{
    "model_card": {
        "Date & Time": "2025-03-06T21:12:29.381066",
        "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",
    "req_versions": {
        "dill": "0.3.8",
        "sqlitedict": "2.1.0",
        "torch": "2.5.1",
        "numpy": "1.26.4",
        "transformers": "4.48.2",
        "datasets": "3.2.0",
        "huggingface_hub": "0.27.1",
        "accelerate": "1.3.0",
        "peft": "0.14.0",
        "tiktoken": "0.7.0",
        "tokenizers": "0.21.0",
        "openai": "1.59.8",
        "ctransformers": "0.2.27",
        "optimum": "1.23.3",
        "bitsandbytes": "0.45.0",
        "litellm": "1.57.8",
        "trl": "0.9.6",
        "setfit": "1.1.1",
        "vllm": "0.7.0"
    },
    "interpreter": "3.11.1 (main, Apr 12 2023, 13:34:00) [GCC 7.5.0]"
}