{
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    "similarity": "cosine",
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    "kd_loss": "KLD",
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    "model_name": "xlm-roberta-large",
    "force_resize_embeddings": true,
    "shuffle_passages": true,
    "sampling_max_beta": 1.0,
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    "query_maxlen": 32,
    "attend_to_mask_tokens": false,
    "interaction": "colbert",
    "dim": 128,
    "doc_maxlen": 220,
    "mask_punctuation": true,
    "checkpoint": "xlm-roberta-large",
    "triples": "\/expscratch\/eyang\/workspace\/plaid-aux\/training_triples\/msmarco-passages\/triples_mt5xxl-monot5-mmarco-engeng.jsonl",
    "collection": null,
    "queries": null,
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    "overwrite": false,
    "root": "\/expscratch\/eyang\/workspace\/plaid-aux\/experiments",
    "experiment": "plaid_xlm-roberta-large_fixeddp",
    "index_root": null,
    "name": "zho-KLD-shuf-5e-6\/mt5xxl-monot5-mmarco-engeng\/64bat.6way",
    "rank": 0,
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    "amp": true,
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    "gpus": 8,
    "meta": {
        "hostname": "r10n01",
        "git_branch": "eugene-training",
        "git_hash": "220bdf8155f0615e1bb2d997d8efe924ffe806b5",
        "git_commit_datetime": "2023-09-29 16:36:59-04:00",
        "current_datetime": "Oct 03, 2023 ;  9:41PM EDT (-0400)",
        "cmd": "train.py --model_name xlm-roberta-large --training_triples \/expscratch\/eyang\/workspace\/plaid-aux\/training_triples\/msmarco-passages\/triples_mt5xxl-monot5-mmarco-engeng.jsonl --training_irds_id neumarco\/zh\/train --maxsteps 200000 --learning_rate 5e-6 --kd_loss KLD --per_device_batch_size 8 --nway 6 --run_tag zho-KLD-shuf-5e-6\/mt5xxl-monot5-mmarco-engeng --experiment plaid_xlm-roberta-large_fixeddp",
        "version": "colbert-v0.4"
    }
}