LoRA fine-tune – full record entity matching
Browse files- .gitattributes +1 -0
- README.md +414 -0
- config.json +37 -0
- model.safetensors +3 -0
- special_tokens_map.json +51 -0
- tokenizer.json +3 -0
- tokenizer_config.json +56 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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| 1 |
+
---
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| 2 |
+
tags:
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| 3 |
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- sentence-transformers
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| 4 |
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- cross-encoder
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| 5 |
+
- reranker
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| 6 |
+
- generated_from_trainer
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| 7 |
+
- dataset_size:147
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| 8 |
+
- loss:BinaryCrossEntropyLoss
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| 9 |
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base_model: BAAI/bge-reranker-v2-m3
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| 10 |
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pipeline_tag: text-ranking
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| 11 |
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library_name: sentence-transformers
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| 12 |
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metrics:
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| 13 |
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- accuracy
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| 14 |
+
- accuracy_threshold
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| 15 |
+
- f1
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| 16 |
+
- f1_threshold
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| 17 |
+
- precision
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| 18 |
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- recall
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| 19 |
+
- average_precision
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| 20 |
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model-index:
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| 21 |
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- name: CrossEncoder based on BAAI/bge-reranker-v2-m3
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| 22 |
+
results:
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| 23 |
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- task:
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| 24 |
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type: cross-encoder-classification
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| 25 |
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name: Cross Encoder Classification
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| 26 |
+
dataset:
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| 27 |
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name: entity matching
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| 28 |
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type: entity-matching
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| 29 |
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metrics:
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| 30 |
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- type: accuracy
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| 31 |
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value: 1.0
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| 32 |
+
name: Accuracy
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| 33 |
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- type: accuracy_threshold
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| 34 |
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value: 0.5193085670471191
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| 35 |
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name: Accuracy Threshold
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| 36 |
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- type: f1
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| 37 |
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value: 1.0
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| 38 |
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name: F1
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| 39 |
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- type: f1_threshold
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| 40 |
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value: 0.5193085670471191
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| 41 |
+
name: F1 Threshold
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| 42 |
+
- type: precision
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| 43 |
+
value: 1.0
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| 44 |
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name: Precision
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| 45 |
+
- type: recall
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| 46 |
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value: 1.0
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| 47 |
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name: Recall
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| 48 |
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- type: average_precision
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| 49 |
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value: 1.0
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| 50 |
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name: Average Precision
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| 51 |
+
---
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| 52 |
+
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| 53 |
+
# CrossEncoder based on BAAI/bge-reranker-v2-m3
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| 54 |
+
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| 55 |
+
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.
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| 56 |
+
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| 57 |
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## Model Details
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| 58 |
+
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| 59 |
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### Model Description
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| 60 |
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- **Model Type:** Cross Encoder
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| 61 |
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- **Base model:** [BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3) <!-- at revision 953dc6f6f85a1b2dbfca4c34a2796e7dde08d41e -->
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| 62 |
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- **Maximum Sequence Length:** 512 tokens
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| 63 |
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- **Number of Output Labels:** 1 label
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| 64 |
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<!-- - **Training Dataset:** Unknown -->
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| 65 |
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<!-- - **Language:** Unknown -->
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| 66 |
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<!-- - **License:** Unknown -->
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| 67 |
+
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| 68 |
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### Model Sources
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| 69 |
+
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| 70 |
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- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
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| 71 |
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- **Documentation:** [Cross Encoder Documentation](https://www.sbert.net/docs/cross_encoder/usage/usage.html)
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| 72 |
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- **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/sentence-transformers)
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| 73 |
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- **Hugging Face:** [Cross Encoders on Hugging Face](https://huggingface.co/models?library=sentence-transformers&other=cross-encoder)
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| 74 |
+
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| 75 |
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## Usage
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| 76 |
+
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| 77 |
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### Direct Usage (Sentence Transformers)
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| 78 |
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| 79 |
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First install the Sentence Transformers library:
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| 80 |
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| 81 |
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```bash
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| 82 |
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pip install -U sentence-transformers
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| 83 |
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```
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| 84 |
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| 85 |
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Then you can load this model and run inference.
