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###########################################################
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# DATA SETTING #
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###########################################################
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dataset_type: Ernie
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train_path: data/iwslt2012_zh/train.txt
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dev_path: data/iwslt2012_zh/dev.txt
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test_path: data/iwslt2012_zh/test.txt
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batch_size: 64
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num_workers: 2
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data_params:
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pretrained_token: ernie-1.0
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punc_path: data/iwslt2012_zh/punc_vocab
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seq_len: 100
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###########################################################
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# MODEL SETTING #
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###########################################################
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model_type: ErnieLinear
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model:
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pretrained_token: ernie-1.0
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num_classes: 4
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###########################################################
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# OPTIMIZER SETTING #
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###########################################################
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optimizer_params:
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weight_decay: 1.0e-6 # weight decay coefficient.
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scheduler_params:
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learning_rate: 1.0e-5 # learning rate.
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gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
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###########################################################
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# TRAINING SETTING #
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###########################################################
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max_epoch: 20
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num_snapshots: 5
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###########################################################
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# OTHER SETTING #
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###########################################################
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num_snapshots: 10 # max number of snapshots to keep while training
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seed: 42 # random seed for paddle, random, and np.random
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