README.md

---
language:
- en
license: apache-2.0
tags:
- biencoder
- sentence-transformers
- text-classification
- sentence-pair-classification
- semantic-similarity
- semantic-search
- retrieval
- reranking
- generated_from_trainer
- dataset_size:1056095
- loss:CoSENTLoss
base_model: Alibaba-NLP/gte-modernbert-base
widget:
- source_sentence: In 2015 Adolf Hitler appeared in the kickstarter short movie ``
    Kung Fury `` as Taccone ( A.K.A .
  sentences:
  - In 2015 , Adolf Hitler appeared in the Kickstarter - short film `` Kung Fury ``
    as Taccone ( A.K.A .
  - In 1795 , the only white residents were Dr. John Laidley and two brothers with
    the surname Ainslie .
  - The 125th University Match was played in March 2014 at the Rye Golf Club , Oxford
    , East Sussex won the game 8.5 - 6.5 .
- source_sentence: From 1973 to 1974 , Aubrey toured with the Cambridge Theatre Company
    as Diggory in `` She Stoops to Conquer `` and again as Aguecheek .
  sentences:
  - Oxide can be reduced to metallic samarium at higher temperatures by heating with
    a reducing agent such as hydrogen or carbon monoxide .
  - From 1973 to 1974 Aguecheek toured with the Cambridge Theatre Company as Diggory
    in `` You Stoops to Conquer `` and again as Aubrey .
  - The medals were presented by Barry Maister , IOC member , New Zealand and Sarah
    Webb Gosling , Vice President of World Sailing .
- source_sentence: There is no official wall on the border , although there are sections
    of fence near populated areas and continuous border crossings .
  sentences:
  - The 2014 -- 15 Boston Bruins season was the 91st season for the National Hockey
    League franchise that was established on November 1 , 1924 .
  - He was trained by the Inghams and owned by John Hawkes .
  - There is no continuous wall on the border , although there are fence sections
    near populated areas and official border crossings .
- source_sentence: Capital . `` The French established similar hill stations in Indochina
    , such as Dalat built in 1921 .
  sentences:
  - Lubuk China is a small town in Alor Gajah District , Melaka , Malaysia . It is
    situated near the border with Negeri Sembilan .
  - The French established similar hill stations in Indochina , such as Dalat , built
    in 1921 .
  - John Potts ( or Pott ) was a doctor and colonial governor of Virginia in the Jamestown
    settlement at Virginia Colony in the early 17th century .
- source_sentence: The band pursued `` signals `` in January 2012 in three weeks ,
    and drums were recorded in a day and a half .
  sentences:
  - It was repaired at the beginning of the 20th century and is listed as closed in
    our records .
  - The band tracked `` Signals `` in three weeks in January 2012 . Drums were recorded
    in a day and a half .
  - Contributors include actor Anton LaVey , Satanist Christopher Lee , serial killer
    expert Clive Barker , author Karen Greenlee , and necrophile Robert Ressler .
datasets:
- aditeyabaral-redis/langcache-sentencepairs-v1
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
- cosine_accuracy
- cosine_accuracy_threshold
- cosine_f1
- cosine_f1_threshold
- cosine_precision
- cosine_recall
- cosine_ap
- cosine_mcc
model-index:
- name: Redis fine-tuned BiEncoder model for semantic caching on LangCache
  results:
  - task:
      type: binary-classification
      name: Binary Classification
    dataset:
      name: val
      type: val
    metrics:
    - type: cosine_accuracy
      value: 0.7629982153480072
      name: Cosine Accuracy
    - type: cosine_accuracy_threshold
      value: 0.8640064001083374
      name: Cosine Accuracy Threshold
    - type: cosine_f1
      value: 0.6907391673746814
      name: Cosine F1
    - type: cosine_f1_threshold
      value: 0.8261547684669495
      name: Cosine F1 Threshold
    - type: cosine_precision
      value: 0.6290946608202218
      name: Cosine Precision
    - type: cosine_recall
      value: 0.7657770800627943
      name: Cosine Recall
    - type: cosine_ap
      value: 0.7350929175906749
      name: Cosine Ap
    - type: cosine_mcc
      value: 0.47714361581572273
      name: Cosine Mcc
  - task:
      type: binary-classification
      name: Binary Classification
    dataset:
      name: test
      type: test
    metrics:
    - type: cosine_accuracy
      value: 0.7035036519888425
      name: Cosine Accuracy
    - type: cosine_accuracy_threshold
      value: 0.8520700931549072
      name: Cosine Accuracy Threshold
    - type: cosine_f1
      value: 0.7118460123901542
      name: Cosine F1
    - type: cosine_f1_threshold
      value: 0.8109649419784546
      name: Cosine F1 Threshold
    - type: cosine_precision
      value: 0.5979034259235814
      name: Cosine Precision
    - type: cosine_recall
      value: 0.8794413407821229
      name: Cosine Recall
    - type: cosine_ap
      value: 0.6473553527394227
      name: Cosine Ap
    - type: cosine_mcc
      value: 0.4408784752892243
      name: Cosine Mcc
---

