Conan-embedding-v1
Performance
Model | Average | CLS | Clustering | Reranking | Retrieval | STS | Pair_CLS |
---|---|---|---|---|---|---|---|
gte-Qwen2-7B-instruct | 72.05 | 75.09 | 66.06 | 68.92 | 76.03 | 65.33 | 87.48 |
xiaobu-embedding-v2 | 72.43 | 74.67 | 65.17 | 72.58 | 76.5 | 64.53 | 91.87 |
Conan-embedding-v1 | 72.62 | 75.03 | 66.33 | 72.76 | 76.67 | 64.18 | 91.66 |
Methods and Training Detials
Please refer to our technical report.
Citation
If you find our models / papers useful in your research, please consider giving ❤️ and citations. Thanks!
@misc{li2024conanembeddinggeneraltextembedding,
title={Conan-embedding: General Text Embedding with More and Better Negative Samples},
author={Shiyu Li and Yang Tang and Shizhe Chen and Xi Chen},
year={2024},
eprint={2408.15710},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2408.15710},
}
About
Created by the Tencent BAC Group. All rights reserved.
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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Evaluation results
- cos_sim_pearson on MTEB AFQMCvalidation set self-reported56.614
- cos_sim_spearman on MTEB AFQMCvalidation set self-reported60.664
- euclidean_pearson on MTEB AFQMCvalidation set self-reported58.421
- euclidean_spearman on MTEB AFQMCvalidation set self-reported59.828
- manhattan_pearson on MTEB AFQMCvalidation set self-reported58.399
- manhattan_spearman on MTEB AFQMCvalidation set self-reported59.818
- cos_sim_pearson on MTEB ATECtest set self-reported56.605
- cos_sim_spearman on MTEB ATECtest set self-reported58.638
- euclidean_pearson on MTEB ATECtest set self-reported62.186
- euclidean_spearman on MTEB ATECtest set self-reported58.232