# Model Card for SynCSE-scratch  
 
# Model Details
 
## Model Description
 
More information needed
 
- **Developed by:** SJTU-LIT
- **Shared by [Optional]:** SJTU-LIT

- **Model type:** Feature Extraction
- **Language(s) (NLP):** More information needed
- **License:** More information needed
- **Parent Model:** RoBERTa-base
- **Resources for more information:**
 	 - [GitHub Repo](https://github.com/SJTU-LIT/SynCSE/tree/main)
 	 - [Associated Paper](https://arxiv.org/abs/2305.15077)


# Uses
 

## Direct Use
This model can be used for the task of feature extraction. 
 
## Out-of-Scope Use
 
The model should not be used to intentionally create hostile or alienating environments for people. 
 
# Bias, Risks, and Limitations
 
Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
## Recommendations
 
 
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.


 
# Training Data
 
  The model craters note in the [Github Repository](https://github.com/SJTU-LIT/SynCSE/blob/main/README.md)
> We use 27.5k generated synthetic train SynCSE-sractch-RoBERTa-base.
 
# Citation

 
**BibTeX:**

```bibtex
@article{zhang2023contrastive,
  title={Contrastive Learning of Sentence Embeddings from Scratch},
  author={Zhang, Junlei and Lan, Zhenzhong and He, Junxian},
  journal={arXiv preprint arXiv:2305.15077},
  year={2023}
}
```

# Model Card Contact
 
If you have any questions related to the code or the paper, feel free to email Junlei (`zhangjunlei@westlake.edu.cn`). If you encounter any problems when using the code, or want to report a bug, you can open an issue. Please try to specify the problem with details so we can help you better and quicker!


 
# How to Get Started with the Model
 
Use the code below to get started with the model.
 
<details>
<summary> Click to expand </summary>

```python
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("sjtu-lit/SynCSE-partial-RoBERTa-base")
model = AutoModel.from_pretrained("sjtu-lit/SynCSE-partial-RoBERTa-base")
 
 ```
</details>
{"language": ["en"], "tags": ["pytorch", "RoBERTa"], "pipeline_tag": "feature-extraction"}
transformers pytorch roberta feature-extraction RoBERTa en arxiv:2305.15077 endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #feature-extraction #RoBERTa #en #arxiv-2305.15077 #endpoints_compatible #region-us 

# Model Card for SynCSE-scratch  
 
# Model Details
 
## Model Description
 
More information needed
 
- Developed by: SJTU-LIT
- Shared by [Optional]: SJTU-LIT

- Model type: Feature Extraction
- Language(s) (NLP): More information needed
- License: More information needed
- Parent Model: RoBERTa-base
- Resources for more information:
 	 - GitHub Repo
 	 - Associated Paper


# Uses
 

## Direct Use
This model can be used for the task of feature extraction. 
 
## Out-of-Scope Use
 
The model should not be used to intentionally create hostile or alienating environments for people. 
 
# Bias, Risks, and Limitations
 
Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
## Recommendations
 
 
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.


 
# Training Data
 
  The model craters note in the Github Repository
> We use 27.5k generated synthetic train SynCSE-sractch-RoBERTa-base.
 
BibTeX:



# Model Card Contact
 
If you have any questions related to the code or the paper, feel free to email Junlei ('zhangjunlei@URL'). If you encounter any problems when using the code, or want to report a bug, you can open an issue. Please try to specify the problem with details so we can help you better and quicker!


 
# How to Get Started with the Model
 
Use the code below to get started with the model.
 
<details>
<summary> Click to expand </summary>


</details>
# Model Card for SynCSE-scratch # Model Details ## Model Description
 
More information needed
 
- Developed by: SJTU-LIT
- Shared by [Optional]: SJTU-LIT

- Model type: Feature Extraction
- Language(s) (NLP): More information needed
- License: More information needed
- Parent Model: RoBERTa-base
- Resources for more information:
 	 - GitHub Repo
 	 - Associated Paper # Uses ## Direct Use
This model can be used for the task of feature extraction. ## Out-of-Scope Use
 
The model should not be used to intentionally create hostile or alienating environments for people. # Bias, Risks, and Limitations
 
Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. ## Recommendations
 
 
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. # Training Data
 
  The model craters note in the Github Repository
> We use 27.5k generated synthetic train SynCSE-sractch-RoBERTa-base.
 
BibTeX: # Model Card Contact
 
If you have any questions related to the code or the paper, feel free to email Junlei ('zhangjunlei@URL'). If you encounter any problems when using the code, or want to report a bug, you can open an issue. Please try to specify the problem with details so we can help you better and quicker! # How to Get Started with the Model
 
Use the code below to get started with the model.
 
<details>
<summary> Click to expand </summary>


</details>
TAGS
#transformers #pytorch #roberta #feature-extraction #RoBERTa #en #arxiv-2305.15077 #endpoints_compatible #region-us 
 # Model Card for SynCSE-scratch # Model Details ## Model Description
 
More information needed
 
- Developed by: SJTU-LIT
- Shared by [Optional]: SJTU-LIT

- Model type: Feature Extraction
- Language(s) (NLP): More information needed
- License: More information needed
- Parent Model: RoBERTa-base
- Resources for more information:
 	 - GitHub Repo
 	 - Associated Paper # Uses ## Direct Use
This model can be used for the task of feature extraction. ## Out-of-Scope Use
 
The model should not be used to intentionally create hostile or alienating environments for people. # Bias, Risks, and Limitations
 
Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. ## Recommendations
 
 
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. # Training Data
 
  The model craters note in the Github Repository
> We use 27.5k generated synthetic train SynCSE-sractch-RoBERTa-base.
 
BibTeX: # Model Card Contact
 
If you have any questions related to the code or the paper, feel free to email Junlei ('zhangjunlei@URL'). If you encounter any problems when using the code, or want to report a bug, you can open an issue. Please try to specify the problem with details so we can help you better and quicker! # How to Get Started with the Model
 
Use the code below to get started with the model.
 
<details>
<summary> Click to expand </summary>


</details>