# Redis fine-tuned BiEncoder model for semantic caching on LangCache

This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Alibaba-NLP/gte-modernbert-base](https://huggingface.co/Alibaba-NLP/gte-modernbert-base) on the [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/aditeyabaral-redis/langcache-sentencepairs-v1) dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for sentence pair similarity.

## Model Details

### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [Alibaba-NLP/gte-modernbert-base](https://huggingface.co/Alibaba-NLP/gte-modernbert-base) <!-- at revision e7f32e3c00f91d699e8c43b53106206bcc72bb22 -->
- **Maximum Sequence Length:** 8192 tokens
- **Output Dimensionality:** 768 dimensions
- **Similarity Function:** Cosine Similarity
- **Training Dataset:**
    - [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/aditeyabaral-redis/langcache-sentencepairs-v1)
- **Language:** en
- **License:** apache-2.0

### Model Sources

- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)

### Full Model Architecture

```
SentenceTransformer(
  (0): Transformer({'max_seq_length': 8192, 'do_lower_case': False, 'architecture': 'ModernBertModel'})
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
)
```

## Usage

### Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

```bash
pip install -U sentence-transformers
```

Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("aditeyabaral-redis/langcache-embed-v3")
# Run inference
sentences = [
    'The band pursued `` signals `` in January 2012 in three weeks , and drums were recorded in a day and a half .',
    'The band tracked `` Signals `` in three weeks in January 2012 . Drums were recorded in a day and a half .',
    'Contributors include actor Anton LaVey , Satanist Christopher Lee , serial killer expert Clive Barker , author Karen Greenlee , and necrophile Robert Ressler .',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities)
# tensor([[1.0000, 0.9599, 0.4944],
#         [0.9599, 1.0000, 0.5097],
#         [0.4944, 0.5097, 1.0000]])
```

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## Evaluation

### Metrics

#### Binary Classification

* Datasets: `val` and `test`
* Evaluated with [<code>BinaryClassificationEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.BinaryClassificationEvaluator)

| Metric                    | val        | test       |
|:--------------------------|:-----------|:-----------|
| cosine_accuracy           | 0.763      | 0.7035     |
| cosine_accuracy_threshold | 0.864      | 0.8521     |
| cosine_f1                 | 0.6907     | 0.7118     |
| cosine_f1_threshold       | 0.8262     | 0.811      |
| cosine_precision          | 0.6291     | 0.5979     |
| cosine_recall             | 0.7658     | 0.8794     |
| **cosine_ap**             | **0.7351** | **0.6474** |
| cosine_mcc                | 0.4771     | 0.4409     |

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## Training Details

### Training Dataset

#### LangCache Sentence Pairs (all)

* Dataset: [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/aditeyabaral-redis/langcache-sentencepairs-v1)
* Size: 62,021 training samples
* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>label</code>
* Approximate statistics based on the first 1000 samples:
  |         | sentence1                                                                         | sentence2                                                                         | label                                           |
  |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:------------------------------------------------|
  | type    | string                                                                            | string                                                                            | int                                             |
  | details | <ul><li>min: 8 tokens</li><li>mean: 27.46 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 27.36 tokens</li><li>max: 52 tokens</li></ul> | <ul><li>0: ~50.30%</li><li>1: ~49.70%</li></ul> |
* Samples:
  | sentence1                                                                                                                                   | sentence2                                                                                                                                     | label          |
