bitsandbytes/main/en/reference/optim/sgd.md

SGD

Stochastic gradient descent (SGD) is a basic gradient descent optimizer to minimize loss given a set of model parameters and updates the parameters in the opposite direction of the gradient. The update is performed on a randomly sampled mini-batch of data from the dataset.

bitsandbytes also supports momentum and Nesterov momentum to accelerate SGD by adding a weighted average of past gradients to the current gradient.

SGD[[api-class]][[bitsandbytes.optim.SGD]]

bitsandbytes.optim.SGD[[bitsandbytes.optim.SGD]]

bitsandbytes.optim.SGD(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, optim_bits = 32, args = None, min_8bit_size = 4096)

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init[[bitsandbytes.optim.SGD.init]]

__init__(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, optim_bits = 32, args = None, min_8bit_size = 4096)

Source

Parameters:

params (torch.tensor) : The input parameters to optimize.

lr (float) : The learning rate.

momentum (float, defaults to 0) : The momentum value speeds up the optimizer by taking bigger steps.

dampening (float, defaults to 0) : The dampening value reduces the momentum of the optimizer.

weight_decay (float, defaults to 0.0) : The weight decay value for the optimizer.

nesterov (bool, defaults to False) : Whether to use Nesterov momentum.

optim_bits (int, defaults to 32) : The number of bits of the optimizer state.

args (object, defaults to None) : An object with additional arguments.

min_8bit_size (int, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization.

Base SGD optimizer.

SGD8bit[[bitsandbytes.optim.SGD8bit]]

bitsandbytes.optim.SGD8bit[[bitsandbytes.optim.SGD8bit]]

bitsandbytes.optim.SGD8bit(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096)

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init[[bitsandbytes.optim.SGD8bit.init]]

__init__(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096)

Source

Parameters:

params (torch.tensor) : The input parameters to optimize.

lr (float) : The learning rate.

momentum (float, defaults to 0) : The momentum value speeds up the optimizer by taking bigger steps.

dampening (float, defaults to 0) : The dampening value reduces the momentum of the optimizer.

weight_decay (float, defaults to 0.0) : The weight decay value for the optimizer.

nesterov (bool, defaults to False) : Whether to use Nesterov momentum.

args (object, defaults to None) : An object with additional arguments.

min_8bit_size (int, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization.

8-bit SGD optimizer.

SGD32bit[[bitsandbytes.optim.SGD32bit]]

bitsandbytes.optim.SGD32bit[[bitsandbytes.optim.SGD32bit]]

bitsandbytes.optim.SGD32bit(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096)

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init[[bitsandbytes.optim.SGD32bit.init]]

__init__(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096)

Source

Parameters:

params (torch.tensor) : The input parameters to optimize.

lr (float) : The learning rate.

momentum (float, defaults to 0) : The momentum value speeds up the optimizer by taking bigger steps.

dampening (float, defaults to 0) : The dampening value reduces the momentum of the optimizer.

weight_decay (float, defaults to 0.0) : The weight decay value for the optimizer.

nesterov (bool, defaults to False) : Whether to use Nesterov momentum.

args (object, defaults to None) : An object with additional arguments.

min_8bit_size (int, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization.

32-bit SGD optimizer.