fit: Train a Model

In ggmlR: 'GGML' Tensor Operations for Machine Learning

Train a Model

Description

Trains the model on data for a fixed number of epochs. This is the keras-compatible interface; it delegates to ggml_fit.

Usage

## S3 method for class 'ggml_sequential_model'
fit(
  object,
  x,
  y,
  epochs = 1L,
  batch_size = 32L,
  validation_split = 0,
  validation_data = NULL,
  verbose = 1L,
  callbacks = list(),
  ...
)

## S3 method for class 'ggml_functional_model'
fit(
  object,
  x,
  y,
  epochs = 1L,
  batch_size = 32L,
  validation_split = 0,
  validation_data = NULL,
  verbose = 1L,
  callbacks = list(),
  ...
)

Arguments

object	A compiled model object.
x	Training data. Matrix, array, or list of matrices (multi-input).
y	Training labels (matrix, one-hot encoded for classification).
epochs	Number of training epochs (default 1).
batch_size	Batch size (default 32).
validation_split	Fraction of data for validation (default 0).
validation_data	Optional list(x_val, y_val).
verbose	0 = silent, 1 = progress (default 1).
callbacks	List of callback objects (default list()).
...	Additional arguments passed to ggml_fit.

Value

The trained model (invisibly), with model$history.

Examples

model <- ggml_model_sequential() |>
  ggml_layer_dense(10, activation = "softmax", input_shape = 4)
model <- compile(model, optimizer = "adam",
                 loss = "categorical_crossentropy")
# model <- fit(model, x_train, y_train, epochs = 5, batch_size = 32)

ggmlR documentation built on July 14, 2026, 1:08 a.m.