  |:--------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------|:---------------|
  | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code>                        | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code>                           | <code>1</code> |
  | <code>Turner Valley , was at the Turner Valley Bar N Ranch Airport , southwest of the Turner Valley Bar N Ranch , Alberta , Canada .</code> | <code>Turner Valley Bar N Ranch Airport , , was located at Turner Valley Bar N Ranch , southwest of Turner Valley , Alberta , Canada .</code> | <code>0</code> |
  | <code>After losing his second election , he resigned as opposition leader and was replaced by Geoff Pearsall .</code>                       | <code>Max Bingham resigned as opposition leader after losing his second election , and was replaced by Geoff Pearsall .</code>                | <code>1</code> |
* Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:
  ```json
  {
      "scale": 20.0,
      "similarity_fct": "pairwise_cos_sim"
  }
  ```

### Evaluation Dataset

#### LangCache Sentence Pairs (all)

* Dataset: [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/aditeyabaral-redis/langcache-sentencepairs-v1)
* Size: 62,021 evaluation samples
* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>label</code>
* Approximate statistics based on the first 1000 samples:
  |         | sentence1                                                                         | sentence2                                                                         | label                                           |
  |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:------------------------------------------------|
  | type    | string                                                                            | string                                                                            | int                                             |
  | details | <ul><li>min: 8 tokens</li><li>mean: 27.46 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 27.36 tokens</li><li>max: 52 tokens</li></ul> | <ul><li>0: ~50.30%</li><li>1: ~49.70%</li></ul> |
* Samples:
  | sentence1                                                                                                                                   | sentence2                                                                                                                                     | label          |
  |:--------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------|:---------------|
  | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code>                        | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code>                           | <code>1</code> |
  | <code>Turner Valley , was at the Turner Valley Bar N Ranch Airport , southwest of the Turner Valley Bar N Ranch , Alberta , Canada .</code> | <code>Turner Valley Bar N Ranch Airport , , was located at Turner Valley Bar N Ranch , southwest of Turner Valley , Alberta , Canada .</code> | <code>0</code> |
  | <code>After losing his second election , he resigned as opposition leader and was replaced by Geoff Pearsall .</code>                       | <code>Max Bingham resigned as opposition leader after losing his second election , and was replaced by Geoff Pearsall .</code>                | <code>1</code> |
* Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:
  ```json
  {
      "scale": 20.0,
      "similarity_fct": "pairwise_cos_sim"
  }
  ```

### Training Logs
| Epoch | Step | val_cosine_ap | test_cosine_ap |
|:-----:|:----:|:-------------:|:--------------:|
| -1    | -1   | 0.7351        | 0.6474         |


### Framework Versions
- Python: 3.12.3
- Sentence Transformers: 5.1.0
- Transformers: 4.55.0
- PyTorch: 2.8.0+cu128
- Accelerate: 1.10.0
- Datasets: 4.0.0
- Tokenizers: 0.21.4

## 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",
}
```

#### CoSENTLoss
```bibtex
@online{kexuefm-8847,
    title={CoSENT: A more efficient sentence vector scheme than Sentence-BERT},
    author={Su Jianlin},
    year={2022},
    month={Jan},
    url={https://kexue.fm/archives/8847},
}
```

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