Update README.md

README.md

@@ -66,11 +66,6 @@ This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [s
 <!-- - **Language:** Unknown -->
 <!-- - **License:** 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
 
@@ -157,26 +152,6 @@ You can finetune this model on your own dataset.
 #### Unnamed Dataset
 
 
-* Size: 46,453 training samples
-* Columns: <code>sentence_0</code> and <code>sentence_1</code>
-* Approximate statistics based on the first 1000 samples:
-  |         | sentence_0                                                                       | sentence_1                                                                         |
-  |:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
-  | type    | string                                                                           | string                                                                             |
-  | details | <ul><li>min: 3 tokens</li><li>mean: 6.64 tokens</li><li>max: 11 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 23.81 tokens</li><li>max: 384 tokens</li></ul> |
-* Samples:
-  | sentence_0                          | sentence_1                                                                                                                                                                                                                                                         |
-  |:------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-  | <code>has been homeless</code>      | <code>He has a GED level education and previously held a stable job for a ___. However, mother reports he recently quit his job suddenly and is homeless right now after multiple family members kicked him out of their homes.</code>                             |
-  | <code>gave list of shelters</code>  | <code>Home With Service Facility:</code>                                                                                                                                                                                                                           |
-  | <code>assessed housing needs</code> | <code>Patient with longstanding history of instrumental suicidal ideation and waxing and waning symptoms of depression and anxiety, SI when his needs, particularly regarding housing, are not being met with documented history of quick retraction of his</code> |
-* Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
-  ```json
-  {
-      "scale": 20.0,
-      "similarity_fct": "cos_sim"
-  }
-  ```
 
 ### Training Hyperparameters
 #### Non-Default Hyperparameters
@@ -476,49 +451,4 @@ You can finetune this model on your own dataset.
 - Datasets: 2.19.1
 - Tokenizers: 0.19.1
 
-## 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",
-}
-```
-
-#### MultipleNegativesRankingLoss
-```bibtex
-@misc{henderson2017efficient,
-    title={Efficient Natural Language Response Suggestion for Smart Reply}, 
-    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
-    year={2017},
-    eprint={1705.00652},
-    archivePrefix={arXiv},
-    primaryClass={cs.CL}
-}
-```
-
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