , City: AHMEDABAD , State: GUJARAT , ZIP: 380001 , Address1: PLOT 713, PHASE 2 ahmedabad , City1: AHMEDABAD , State1: GUJARAT , ZIP1: 380001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9581682167 , Phone1: , Phone2: , Phone3: , Phone4: , Email: meenasharma@yahoo.com , Email1: , Email2: , Email3: , Email4: </code> | <code>0</code> |
| <code>Name: Swati Iyer , First: Swati , Middle: , Last: Iyer , Gender: F , DOB: 1996-06-14 , Spouse: , Mother: , Father: , Company: EDU SERVICES , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: HOUSE 339, SECTOR 12 lucknow , City: LUCKNOW , State: UTTAR PRADESH , ZIP: 226001 , Address1: HOUSE 339, SECTOR 12 lucknow , City1: LUCKNOW , State1: UTTAR PRADESH , ZIP1: 226001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9390894296 , Phone1: , Phone2: , Phone3: , Phone4: , Email: swatiiyer@gmail.com , Email1: , Email2: , Email3: , Email4: </code> | <code>Name: Riya Verma , First: Riya , Middle: , Last: Verma , Gender: F , DOB: 1982-12-07 , Spouse: , Mother: , Father: , Company: ENERGY SOLUTIONS , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: PLOT 123, OLD TOWN kolkata , City: KOLKATA , State: WEST BENGAL , ZIP: 700001 , Address1: PLOT 123, OLD TOWN kolkata , City1: KOLKATA , State1: WEST BENGAL , ZIP1: 700001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9918394863 , Phone1: , Phone2: , Phone3: , Phone4: , Email: riyaverma@yahoo.com , Email1: , Email2: , Email3: , Email4: </code> | <code>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: 32 evaluation samples
* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>label</code>
* Approximate statistics based on the first 32 samples:
| | sentence1 | sentence2 | label |
|:--------|:--------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------|:------------------------------------------------|
| type | string | string | int |
| details | <ul><li>min: 622 characters</li><li>mean: 662.03 characters</li><li>max: 708 characters</li></ul> | <ul><li>min: 629 characters</li><li>mean: 666.31 characters</li><li>max: 725 characters</li></ul> | <ul><li>0: ~53.12%</li><li>1: ~46.88%</li></ul> |
* Samples:
| sentence1 | sentence2 | label |
|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------|
| <code>Name: Sneha Reddy , First: Sneha , Middle: , Last: Reddy , Gender: F , DOB: 1991-07-11 , Spouse: , Mother: , Father: , Company: FINANCE CORP INDIA , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: HOUSE 687, BLOCK A kolkata , City: KOLKATA , State: WEST BENGAL , ZIP: 700001 , Address1: HOUSE 687, BLOCK A kolkata , City1: KOLKATA , State1: WEST BENGAL , ZIP1: 700001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9454123990 , Phone1: , Phone2: , Phone3: , Phone4: , Email: snehareddy@gmail.com , Email1: , Email2: , Email3: , Email4: </code> | <code>Name: Swati Gupta , First: Swati , Middle: , Last: Gupta , Gender: F , DOB: 2000-09-02 , Spouse: , Mother: , Father: , Company: RETAIL GIANT LTD , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: PLOT 91, NEAR TEMPLE lucknow , City: LUCKNOW , State: UTTAR PRADESH , ZIP: 226001 , Address1: PLOT 91, NEAR TEMPLE lucknow , City1: LUCKNOW , State1: UTTAR PRADESH , ZIP1: 226001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9447112584 , Phone1: , Phone2: , Phone3: , Phone4: , Email: swatigupta@yahoo.com , Email1: , Email2: , Email3: , Email4: </code> | <code>0</code> |
| <code>Name: Pradeep Kumar , First: Pradeep , Middle: , Last: Kumar , Gender: M , DOB: 1984-05-19 , Spouse: , Mother: , Father: , Company: MICROSOFT INDIA , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: 169 KONDHWA NEAR SCHOOL , City: BANGALORE , State: KARNATAKA , ZIP: 560066 , Address1: 169 KONDHWA NEAR SCHOOL , City1: BANGALORE , State1: KARNATAKA , ZIP1: 560066 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 8574585188 , Phone1: , Phone2: , Phone3: , Phone4: , Email: pradeepkumar@workmail.com , Email1: , Email2: , Email3: , Email4: </code> | <code>Name: Kavya Sharma , First: Kavya , Middle: , Last: Sharma , Gender: F , DOB: 2002-02-20 , Spouse: , Mother: , Father: , Company: PAYTM , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: 477 LAJPAT NAGAR NEAR TEMPLE , City: MUMBAI , State: MAHARASHTRA , ZIP: 400017 , Address1: 477 LAJPAT NAGAR NEAR TEMPLE , City1: MUMBAI , State1: MAHARASHTRA , ZIP1: 400017 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 7168571579 , Phone1: , Phone2: , Phone3: , Phone4: , Email: kavyasharma@workmail.com , Email1: , Email2: , Email3: , Email4: </code> | <code>0</code> |
