README.md

---
language:
- ja
library_name: sentence-transformers
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
base_model: cl-nagoya/ruri-pt-large
widget: []
pipeline_tag: sentence-similarity
license: apache-2.0
---

# Ruri: Japanese General Text Embeddings


## 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
import torch.nn.functional as F
from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("cl-nagoya/ruri-large")

sentences = [
    'The weather is lovely today.',
    "It's so sunny outside!",
    'He drove to the stadium.',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]

similarities = F.cosine_similarity(embeddings.unsqueeze(0), embeddings.unsqueeze(1))
print(similarities.shape)
# [3, 3]
```

## Benchmarks

### JMTEB
Evaluated with [JMTEB](https://github.com/sbintuitions/JMTEB).

|Model|#Param.|Retrieval|STS|Classfification|Reranking|Clustering|PairClassification|Avg.|
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
|[cl-nagoya/sup-simcse-ja-base](https://huggingface.co/cl-nagoya/sup-simcse-ja-base)|111M|49.64|82.05|73.47|91.83|51.79|62.57|68.56|
|[cl-nagoya/sup-simcse-ja-large](https://huggingface.co/cl-nagoya/sup-simcse-ja-large)|337M|37.62|83.18|73.73|91.48|50.56|62.51|66.51|
|[cl-nagoya/unsup-simcse-ja-base](https://huggingface.co/cl-nagoya/unsup-simcse-ja-base)|111M|40.23|78.72|73.07|91.16|44.77|62.44|65.07|
|[cl-nagoya/unsup-simcse-ja-large](https://huggingface.co/cl-nagoya/unsup-simcse-ja-large)|337M|40.53|80.56|74.66|90.95|48.41|62.49|66.27|
|[pkshatech/GLuCoSE-base-ja](https://huggingface.co/pkshatech/GLuCoSE-base-ja)|133M|59.02|78.71|76.82|91.90|49.78|66.39|70.44|
||||||||||
|[sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE)|472M|40.12|76.56|72.66|91.63|44.88|62.33|64.70|
|[intfloat/multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small)|118M|67.27|80.07|67.62|93.03|46.91|62.19|69.52|
|[intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base)|278M|68.21|79.84|69.30|92.85|48.26|62.26|70.12|
|[intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large)|560M|70.98|79.70|72.89|92.96|51.24|62.15|71.65|
||||||||||
|OpenAI/text-embedding-ada-002|-|64.38|79.02|69.75|93.04|48.30|62.40|69.48|
|OpenAI/text-embedding-3-small|-|66.39|79.46|73.06|92.92|51.06|62.27|70.86|
|OpenAI/text-embedding-3-large|-|74.48|82.52|77.58|93.58|53.32|62.35|73.97|
||||||||||
|[Ruri-Small](https://huggingface.co/cl-nagoya/ruri-small)|68M|69.41|82.79|76.22|93.00|51.19|62.11|71.53|
|[Ruri-Base](https://huggingface.co/cl-nagoya/ruri-base)|111M|69.82|82.87|75.58|92.91|54.16|62.38|71.91|
|[Ruri-Large](https://huggingface.co/cl-nagoya/ruri-large)|337M|73.02|83.13|77.43|92.99|51.82|62.29|73.31|



## Model Details

### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [cl-nagoya/ruri-large-pt](https://huggingface.co/cl-nagoya/ruri-large-pt) 
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 1024
- **Similarity Function:** Cosine Similarity
- **Language:** Japanese
- **License:** Apache 2.0
<!-- - **Training Dataset:** Unknown -->

### 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

```
MySentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 1024, '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})
)
```


## Training Details


### Framework Versions
- Python: 3.10.13
- Sentence Transformers: 3.0.0
- Transformers: 4.41.2
- PyTorch: 2.3.1+cu118
- Accelerate: 0.30.1
- Datasets: 2.19.1
- Tokenizers: 0.19.1

<!-- ## Citation

### BibTeX
 -->

## License
This model is published under the [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).