config/inference-config.yaml [45:79]:
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    keyword: 'NO'

  model_parameters:
    image_encoder:
        algorithm: 'DenseNet'
        image_width: 224
        image_height: 224
        image_embedding_dim: 94080

    text_encoder:
        algorithm: 'LSTM'
        embedding_dim: 200
        hidden_dim: 64
        dropout: 0.5

    decoder:
        algorithm: 'greedy'
        hidden_dim: 256
        beam_size: 5

    optimizer:
        algorithm: 'Adam'
        lr: 0.0001
        beta_1: 0.9
        beta_2: 0.999

    loss_function: 'categorical_crossentropy'

    training:
        batch_size: 4
        epoch: 200

    inference:
        model_file: 'apple/bert/densenet/model_121.h5' # 'apple/glove/densenet/keyword/model_199.h5'
        user_input: 'NO'
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config/training-config.yaml [45:79]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    keyword: 'NO'

  model_parameters:
    image_encoder:
        algorithm: 'DenseNet'
        image_width: 224
        image_height: 224
        image_embedding_dim: 94080

    text_encoder:
        algorithm: 'LSTM'
        embedding_dim: 200
        hidden_dim: 64
        dropout: 0.5

    decoder:
        algorithm: 'greedy'
        hidden_dim: 256
        beam_size: 5

    optimizer:
        algorithm: 'Adam'
        lr: 0.0001
        beta_1: 0.9
        beta_2: 0.999

    loss_function: 'categorical_crossentropy'

    training:
        batch_size: 4
        epoch: 200

    inference:
        model_file: 'apple/bert/densenet/model_121.h5' # 'apple/glove/densenet/keyword/model_199.h5'
        user_input: 'NO'
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