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| 86 |
+
```python
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| 87 |
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from sentence_transformers import CrossEncoder
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| 88 |
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| 89 |
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# Download from the 🤗 Hub
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| 90 |
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model = CrossEncoder("pujithapsx/test")
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| 91 |
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# Get scores for pairs of texts
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| 92 |
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pairs = [
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| 93 |
+
['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: '],
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| 94 |
+
['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: '],
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| 95 |
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['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: '],
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| 96 |
+
['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: '],
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| 97 |
+
['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: '],
|
| 98 |
+
]
|
| 99 |
+
scores = model.predict(pairs)
|
| 100 |
+
print(scores.shape)
|
| 101 |
+
# (5,)
|
| 102 |
+
|
| 103 |
+
# Or rank different texts based on similarity to a single text
|
| 104 |
+
ranks = model.rank(
|
| 105 |
+
'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: ',
|
| 106 |
+
[
|
| 107 |
+
'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: ',
|
| 108 |
+
'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: ',
|
| 109 |
+
'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: ',
|
| 110 |
+
'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: ',
|
| 111 |
+
'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: ',
|
| 112 |
+
]
|
| 113 |
+
)
|
| 114 |
+
# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]
|
| 115 |
+
```
|
| 116 |
+
|
| 117 |
+
<!--
|
| 118 |
+
### Direct Usage (Transformers)
|
| 119 |
+
|
| 120 |
+
<details><summary>Click to see the direct usage in Transformers</summary>
|
| 121 |
+
|
| 122 |
+
</details>
|
| 123 |
+
-->
|
| 124 |
+
|
| 125 |
+
<!--
|
| 126 |
+
### Downstream Usage (Sentence Transformers)
|
| 127 |
+
|
| 128 |
+
You can finetune this model on your own dataset.
|
| 129 |
+
|
| 130 |
+
<details><summary>Click to expand</summary>
|
| 131 |
+
|
| 132 |
+
</details>
|
| 133 |
+
-->
|
| 134 |
+
|
| 135 |
+
<!--
|
| 136 |
+
### Out-of-Scope Use
|
| 137 |
+
|
| 138 |
+
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
|
| 139 |
+
-->
|
| 140 |
+
|
| 141 |
+
## Evaluation
|
| 142 |
+
|
| 143 |
+
### Metrics
|
| 144 |
+
|
| 145 |
+
#### Cross Encoder Classification
|
| 146 |
+
|
| 147 |
+
* Dataset: `entity-matching`
|
| 148 |
+
* Evaluated with [<code>CrossEncoderClassificationEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderClassificationEvaluator)
|
| 149 |
+
|
| 150 |
+
| Metric | Value |
|
| 151 |
+
|:----------------------|:--------|
|
| 152 |
+
| accuracy | 1.0 |
|
| 153 |
+
| accuracy_threshold | 0.5193 |
|
| 154 |
+
| f1 | 1.0 |
|
| 155 |
+
| f1_threshold | 0.5193 |
|
| 156 |
+
| precision | 1.0 |
|
| 157 |
+
| recall | 1.0 |
|
| 158 |
+
| **average_precision** | **1.0** |
|
| 159 |
+
|
| 160 |
+
<!--
|
| 161 |
+
## Bias, Risks and Limitations
|
| 162 |
+
|
| 163 |
+
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
|
| 164 |
+
-->
|
| 165 |
+
|
| 166 |
+
<!--
|
| 167 |
+
### Recommendations
|
| 168 |
+
|
| 169 |
+
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
|
| 170 |
+
-->
|
| 171 |
+
|
| 172 |
+
## Training Details
|
| 173 |
+
|
| 174 |
+
### Training Dataset
|
| 175 |
+
|
| 176 |
+
#### Unnamed Dataset
|
| 177 |
+
|
| 178 |
+
* Size: 147 training samples
