Update README.md

README.md

@@ -373,9 +373,6 @@ You can finetune this model on your own dataset.
 | 12.3967 | 1500 | 2.1294        | 0.6463              |
 
 
-### Training Time
-- **Training**: 2.4 minutes
-
 ### Framework Versions
 - Python: 3.13.15
 - Sentence Transformers: 5.7.0
@@ -385,42 +382,6 @@ You can finetune this model on your own dataset.
 - Datasets: 4.8.5
 - Tokenizers: 0.23.1
 
-## Additional Resources
-
-- [Training and Finetuning Embedding Models with Sentence Transformers](https://huggingface.co/blog/train-sentence-transformers): the end-to-end guide for training or finetuning Sentence Transformer models.
-- [Introduction to Matryoshka Embedding Models](https://huggingface.co/blog/matryoshka): variable-size embeddings that can be truncated with minimal quality loss.
-- [Binary and Scalar Embedding Quantization for Significantly Faster & Cheaper Retrieval](https://huggingface.co/blog/embedding-quantization): post-training compression of embedding vectors.
-- [Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/multimodal-sentence-transformers): use text, image, audio, and video models through the same API.
-- [Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/train-multimodal-sentence-transformers): train multimodal embedding models, with a Visual Document Retrieval walkthrough.
-
-## 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{oord2019representationlearningcontrastivepredictive,
-      title={Representation Learning with Contrastive Predictive Coding},
-      author={Aaron van den Oord and Yazhe Li and Oriol Vinyals},
-      year={2019},
-      eprint={1807.03748},
-      archivePrefix={arXiv},
-      primaryClass={cs.LG},
-      url={https://arxiv.org/abs/1807.03748},
-}
 ```
 
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