系统
操作系统：UbuntuPython版本：3.6.7AllenNLP版本：1.0.0
问题：通过以下命令，我可以训练模型，但我不知道是更新权重进行微调，还是只是训练一个新模型？
我正试图使用以下命令对新数据(即SQuAD格式)的阅读理解模型进行微调：
allennlp train fine_tune_config.json -s fine-tune-test/和以下配置：
{
"dataset_reader": {
"type": "squad",
"token_indexers": {
"tokens": {
"type": "single_id",
"lowercase_tokens": true
},
"elmo": {
"type": "elmo_characters"
},
"token_characters": {
"type": "characters",
"character_tokenizer": {
"byte_encoding": "utf-8",
"start_tokens": [259],
"end_tokens": [260]
},
"min_padding_length": 5
}
}
},
"train_data_path": "train-v2.0_trimed.json",
"validation_data_path": "validation_data.json",
"model": {
"type": "bidaf",
"text_field_embedder": {
"token_embedders": {
"tokens": {
"type": "embedding",
"pretrained_file": "glove.6B.100d.txt",
"embedding_dim": 100,
"trainable": true
},
"elmo":{
"type": "elmo_token_embedder",
// "options_file": "https://allennlp.s3.amazonaws.com/models/elmo/2x4096_512_2048cnn_2xhighway/elmo_2x4096_512_2048cnn_2xhighway_options.json",
"options_file": "options_file.json",
// "weight_file": "https://allennlp.s3.amazonaws.com/models/elmo/2x4096_512_2048cnn_2xhighway/elmo_2x4096_512_2048cnn_2xhighway_weights.hdf5",
"weight_file": "elmo_2x4096_512_2048cnn_2xhighway_weights.hdf5",
"do_layer_norm": false,
"dropout": 0.0
},
"token_characters": {
"type": "character_encoding",
"embedding": {
"num_embeddings": 262,
"embedding_dim": 16
},
"encoder": {
"type": "cnn",
"embedding_dim": 16,
"num_filters": 100,
"ngram_filter_sizes": [5]
},
"dropout": 0.2
}
}
},
"num_highway_layers": 2,
"phrase_layer": {
"type": "lstm",
"bidirectional": true,
"input_size": 1224,
"hidden_size": 100,
"num_layers": 1
},
"matrix_attention": {
"type": "linear",
"combination": "x,y,x*y",
"tensor_1_dim": 200,
"tensor_2_dim": 200
},
"modeling_layer": {
"type": "lstm",
"bidirectional": true,
"input_size": 800,
"hidden_size": 100,
"num_layers": 2,
"dropout": 0.2
},
"span_end_encoder": {
"type": "lstm",
"bidirectional": true,
"input_size": 1400,
"hidden_size": 100,
"num_layers": 1
},
"dropout": 0.2
},
"data_loader": {
"batch_sampler": {
"type": "bucket",
"batch_size": 40
}
},
"trainer": {
"num_epochs": 20,
"grad_norm": 5.0,
"patience": 10,
"validation_metric": "+em",
"learning_rate_scheduler": {
"type": "reduce_on_plateau",
"factor": 0.5,
"mode": "max",
"patience": 2
},
"optimizer": {
"type": "adam",
"betas": [0.9, 0.9]
}
}
}
'''
此训练配置将使用预先训练的ELMo权重并从那里开始。不过，我不确定是否要注释掉"options_file"行。
模型中还有其他权重，这些权重不属于ELMo。这些将被随机初始化，然后进行训练。