Summary
Functions
Trains a binary classifier on the given data stream.
Functions
Trains a binary classifier on the given data stream.
Options
:epochs- Number of training epochs. Defaults to10.:batch_size- Batch size for training. Defaults to32.:learning_rate- Initial learning rate. Defaults to1.0e-3.:decay- Learning rate decay. Defaults to1.0e-2.:labels- Mapping of labels. Can be a list or a map. Defaults to[0, 1].:validation_split- Fraction of data to use for validation. Defaults to0.1.:patience- Number of epochs to wait for improvement before early stopping. Defaults to5.:compiler- The Nx compiler to use. Defaults toEXLA.:model_version- The architecture version to use. Defaults tosep_se_cnn.:tune- Iftrue, performs automatic hyperparameter tuning for learning rate and dropout. Defaults tofalse.:dropout_rate- Dropout rate for the model (ignored if:tuneistrue). Defaults to0.2.:vector_length- Fixed sequence length for tokenization. If not provided, it is automatically calculated from data.:tokenizer_data- Custom data stream to train the tokenizer. Defaults to the:textfield ofdata_stream.