|
| 179 |
+
* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>label</code>
|
| 180 |
+
* Approximate statistics based on the first 147 samples:
|
| 181 |
+
| | sentence1 | sentence2 | label |
|
| 182 |
+
|:--------|:--------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------|:------------------------------------------------|
|
| 183 |
+
| type | string | string | int |
|
| 184 |
+
| 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> |
|
| 185 |
+
* Samples:
|
| 186 |
+
| sentence1 | sentence2 | label |
|
| 187 |
+
|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------|
|
| 188 |
+
| <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> |
|
| 189 |
+
| <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> |
|
| 190 |
+
| <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> |
|
| 191 |
+
* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/cross_encoder/losses.html#binarycrossentropyloss) with these parameters:
|
| 192 |
+
```json
|
| 193 |
+
{
|
| 194 |
+
"activation_fn": "torch.nn.modules.linear.Identity",
|
| 195 |
+
"pos_weight": null
|
| 196 |
+
}
|
| 197 |
+
```
|
| 198 |
+
|
| 199 |
+
### Evaluation Dataset
|
| 200 |
+
|
| 201 |
+
#### Unnamed Dataset
|
| 202 |
+
|
| 203 |
+
* Size: 32 evaluation samples
|
| 204 |
+
* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>label</code>
|
| 205 |
+
* Approximate statistics based on the first 32 samples:
|
| 206 |
+
| | sentence1 | sentence2 | label |
|
| 207 |
+
|:--------|:--------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------|:------------------------------------------------|
|
| 208 |
+
| type | string | string | int |
|
| 209 |
+
| 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> |
|
| 210 |
+
* Samples:
|
| 211 |
+
| sentence1 | sentence2 | label |
|
| 212 |
+
|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------|
|
| 213 |
+
| <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> |
|
| 214 |
+
| <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> |
|
| 215 |
+
| <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> |
|
| 216 |
+
* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/cross_encoder/losses.html#binarycrossentropyloss) with these parameters:
|
| 217 |
+
```json
|
| 218 |
+
{
|
| 219 |
+
"activation_fn": "torch.nn.modules.linear.Identity",
|
| 220 |
+
"pos_weight": null
|
| 221 |
+
}
|
| 222 |
+
```
|
| 223 |
+
|
| 224 |
+
### Training Hyperparameters
|
| 225 |
+
#### Non-Default Hyperparameters
|
| 226 |
+
|
| 227 |
+
- `eval_strategy`: steps
|
| 228 |
+
- `per_device_train_batch_size`: 64
|
| 229 |
+
- `per_device_eval_batch_size`: 64
|
| 230 |
+
- `learning_rate`: 2e-05
|
| 231 |
+
- `weight_decay`: 0.01
|
| 232 |
+
- `num_train_epochs`: 1
|
| 233 |
+
- `warmup_ratio`: 0.1
|
| 234 |
+
- `use_cpu`: True
|
| 235 |
+
- `load_best_model_at_end`: True
|
| 236 |
+
- `dataloader_pin_memory`: False
|
| 237 |
+
|
| 238 |
+
#### All Hyperparameters
|
| 239 |
+
<details><summary>Click to expand</summary>
|
| 240 |
+
|
| 241 |
+
- `overwrite_output_dir`: False
|
| 242 |
+
- `do_predict`: False
|
| 243 |
+
- `eval_strategy`: steps
|
| 244 |
+
- `prediction_loss_only`: True
|
| 245 |
+
- `per_device_train_batch_size`: 64
|
| 246 |
+
- `per_device_eval_batch_size`: 64
|
| 247 |
+
- `per_gpu_train_batch_size`: None
|
| 248 |
+
- `per_gpu_eval_batch_size`: None
|
| 249 |
+
- `gradient_accumulation_steps`: 1
|
| 250 |
+
- `eval_accumulation_steps`: None
|
| 251 |
+
- `torch_empty_cache_steps`: None
|
| 252 |
+
- `learning_rate`: 2e-05
|
| 253 |
+
- `weight_decay`: 0.01
|
| 254 |
+
- `adam_beta1`: 0.9
|
| 255 |
+
- `adam_beta2`: 0.999
|
| 256 |
+
- `adam_epsilon`: 1e-08
|
| 257 |
+
- `max_grad_norm`: 1.0
|
| 258 |
+
- `num_train_epochs`: 1
|
| 259 |
+
- `max_steps`: -1
|
| 260 |
+
- `lr_scheduler_type`: linear
|
| 261 |
+
- `lr_scheduler_kwargs`: None
|
| 262 |
+
- `warmup_ratio`: 0.1
|
| 263 |
+
- `warmup_steps`: 0
|
| 264 |
+
- `log_level`: passive
|
| 265 |
+
- `log_level_replica`: warning
|
| 266 |
+
- `log_on_each_node`: True
|
| 267 |
+
- `logging_nan_inf_filter`: True
|
| 268 |
+
- `save_safetensors`: True
|
| 269 |
+
