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# 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]]
```python
bitsandbytes.optim.SGD(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, optim_bits = 32, args = None, min_8bit_size = 4096)
```
[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/sgd.py#L8)
#### __init__[[bitsandbytes.optim.SGD.__init__]]
```python
__init__(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, optim_bits = 32, args = None, min_8bit_size = 4096)
```
[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/sgd.py#L9)
**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]]
```python
bitsandbytes.optim.SGD8bit(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096)
```
[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/sgd.py#L59)
#### __init__[[bitsandbytes.optim.SGD8bit.__init__]]
```python
__init__(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096)
```
[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/sgd.py#L60)
**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]]
```python
bitsandbytes.optim.SGD32bit(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096)
```
[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/sgd.py#L107)
#### __init__[[bitsandbytes.optim.SGD32bit.__init__]]
```python
__init__(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096)
```
[Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2030/bitsandbytes/optim/sgd.py#L108)
**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.

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