bitsandbytes/v0.50.0/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]]

• 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]]

• 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]]

• 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.