- `save_on_each_node`: False
|
| 270 |
+
- `save_only_model`: False
|
| 271 |
+
- `restore_callback_states_from_checkpoint`: False
|
| 272 |
+
- `no_cuda`: False
|
| 273 |
+
- `use_cpu`: True
|
| 274 |
+
- `use_mps_device`: False
|
| 275 |
+
- `seed`: 42
|
| 276 |
+
- `data_seed`: None
|
| 277 |
+
- `jit_mode_eval`: False
|
| 278 |
+
- `bf16`: False
|
| 279 |
+
- `fp16`: False
|
| 280 |
+
- `fp16_opt_level`: O1
|
| 281 |
+
- `half_precision_backend`: auto
|
| 282 |
+
- `bf16_full_eval`: False
|
| 283 |
+
- `fp16_full_eval`: False
|
| 284 |
+
- `tf32`: None
|
| 285 |
+
- `local_rank`: 0
|
| 286 |
+
- `ddp_backend`: None
|
| 287 |
+
- `tpu_num_cores`: None
|
| 288 |
+
- `tpu_metrics_debug`: False
|
| 289 |
+
- `debug`: []
|
| 290 |
+
- `dataloader_drop_last`: False
|
| 291 |
+
- `dataloader_num_workers`: 0
|
| 292 |
+
- `dataloader_prefetch_factor`: None
|
| 293 |
+
- `past_index`: -1
|
| 294 |
+
- `disable_tqdm`: False
|
| 295 |
+
- `remove_unused_columns`: True
|
| 296 |
+
- `label_names`: None
|
| 297 |
+
- `load_best_model_at_end`: True
|
| 298 |
+
- `ignore_data_skip`: False
|
| 299 |
+
- `fsdp`: []
|
| 300 |
+
- `fsdp_min_num_params`: 0
|
| 301 |
+
- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
|
| 302 |
+
- `fsdp_transformer_layer_cls_to_wrap`: None
|
| 303 |
+
- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
|
| 304 |
+
- `parallelism_config`: None
|
| 305 |
+
- `deepspeed`: None
|
| 306 |
+
- `label_smoothing_factor`: 0.0
|
| 307 |
+
- `optim`: adamw_torch_fused
|
| 308 |
+
- `optim_args`: None
|
| 309 |
+
- `adafactor`: False
|
| 310 |
+
- `group_by_length`: False
|
| 311 |
+
- `length_column_name`: length
|
| 312 |
+
- `project`: huggingface
|
| 313 |
+
- `trackio_space_id`: trackio
|
| 314 |
+
- `ddp_find_unused_parameters`: None
|
| 315 |
+
- `ddp_bucket_cap_mb`: None
|
| 316 |
+
- `ddp_broadcast_buffers`: False
|
| 317 |
+
- `dataloader_pin_memory`: False
|
| 318 |
+
- `dataloader_persistent_workers`: False
|
| 319 |
+
- `skip_memory_metrics`: True
|
| 320 |
+
- `use_legacy_prediction_loop`: False
|
| 321 |
+
- `push_to_hub`: False
|
| 322 |
+
- `resume_from_checkpoint`: None
|
| 323 |
+
- `hub_model_id`: None
|
| 324 |
+
- `hub_strategy`: every_save
|
| 325 |
+
- `hub_private_repo`: None
|
| 326 |
+
- `hub_always_push`: False
|
| 327 |
+
- `hub_revision`: None
|
| 328 |
+
- `gradient_checkpointing`: False
|
| 329 |
+
- `gradient_checkpointing_kwargs`: None
|
| 330 |
+
- `include_inputs_for_metrics`: False
|
| 331 |
+
- `include_for_metrics`: []
|
| 332 |
+
- `eval_do_concat_batches`: True
|
| 333 |
+
- `fp16_backend`: auto
|
| 334 |
+
- `push_to_hub_model_id`: None
|
| 335 |
+
- `push_to_hub_organization`: None
|
| 336 |
+
- `mp_parameters`:
|
| 337 |
+
- `auto_find_batch_size`: False
|
| 338 |
+
- `full_determinism`: False
|
| 339 |
+
- `torchdynamo`: None
|
| 340 |
+
- `ray_scope`: last
|
| 341 |
+
- `ddp_timeout`: 1800
|
| 342 |
+
- `torch_compile`: False
|
| 343 |
+
- `torch_compile_backend`: None
|
| 344 |
+
- `torch_compile_mode`: None
|
| 345 |
+
- `include_tokens_per_second`: False
|
| 346 |
+
- `include_num_input_tokens_seen`: no
|
| 347 |
+
- `neftune_noise_alpha`: None
|
| 348 |
+
- `optim_target_modules`: None
|
| 349 |
+
- `batch_eval_metrics`: False
|
| 350 |
+
- `eval_on_start`: False
|
| 351 |
+
- `use_liger_kernel`: False
|
| 352 |
+
- `liger_kernel_config`: None
|
| 353 |
+
- `eval_use_gather_object`: False
|
| 354 |
+
- `average_tokens_across_devices`: True
|
| 355 |
+
- `prompts`: None
|
| 356 |
+
- `batch_sampler`: batch_sampler
|
| 357 |
+
- `multi_dataset_batch_sampler`: proportional
|
| 358 |
+
- `router_mapping`: {}
|
| 359 |
+
- `learning_rate_mapping`: {}
|
| 360 |
+
|
| 361 |
+
</details>
|
| 362 |
+
|
| 363 |
+
### Training Logs
|
| 364 |
+
| Epoch | Step | Validation Loss | entity-matching_average_precision |
|
| 365 |
+
|:----------:|:-----:|:---------------:|:---------------------------------:|
|
| 366 |
+
| **0.3333** | **1** | **0.0162** | **1.0** |
|
| 367 |
+
| 0.6667 | 2 | 0.0148 | 1.0 |
|
| 368 |
+
| 1.0 | 3 | 0.0162 | 1.0 |
|
| 369 |
+
|
| 370 |
+
* The bold row denotes the saved checkpoint.
