langcache-embed-v3 / README.md
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---
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:9233417
- loss:ArcFaceInBatchLoss
base_model: answerdotai/ModernBERT-base
widget:
- source_sentence: Hayley Vaughan portrayed Ripa on the ABC daytime soap opera , ``
All My Children `` , between 1990 and 2002 .
sentences:
- Traxxpad is a music application for Sony 's PlayStation Portable published by
Definitive Studios and developed by Eidos Interactive .
- Between 1990 and 2002 , Hayley Vaughan Ripa portrayed in the ABC soap opera ``
All My Children `` .
- Between 1990 and 2002 , Ripa Hayley portrayed Vaughan in the ABC soap opera ``
All My Children `` .
- source_sentence: Olivella monilifera is a species of dwarf sea snail , small gastropod
mollusk in the family Olivellidae , the marine olives .
sentences:
- Olivella monilifera is a species of the dwarf - sea snail , small gastropod mollusk
in the Olivellidae family , the marine olives .
- He was cut by the Browns after being signed by the Bills in 2013 . He was later
released .
- Olivella monilifera is a kind of sea snail , marine gastropod mollusk in the Olivellidae
family , the dwarf olives .
- source_sentence: Hayashi said that Mackey `` is a sort of `` of the original model
for Tenchi .
sentences:
- In the summer of 2009 , Ellick shot a documentary about Malala Yousafzai .
- Hayashi said that Mackey is `` sort of `` the original model for Tenchi .
- Mackey said that Hayashi is `` sort of `` the original model for Tenchi .
- source_sentence: Much of the film was shot on location in Los Angeles and in nearby
Burbank and Glendale .
sentences:
- Much of the film was shot on location in Los Angeles and in nearby Burbank and
Glendale .
- Much of the film was shot on site in Burbank and Glendale and in the nearby Los
Angeles .
- Traxxpad is a music application for the Sony PlayStation Portable developed by
the Definitive Studios and published by Eidos Interactive .
- source_sentence: According to him , the earth is the carrier of his artistic work
, which is only integrated into the creative process by minimal changes .
sentences:
- National players are Bold players .
- According to him , earth is the carrier of his artistic work being integrated
into the creative process only by minimal changes .
- According to him , earth is the carrier of his creative work being integrated
into the artistic process only by minimal changes .
datasets:
- redis/langcache-sentencepairs-v2
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
- cosine_accuracy@1
- cosine_precision@1
- cosine_recall@1
- cosine_ndcg@10
- cosine_mrr@1
- cosine_map@100
model-index:
- name: Redis fine-tuned BiEncoder model for semantic caching on LangCache
results:
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: test
type: test
metrics:
- type: cosine_accuracy@1
value: 0.4126938643934238
name: Cosine Accuracy@1
- type: cosine_precision@1
value: 0.4126938643934238
name: Cosine Precision@1
- type: cosine_recall@1
value: 0.39900881466078997
name: Cosine Recall@1
- type: cosine_ndcg@10
value: 0.5950456720106155
name: Cosine Ndcg@10
- type: cosine_mrr@1
value: 0.4126938643934238
name: Cosine Mrr@1
- type: cosine_map@100
value: 0.543168962594735
name: Cosine Map@100
---
# Redis fine-tuned BiEncoder model for semantic caching on LangCache
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2) 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:** [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) <!-- at revision 8949b909ec900327062f0ebf497f51aef5e6f0c8 -->
- **Maximum Sequence Length:** 100 tokens
- **Output Dimensionality:** 768 dimensions
- **Similarity Function:** Cosine Similarity
- **Training Dataset:**
- [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2)
- **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': 100, 'do_lower_case': False, 'architecture': 'ModernBertModel'})
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, '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("redis/langcache-embed-v3")
# Run inference
sentences = [
'According to him , the earth is the carrier of his artistic work , which is only integrated into the creative process by minimal changes .',
'According to him , earth is the carrier of his artistic work being integrated into the creative process only by minimal changes .',
'According to him , earth is the carrier of his creative work being integrated into the artistic process only by minimal changes .',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities)
# tensor([[0.9961, 0.9922, 0.9922],
# [0.9922, 1.0000, 1.0000],
# [0.9922, 1.0000, 1.0000]], dtype=torch.bfloat16)
```
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## Evaluation
### Metrics
#### Information Retrieval
* Dataset: `test`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:-------------------|:----------|
| cosine_accuracy@1 | 0.4127 |
| cosine_precision@1 | 0.4127 |
| cosine_recall@1 | 0.399 |
| **cosine_ndcg@10** | **0.595** |
| cosine_mrr@1 | 0.4127 |
| cosine_map@100 | 0.5432 |
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## Training Details
### Training Dataset
#### LangCache Sentence Pairs (all)
* Dataset: [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2)
* Size: 126,938 training samples
* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
* Approximate statistics based on the first 1000 samples:
| | anchor | positive | negative |
|:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
| type | string | string | string |
| details | <ul><li>min: 8 tokens</li><li>mean: 27.27 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 27.27 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 26.54 tokens</li><li>max: 61 tokens</li></ul> |
* Samples:
| anchor | positive | negative |
|:--------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------|
| <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>how can I get financial freedom as soon as possible?</code> |
| <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code> | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code> | <code>The older Punts are still very much in existence today and race in the same fleets as the newer boats .</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 , , was located at Turner Valley Bar N Ranch Airport , southwest of 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> |
* Loss: <code>losses.ArcFaceInBatchLoss</code> with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "cos_sim",
"gather_across_devices": false
}
```
### Evaluation Dataset
#### LangCache Sentence Pairs (all)
* Dataset: [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2)
* Size: 126,938 evaluation samples
* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
* Approximate statistics based on the first 1000 samples:
| | anchor | positive | negative |
|:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
| type | string | string | string |
| details | <ul><li>min: 8 tokens</li><li>mean: 27.27 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 27.27 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 26.54 tokens</li><li>max: 61 tokens</li></ul> |
* Samples:
| anchor | positive | negative |
|:--------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------|
| <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>how can I get financial freedom as soon as possible?</code> |
| <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code> | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code> | <code>The older Punts are still very much in existence today and race in the same fleets as the newer boats .</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 , , was located at Turner Valley Bar N Ranch Airport , southwest of 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> |
* Loss: <code>losses.ArcFaceInBatchLoss</code> with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "cos_sim",
"gather_across_devices": false
}
```
### Training Logs
| Epoch | Step | test_cosine_ndcg@10 |
|:-----:|:----:|:-------------------:|
| -1 | -1 | 0.5950 |
### Framework Versions
- Python: 3.12.3
- Sentence Transformers: 5.1.0
- Transformers: 4.56.0
- PyTorch: 2.8.0+cu128
- Accelerate: 1.10.1
- Datasets: 4.0.0
- Tokenizers: 0.22.0
## 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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