tflite_model_maker.text_classifier.MobileBertClassifierSpec

Creates MobileBert model spec for the text classification task. See also: tflite_model_maker.text_classifier.BertClassifierSpec.

tflite_model_maker.text_classifier.MobileBertClassifierSpec(
    *,
    uri='https://tfhub.dev/google/mobilebert/uncased_L-24_H-128_B-512_A-4_F-4_OPT/1',
    model_dir=None,
    seq_len=128,
    dropout_rate=0.1,
    initializer_range=0.02,
    learning_rate=3e-05,
    distribution_strategy='off',
    num_gpus=-1,
    tpu='',
    trainable=True,
    do_lower_case=True,
    is_tf2=False,
    name='MobileBert',
    tflite_input_name=None,
    default_batch_size=48,
    index_to_label=None
)

uri TF-Hub path/url to Bert module.
model_dir The location of the model checkpoint files.
seq_len Length of the sequence to feed into the model.
dropout_rate The rate for dropout.
initializer_range The stdev of the truncated_normal_initializer for initializing all weight matrices.
learning_rate The initial learning rate for Adam.
distribution_strategy A string specifying which distribution strategy to use. Accepted values are 'off', 'one_device', 'mirrored', 'parameter_server', 'multi_worker_mirrored', and 'tpu' -- case insensitive. 'off' means not to use Distribution Strategy; 'tpu' means to use TPUStrategy using tpu_address.
num_gpus How many GPUs to use at each worker with the DistributionStrategies API. The default is -1, which means utilize all available GPUs.
tpu TPU address to connect to.
trainable boolean, whether pretrain layer is trainable.
do_lower_case boolean, whether to lower case the input text. Should be True for uncased models and False for cased models.
is_tf2 boolean, whether the hub module is in TensorFlow 2.x format.
name The name of the object.
tflite_input_name Dict, input names for the TFLite model.
default_batch_size Default batch size for training.
index_to_label List of labels in the training data. e.g. ['neg', 'pos'].