|
| 371 |
+
|
| 372 |
+
### Framework Versions
|
| 373 |
+
- Python: 3.10.12
|
| 374 |
+
- Sentence Transformers: 5.3.0
|
| 375 |
+
- Transformers: 4.57.6
|
| 376 |
+
- PyTorch: 2.10.0+cu128
|
| 377 |
+
- Accelerate: 1.13.0
|
| 378 |
+
- Datasets: 4.8.4
|
| 379 |
+
- Tokenizers: 0.22.2
|
| 380 |
+
|
| 381 |
+
## Citation
|
| 382 |
+
|
| 383 |
+
### BibTeX
|
| 384 |
+
|
| 385 |
+
#### Sentence Transformers
|
| 386 |
+
```bibtex
|
| 387 |
+
@inproceedings{reimers-2019-sentence-bert,
|
| 388 |
+
title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
|
| 389 |
+
author = "Reimers, Nils and Gurevych, Iryna",
|
| 390 |
+
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
|
| 391 |
+
month = "11",
|
| 392 |
+
year = "2019",
|
| 393 |
+
publisher = "Association for Computational Linguistics",
|
| 394 |
+
url = "https://arxiv.org/abs/1908.10084",
|
| 395 |
+
}
|
| 396 |
+
```
|
| 397 |
+
|
| 398 |
+
<!--
|
| 399 |
+
## Glossary
|
| 400 |
+
|
| 401 |
+
*Clearly define terms in order to be accessible across audiences.*
|
| 402 |
+
-->
|
| 403 |
+
|
| 404 |
+
<!--
|
| 405 |
+
## Model Card Authors
|
| 406 |
+
|
| 407 |
+
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
| 408 |
+
-->
|
| 409 |
+
|
| 410 |
+
<!--
|
| 411 |
+
## Model Card Contact
|
| 412 |
+
|
| 413 |
+
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
| 414 |
+
-->
|
config.json
ADDED
|
@@ -0,0 +1,37 @@
|
|
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|
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|
|
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|
|
|
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|
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|
|
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|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"XLMRobertaForSequenceClassification"
|
| 4 |
+
],
|
| 5 |
+
"attention_probs_dropout_prob": 0.1,
|
| 6 |
+
"bos_token_id": 0,
|
| 7 |
+
"classifier_dropout": null,
|
| 8 |
+
"dtype": "float32",
|
| 9 |
+
"eos_token_id": 2,
|
| 10 |
+
"hidden_act": "gelu",
|
| 11 |
+
"hidden_dropout_prob": 0.1,
|
| 12 |
+
"hidden_size": 1024,
|
| 13 |
+
"id2label": {
|
| 14 |
+
"0": "LABEL_0"
|
| 15 |
+
},
|
| 16 |
+
"initializer_range": 0.02,
|
| 17 |
+
"intermediate_size": 4096,
|
| 18 |
+
"label2id": {
|
| 19 |
+
"LABEL_0": 0
|
| 20 |
+
},
|
| 21 |
+
"layer_norm_eps": 1e-05,
|
| 22 |
+
"max_position_embeddings": 8194,
|
| 23 |
+
"model_type": "xlm-roberta",
|
| 24 |
+
"num_attention_heads": 16,
|
| 25 |
+
"num_hidden_layers": 24,
|
| 26 |
+
"output_past": true,
|
| 27 |
+
"pad_token_id": 1,
|
| 28 |
+
"position_embedding_type": "absolute",
|
| 29 |
+
"sentence_transformers": {
|
| 30 |
+
"activation_fn": "torch.nn.modules.activation.Sigmoid",
|
| 31 |
+
"version": "5.3.0"
|
| 32 |
+
},
|
| 33 |
+
"transformers_version": "4.57.6",
|
| 34 |
+
"type_vocab_size": 1,
|
| 35 |
+
"use_cache": true,
|
| 36 |
+
"vocab_size": 250002
|
| 37 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:090765ff55ca33f2f35a1f3938aff17b5164bdd5d1941b28dcf346a5f5b31ef7
|
| 3 |
+
size 2271071852
