# tinker.types.AdamParams

*Generated from tinker 0.30.4 at commit [`1e5777e`](https://github.com/thinking-machines-lab/tinker/tree/1e5777ef1e0bb2bae6d9b8d63a6144eec405377d). Source links point at that snapshot.*

## *class* [**tinker.types.AdamParams**](https://github.com/thinking-machines-lab/tinker/blob/1e5777ef1e0bb2bae6d9b8d63a6144eec405377d/src/tinker/types/optimizer.py#L29)(*[StrictBase](https://github.com/thinking-machines-lab/tinker/blob/1e5777ef1e0bb2bae6d9b8d63a6144eec405377d/src/tinker/_models.py#L76)*)

**Fields:**

- [**learning_rate**](https://github.com/thinking-machines-lab/tinker/blob/1e5777ef1e0bb2bae6d9b8d63a6144eec405377d/src/tinker/types/optimizer.py#L30) (*float*) – Learning rate for the optimizer
- [**beta1**](https://github.com/thinking-machines-lab/tinker/blob/1e5777ef1e0bb2bae6d9b8d63a6144eec405377d/src/tinker/types/optimizer.py#L33) (*float*) – Coefficient used for computing running averages of gradient
- [**beta2**](https://github.com/thinking-machines-lab/tinker/blob/1e5777ef1e0bb2bae6d9b8d63a6144eec405377d/src/tinker/types/optimizer.py#L36) (*float*) – Coefficient used for computing running averages of gradient square
- [**eps**](https://github.com/thinking-machines-lab/tinker/blob/1e5777ef1e0bb2bae6d9b8d63a6144eec405377d/src/tinker/types/optimizer.py#L39) (*float*) – Term added to the denominator to improve numerical stability
- [**weight_decay**](https://github.com/thinking-machines-lab/tinker/blob/1e5777ef1e0bb2bae6d9b8d63a6144eec405377d/src/tinker/types/optimizer.py#L42) (*float*) – Weight decay for the optimizer. Uses decoupled weight decay.
- [**grad_clip_norm**](https://github.com/thinking-machines-lab/tinker/blob/1e5777ef1e0bb2bae6d9b8d63a6144eec405377d/src/tinker/types/optimizer.py#L45) (*float*) – Maximum global gradient norm. If the global gradient norm is greater than this value, it will be clipped to this value. 0.0 means no clipping.

## Referenced by

- [TrainingClient.optim_step](https://tinker-docs.thinkingmachines.ai/tinker/api-reference/trainingclient/#optim_step)