csc.config

{
    "CUDA_VISIBLE_DEVICES": "0",
    "USE_TORCH": "1",
    "output_hidden_states": null,
    "pretrained_model_name_or_path": "hfl/chinese-macbert-base",
    "model_save_path": "../output/text_correction/model_public_csc",
    "config_name": "csc.config",
    "model_name": "pytorch_model.bin",
    "path_train": "csc_public.train.json",
    "path_dev": "csc_public.dev.json",
    "path_tet": "csc_public.tet.json",
    "scheduler_name": "cosine",
    "tokenizer_type": "CHAR",
    "padding_side": "RIGHT",
    "active_type": "RELU",
    "task_type": "CSC",
    "model_type": "BERT",
    "loss_type": "BCE",
    "loss_det_rate": 0.3,
    "max_len_limit": 512,
    "batch_size": 32,
    "num_labels": 0,
    "max_len": 128,
    "epochs": 3,
    "lr": 3e-05,
    "grad_accum_steps": 4,
    "max_grad_norm": 1.0,
    "weight_decay": 0.01,
    "dropout_rate": 0.1,
    "adam_eps": 1e-08,
    "seed": 42,
    "evaluate_steps": 1000,
    "warmup_steps": 0.1,
    "ignore_index": 0,
    "save_steps": 1000,
    "stop_epochs": 4,
    "num_workers": 0,
    "max_steps": -1,
    "flag_save_model_state": true,
    "flag_dynamic_encode": false,
    "flag_tokenizer_char": true,
    "flag_soft_label": true,
    "flag_save_best": true,
    "flag_dropout": false,
    "flag_shuffle": true,
    "flag_active": false,
    "flag_train": false,
    "flag_cuda": true,
    "flag_mft": true,
    "flag_adv": false,
    "xy_keys_predict": [
        "original_text",
        "correct_text",
        "wrong_ids"
    ],
    "keys": [
        "original_text",
        "correct_text",
        "wrong_ids"
    ],
    "save_best_mertics_key": [
        "sentence",
        "strict_cor_f1"
    ],
    "label_sep": "|myz|",
    "multi_label_threshold": 0.5,
    "len_rate": 1,
    "adv_emb_name": "word_embeddings.",
    "adv_eps": 1.0,
    "additional_special_tokens": [],
    "len_corpus": null,
    "prior_count": null,
    "prior": null,
    "l2i": null,
    "i2l": null,
    "xy_keys": [
        "original_text",
        "correct_text",
        "wrong_ids"
    ]
}