| <code>Name: Priya Prasad Reddy , First: Priya , Middle: Prasad , Last: Reddy , Gender: F , DOB: 1983-07-03 , Spouse: , Mother: , Father: , Company: GLOBAL INFOTECH , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: FLAT 401, LAKE APT, 24 MAIN RD , City: LUCKNOW , State: UTTAR PRADESH , ZIP: 226001 , Address1: FLAT 401, LAKE APT, 24 MAIN RD , City1: LUCKNOW , State1: UTTAR PRADESH , ZIP1: 226001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9149203558 , Phone1: , Phone2: , Phone3: , Phone4: , Email: priyareddy@gmail.com , Email1: priya.reddy@globalinfotech.com , Email2: , Email3: , Email4: </code> | <code>Name: Priya Reddy , First: Priya , Middle: , Last: Reddy , Gender: F , DOB: 1983-07-03 , Spouse: , Mother: , Father: , Company: GLOBAL INFOTECH PVT LTD , ParentCompany: , TaxID: , LicenseID: , PassportID: , Address: FLAT 401, LAKE APARTMENT, 24 MAIN ROAD , City: LUCKNOW , State: UTTAR PRADESH , ZIP: 226001 , Address1: FLAT 401, LAKE APARTMENT, 24 MAIN ROAD , City1: LUCKNOW , State1: UTTAR PRADESH , ZIP1: 226001 , Address2: , City2: , State2: , ZIP2: , Address3: , City3: , State3: , ZIP3: , Address4: , City4: , State4: , ZIP4: , Phone: 9208449460 , Phone1: , Phone2: , Phone3: , Phone4: , Email: priyareddy@gmail.com , Email1: priya.reddy@globalinfotech.com , Email2: , Email3: , Email4: </code> | <code>1</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
- `eval_strategy`: steps
- `per_device_train_batch_size`: 64
- `per_device_eval_batch_size`: 64
- `learning_rate`: 2e-05
- `weight_decay`: 0.01
- `num_train_epochs`: 1
- `warmup_ratio`: 0.1
- `use_cpu`: True
- `load_best_model_at_end`: True
- `dataloader_pin_memory`: False
#### All Hyperparameters
<details><summary>Click to expand</summary>
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: steps
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 64
- `per_device_eval_batch_size`: 64
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 1
- `eval_accumulation_steps`: None
- `torch_empty_cache_steps`: None
- `learning_rate`: 2e-05
- `weight_decay`: 0.01
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1.0
- `num_train_epochs`: 1
- `max_steps`: -1
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: None
- `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`: True
- `use_mps_device`: False
- `seed`: 42
- `data_seed`: None
- `jit_mode_eval`: False
- `bf16`: False
- `fp16`: False
- `fp16_opt_level`: O1
- `half_precision_backend`: auto
- `bf16_full_eval`: False
- `fp16_full_eval`: False
- `tf32`: None
- `local_rank`: 0
- `ddp_backend`: None
- `tpu_num_cores`: None
- `tpu_metrics_debug`: False
- `debug`: []
- `dataloader_drop_last`: False
- `dataloader_num_workers`: 0
- `dataloader_prefetch_factor`: None
- `past_index`: -1
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: 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}
- `parallelism_config`: 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
- `project`: huggingface
- `trackio_space_id`: trackio
- `ddp_find_unused_parameters`: None
- `ddp_bucket_cap_mb`: None
- `ddp_broadcast_buffers`: False
- `dataloader_pin_memory`: False
- `dataloader_persistent_workers`: False
- `skip_memory_metrics`: True
- `use_legacy_prediction_loop`: False
- `push_to_hub`: False
- `resume_from_checkpoint`: None
- `hub_model_id`: None
- `hub_strategy`: every_save
- `hub_private_repo`: None
- `hub_always_push`: False
- `hub_revision`: None
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `include_for_metrics`: []
- `eval_do_concat_batches`: True
- `fp16_backend`: auto
- `push_to_hub_model_id`: None
- `push_to_hub_organization`: None
- `mp_parameters`:
- `auto_find_batch_size`: False
- `full_determinism`: False
- `torchdynamo`: None
- `ray_scope`: last
- `ddp_timeout`: 1800
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `include_tokens_per_second`: False
- `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
- `prompts`: None
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: proportional
- `router_mapping`: {}
- `learning_rate_mapping`: {}
</details>
### Training Logs
| Epoch | Step | Validation Loss | entity-matching_average_precision |
|:----------:|:-----:|:---------------:|:---------------------------------:|
| **0.3333** | **1** | **0.0162** | **1.0** |
| 0.6667 | 2 | 0.0148 | 1.0 |
| 1.0 | 3 | 0.0162 | 1.0 |
* The bold row denotes the saved checkpoint.
### Framework Versions
- Python: 3.10.12
- Sentence Transformers: 5.3.0
- Transformers: 4.57.6
- PyTorch: 2.10.0+cu128
- Accelerate: 1.13.0
- Datasets: 4.8.4
- 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",
}
```
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