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"device": "cuda",
# "device": "cpu",
"checkpoint_path": "./data/checkpoint",
"lr": 0.0002,
"weight_decay": 0.0005,
"dropout": 0.3,

"report_frequency": 50,
"eval_frequency": 200,

# ontonotes dir
# 英文
# "ontonotes_root_dir": "./data/ontonotes",
# 中文零指代
"ontonotes_root_dir": "./data/ontonotes/data/files/data/chinese/annotations",
"train_file_path": "./data/train.json",
"test_file_path": "./data/test.json",
"val_file_path": "./data/val.json",

# max candidate mentions size in first/second stage
"top_unit_ratio": 0.5,
"max_top_antecedents": 50,
# use coarse to fine pruning
"coarse_to_fine": True,
# high order coref depth
"coref_depth": 2,

# FFNN config
"ffnn_depth": 1,
"ffnn_size": 3000,

# use span features, such as distance
"use_features": True,
"feature_dim": 20,
"model_heads": True,
# use metadata, such as genre and speaker info
"use_metadata": True,
"genres": ["bc", "bn", "mz", "nw", "tc", "wb"],

# 选择topk时是否考虑单元互斥
"extract_units": True,

# 指代检测损失权重
"unit_detection_loss_weight": 0.2,

# interaction among units
"use_units_interaction_before_score": True,  # 计算得分前的交互
"use_units_interaction_after_score": True,  # 计算得分后的交互
"interaction_method_after_score": "max",  # 计算得分后的交互方式max/mean

# 带权self attention
"wsa_depth": 1,
"wsa_layer_num": 1,
"wsa_dropout": 0.3,
"wsa_pwff_size": 3072,
"wsa_head_num": 8,
"wsa_lr": 0.0002,

# transformer model
# "transformer_model_name": './data/bert-base-chinese',
"transformer_model_name": 'bert-base-chinese',
"transformer_lr": 0.00001,