Buckets:
| # 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. | |
Xet Storage Details
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