|
{ |
|
"model_card": { |
|
"Date & Time": "2025-03-06T21:12:29.381066", |
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"Model Card": [ |
|
"https://huggingface.co/BAAI/bge-m3" |
|
], |
|
"License Information": [ |
|
"mit" |
|
], |
|
"Citation Information": [ |
|
"\n@inproceedings{Wolf_Transformers_State-of-the-Art_Natural_2020,\n author = {Wolf, Thomas and Debut, Lysandre and Sanh, Victor and Chaumond, Julien", |
|
"\n@Misc{peft,\n title = {PEFT: State-of-the-art Parameter-Efficient Fine-Tuning methods},\n author = {Sourab Mangrulkar and Sylvain Gugger and Lysandre Debut and Younes", |
|
"@misc{bge-m3,\n title={BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation}, \n author={Jianlv Chen and Shitao Xiao and Peitian Zhang and Kun Luo and Defu Lian and Zheng Liu},\n year={2024},\n eprint={2402.03216},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}", |
|
"@inproceedings{reimers-2019-sentence-bert,\n title = \"Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks\",\n author = \"Reimers, Nils and Gurevych, Iryna\",\n booktitle = \"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing\",\n month = \"11\",\n year = \"2019\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://arxiv.org/abs/1908.10084\",\n}" |
|
] |
|
}, |
|
"data_card": { |
|
"Get Matching Calibration": { |
|
"Date & Time": "2025-03-05T12:33:06.921999", |
|
"Dataset Name": [ |
|
"fineinstructions/matching_calibration" |
|
], |
|
"Dataset Card": [ |
|
"https://huggingface.co/datasets/fineinstructions/matching_calibration" |
|
] |
|
}, |
|
"Adjust sims for hard positives and negatives": { |
|
"Date & Time": "2025-03-05T12:35:51.663481" |
|
}, |
|
"Filter out too long rows": { |
|
"Date & Time": "2025-03-05T12:37:19.256235" |
|
}, |
|
"Filter out too long rows (train split)": { |
|
"Date & Time": "2025-03-05T12:40:43.387535" |
|
} |
|
}, |
|
"__version__": "0.46.0", |
|
"datetime": "2025-03-06T20:29:33.338084", |
|
"type": "TrainSentenceTransformer", |
|
"name": "Train Matching Embedding", |
|
"version": 1.0, |
|
"fingerprint": "66bfe8a08b39004c", |
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"req_versions": { |
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"dill": "0.3.8", |
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"sqlitedict": "2.1.0", |
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"torch": "2.5.1", |
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"numpy": "1.26.4", |
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"transformers": "4.48.2", |
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"datasets": "3.2.0", |
|
"huggingface_hub": "0.27.1", |
|
"accelerate": "1.3.0", |
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"peft": "0.14.0", |
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"tiktoken": "0.7.0", |
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"tokenizers": "0.21.0", |
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"openai": "1.59.8", |
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"ctransformers": "0.2.27", |
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"optimum": "1.23.3", |
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"bitsandbytes": "0.45.0", |
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"litellm": "1.57.8", |
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"trl": "0.9.6", |
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"setfit": "1.1.1", |
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"vllm": "0.7.0" |
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}, |
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"interpreter": "3.11.1 (main, Apr 12 2023, 13:34:00) [GCC 7.5.0]" |
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} |