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---
pipeline_tag: sentence-similarity
tags:
- finetuner
- sentence-transformers
- feature-extraction
- sentence-similarity
datasets:
- jinaai/negation-dataset
language: en
license: apache-2.0
---
<br><br>
<p align="center">
<img src="https://github.com/jina-ai/finetuner/blob/main/docs/_static/finetuner-logo-ani.svg?raw=true" alt="Finetuner logo: Finetuner helps you to create experiments in order to improve embeddings on search tasks. It accompanies you to deliver the last mile of performance-tuning for neural search applications." width="150px">
</p>
<p align="center">
<b>The text embedding set trained by Jina AI, Finetuner team.</b>
</p>
## Intented Usage & Model Info
`jina-embedding-t-en-v1` is a language model that has been trained using Jina AI's Linnaeus-Clean dataset.
This dataset consists of 380 million pairs of sentences, which include both query-document pairs.
These pairs were obtained from various domains and were carefully selected through a thorough cleaning process.
The Linnaeus-Full dataset, from which the Linnaeus-Clean dataset is derived, originally contained 1.6 billion sentence pairs.
The model has a range of use cases, including information retrieval, semantic textual similarity, text reranking, and more.
With a compact size of just 14 million parameters,
the model enables lightning-fast inference while still delivering impressive performance.
Additionally, we provide the following options:
- `jina-embedding-t-en-v1`: 14 million parameters **(you are here)**.
- `jina-embedding-s-en-v1`: 35 million parameters.
- `jina-embedding-b-en-v1`: 110 million parameters.
- `jina-embedding-l-en-v1`: 330 million parameters.
- `jina-embedding-1b-en-v1`: 1.2 billion parameters, 10* bert-base size (soon).
- `jina-embedding-6b-en-v1`: 6 billion parameters 30* bert-base size(soon).
## Data & Parameters
More info will be released together with the technique report.
## Metrics
We compared the model against `all-minilm-l6-v2`/`all-mpnet-base-v2` from sbert and `text-embeddings-ada-002` from OpenAI:
|Name|param |dimension|
|------------------------------|-----|------|
|all-minilm-l6-v2|33m |384|
|all-mpnet-base-v2 |110m |768|
|ada-embedding-002|Unknown/OpenAI API |8192|
|jina-embedding-t-en-v1|14m |312|
|jina-embedding-s-en-v1|35m |512|
|jina-embedding-b-en-v1|110m |768|
|jina-embedding-l-en-v1|330m |1024|
|Name|STS12|STS13|STS14|STS15|STS16|STS17|TRECOVID|Quora|SciFact|
|------------------------------|-----|-----|-----|-----|-----|-----|--------|-----|-----|
|all-minilm-l6-v2|0.724|0.806|0.756|0.854|0.79 |0.876|0.473 |0.876|0.645 |
|all-mpnet-base-v2|0.726|0.835|**0.78** |0.857|0.8 |**0.906**|0.513 |0.875|0.656 |
|ada-embedding-002|0.698|0.833|0.761|0.861|**0.86** |0.903|**0.685** |0.876|**0.726** |
|jina-embedding-t-en-v1|0.714|0.775|0.723|0.825|0.771|0.863|0.479 |0.841|0.542 |
|jina-embedding-s-en-v1|**0.743**|0.786|0.738|0.837|0.80|0.875|0.523 |0.857|0.524 |
|jina-embedding-b-en-v1|0.735|0.792|0.752|0.851|0.801|0.89|0.546 |0.871|0.586 |
|jina-embedding-l-en-v1|0.739|**0.844**|0.778|**0.863**|0.821|0.896|0.566 |**0.882**|0.608 |
## Usage
Use with Jina AI Finetuner
```python
!pip install finetuner
import finetuner
model = finetuner.build_model('jinaai/jina-embedding-t-en-v1')
embeddings = finetuner.encode(
model=model,
data=['how is the weather today', 'What is the current weather like today?']
)
print(finetuner.cos_sim(embeddings[0], embeddings[1]))
```
Use directly with sentence-transformers:
```python
from sentence_transformers import SentenceTransformer
from sentence_transformers.util import cos_sim
sentences = ['how is the weather today', 'What is the current weather like today?']
model = SentenceTransformer('jinaai/jina-embedding-t-en-v1')
embeddings = model.encode(sentences)
print(cos_sim(embeddings[0], embeddings[1]))
```
## Fine-tuning
Please consider [Finetuner](https://github.com/jina-ai/finetuner).
## Plans
1. The development of `jina-embedding-s-en-v2` is currently underway with two main objectives: improving performance and increasing the maximum sequence length.
2. We are currently working on a bilingual embedding model that combines English and X language. The upcoming model will be called `jina-embedding-s/b/l-de-v1`.
## Contact
Join our [Discord community](https://discord.jina.ai) and chat with other community members about ideas. |