model: ernie_config_path: val: "../LARK/ERNIE/config/ernie_config.json" meaning: "Path to the json file for ernie model config." init_checkpoint: val: "" meaning: "Path to init model" mode: val: "train" meaning: "Setting to train or eval or infer" init_pretraining_params: val: "pretrained/params/" meaning: "Init pre-training params which preforms fine-tuning from. If the arg 'init_checkpoint' has been set, this argument wouldn't be valid." train: random_seed: val: 0 meaning: "Random seed for training" batch_size: val: 10 meaning: "The number of sequences contained in a mini-batch" epoch: val: 10 meaning: "Corpus iteration num" use_cuda: val: True meaning: "If set, use GPU for training." base_learning_rate: val: 0.0002 meaning: "The basic learning rate that affects the entire network." init_bound: val: 0.1 meaning: "init bound for initialization." crf_learning_rate: val: 0.2 meaning: "The real learning rate of the embedding layer will be (crf_learning_rate * base_learning_rate)." cpu_num: val: 10 meaning: "The number of cpu used to train model, it works when use_cuda=False" print_steps: val: 1 meaning: "Print the result per xxx batch of training" save_steps: val: 10 meaning: "Save the model once per xxxx batch of training" validation_steps: val: 5 meaning: "Do the validation once per xxxx batch of training" data: vocab_path: val: "../LARK/ERNIE/config/vocab.txt" meaning: "The path of the vocabulary." label_map_config: val: "./conf/label_map.json" meaning: "The path of the label dictionary." num_labels: val: 57 meaning: "label number" max_seq_len: val: 128 meaning: "Number of words of the longest seqence." do_lower_case: val: True meaning: "Whether to lower case the input text. Should be True for uncased models and False for cased models." train_data: val: "./data/train.tsv" meaning: "The folder where the training data is located." test_data: val: "./data/test.tsv" meaning: "The folder where the test data is located." infer_data: val: "./data/test.tsv" meaning: "The folder where the infer data is located." model_save_dir: val: "./ernie_models" meaning: "The model will be saved in this path."