{
    "model_card": {
        "Date & Time": "2024-12-05T09:20:42.556129",
        "Model Card": [
            "https://huggingface.co/FacebookAI/xlm-roberta-base"
        ],
        "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",
            "@article{DBLP:journals/corr/abs-1911-02116,\n  author    = {Alexis Conneau and\n               Kartikay Khandelwal and\n               Naman Goyal and\n               Vishrav Chaudhary and\n               Guillaume Wenzek and\n               Francisco Guzm{\\'{a}}n and\n               Edouard Grave and\n               Myle Ott and\n               Luke Zettlemoyer and\n               Veselin Stoyanov},\n  title     = {Unsupervised Cross-lingual Representation Learning at Scale},\n  journal   = {CoRR},\n  volume    = {abs/1911.02116},\n  year      = {2019},\n  url       = {http://arxiv.org/abs/1911.02116},\n  eprinttype = {arXiv},\n  eprint    = {1911.02116},\n  timestamp = {Mon, 11 Nov 2019 18:38:09 +0100},\n  biburl    = {https://dblp.org/rec/journals/corr/abs-1911-02116.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\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 SynthSTEL Training Triplets Dataset": {
            "Date & Time": "2024-11-20T18:38:17.601393",
            "Dataset Name": [
                "StyleDistance/mstyledistance_training_triplets"
            ],
            "Dataset Card": [
                "https://huggingface.co/datasets/StyleDistance/mstyledistance_training_triplets"
            ]
        },
        "Get SynthSTEL Training Triplets Dataset (train split)": {
            "Date & Time": "2024-11-20T18:57:23.493502"
        },
        "Get SynthSTEL Training Triplets Dataset (train split) (shuffle)": {
            "Date & Time": "2024-11-30T22:23:37.582505"
        }
    },
    "__version__": "0.35.0",
    "datetime": "2024-11-30T22:23:38.698076",
    "type": "TrainSentenceTransformer",
    "name": "Train StyleDistance Model",
    "version": 1.0,
    "fingerprint": "d175c760f39a5f90",
    "req_versions": {
        "dill": "0.3.8",
        "sqlitedict": "2.1.0",
        "torch": "2.3.1",
        "numpy": "1.26.4",
        "transformers": "4.40.1",
        "datasets": "2.17.0",
        "huggingface_hub": "0.23.4",
        "accelerate": "0.32.1",
        "peft": "0.11.1",
        "tiktoken": "0.7.0",
        "tokenizers": "0.19.1",
        "openai": "1.35.13",
        "ctransformers": "0.2.27",
        "optimum": "1.21.2",
        "bitsandbytes": "0.43.1",
        "litellm": "1.31.14",
        "trl": "0.8.1",
        "setfit": "1.0.3"
    },
    "interpreter": "3.10.9 (main, Apr 17 2023, 21:32:03) [GCC 7.5.0]"
}