task:
  init_checkpoint: ""
  model:
    cls_heads:
      [
        {
          activation: tanh,
          cls_token_idx: 0,
          dropout_rate: 0.1,
          inner_dim: 768,
          name: next_sentence,
          num_classes: 2,
        },
      ]
    encoder:
      type: any
      any:
        attention_dropout_rate: 0.1
        dropout_rate: 0.1
        embedding_size: 768
        hidden_activation: gelu
        hidden_size: 768
        initializer_range: 0.02
        intermediate_size: 3072
        max_position_embeddings: 512
        num_attention_heads: 12
        num_layers: 12
        type_vocab_size: 2
        vocab_size: 30522
        attention_window: [32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32]
        global_attention_size: 1
  train_data:
    drop_remainder: true
    global_batch_size: 256
    input_path: 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    max_predictions_per_seq: 76
    seq_length: 512
    use_next_sentence_label: true
    use_position_id: false
  validation_data:
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    global_batch_size: 256
    input_path: TODO
    is_training: false
    max_predictions_per_seq: 76
    seq_length: 512
    use_next_sentence_label: true
    use_position_id: false
trainer:
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  optimizer_config:
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        decay_steps: 1000000
        end_learning_rate: 0.0
        initial_learning_rate: 0.0001
        power: 1.0
      type: polynomial
    optimizer:
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    warmup:
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        warmup_steps: 10000
      type: polynomial
  steps_per_loop: 50
  summary_interval: 50
  train_steps: 1000000
  validation_interval: 1000
  validation_steps: 64