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,51 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": {
|
| 3 |
+
"content": "<s>",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"cls_token": {
|
| 10 |
+
"content": "<s>",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"eos_token": {
|
| 17 |
+
"content": "</s>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
},
|
| 23 |
+
"mask_token": {
|
| 24 |
+
"content": "<mask>",
|
| 25 |
+
"lstrip": true,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
},
|
| 30 |
+
"pad_token": {
|
| 31 |
+
"content": "<pad>",
|
| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": false,
|
| 34 |
+
"rstrip": false,
|
| 35 |
+
"single_word": false
|
| 36 |
+
},
|
| 37 |
+
"sep_token": {
|
| 38 |
+
"content": "</s>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false
|
| 43 |
+
},
|
| 44 |
+
"unk_token": {
|
| 45 |
+
"content": "<unk>",
|
| 46 |
+
"lstrip": false,
|
| 47 |
+
"normalized": false,
|
| 48 |
+
"rstrip": false,
|
| 49 |
+
"single_word": false
|
| 50 |
+
}
|
| 51 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:cf44dabfaa82b1276a7af64a2ea2c76c047d560cf7bfb5711d6135382372c93d
|
| 3 |
+
size 17083153
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,56 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
|
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|
|
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|
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|
|
|
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|
|
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|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"added_tokens_decoder": {
|
| 3 |
+
"0": {
|
| 4 |
+
"content": "<s>",
|
| 5 |
+
"lstrip": false,
|
| 6 |
+
"normalized": false,
|
| 7 |
+
"rstrip": false,
|
| 8 |
+
"single_word": false,
|
| 9 |
+
"special": true
|
| 10 |
+
},
|
| 11 |
+
"1": {
|
| 12 |
+
"content": "<pad>",
|
| 13 |
+
"lstrip": false,
|
| 14 |
+
"normalized": false,
|
| 15 |
+
"rstrip": false,
|
| 16 |
+
"single_word": false,
|
| 17 |
+
"special": true
|
| 18 |
+
},
|
| 19 |
+
"2": {
|
| 20 |
+
"content": "</s>",
|
| 21 |
+
"lstrip": false,
|
| 22 |
+
"normalized": false,
|
| 23 |
+
"rstrip": false,
|
| 24 |
+
"single_word": false,
|
| 25 |
+
"special": true
|
| 26 |
+
},
|
| 27 |
+
"3": {
|
| 28 |
+
"content": "<unk>",
|
| 29 |
+
"lstrip": false,
|
| 30 |
+
"normalized": false,
|
| 31 |
+
"rstrip": false,
|
| 32 |
+
"single_word": false,
|
| 33 |
+
"special": true
|
| 34 |
+
},
|
| 35 |
+
"250001": {
|
| 36 |
+
"content": "<mask>",
|
| 37 |
+
"lstrip": true,
|
| 38 |
+
"normalized": false,
|
| 39 |
+
"rstrip": false,
|
| 40 |
+
"single_word": false,
|
| 41 |
+
"special": true
|
| 42 |
+
}
|
| 43 |
+
},
|
| 44 |
+
"bos_token": "<s>",
|
| 45 |
+
"clean_up_tokenization_spaces": true,
|
| 46 |
+
"cls_token": "<s>",
|
| 47 |
+
"eos_token": "</s>",
|
| 48 |
+
"extra_special_tokens": {},
|
| 49 |
+
"mask_token": "<mask>",
|
| 50 |
+
"model_max_length": 512,
|
| 51 |
+
"pad_token": "<pad>",
|
| 52 |
+
"sep_token": "</s>",
|
| 53 |
+
"sp_model_kwargs": {},
|
| 54 |
+
"tokenizer_class": "XLMRobertaTokenizer",
|
| 55 |
+
"unk_token": "<unk>"
|
| 56 |
+
}
|