Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.

The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.

Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.

The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.