reformat documentation
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@ -55,8 +55,8 @@ class PyTorchModelTrainer:
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:param device: The device to use for training (e.g. 'cpu', 'cuda').
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:param device: The device to use for training (e.g. 'cpu', 'cuda').
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:param batch_size: The size of the batches to use during training.
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:param batch_size: The size of the batches to use during training.
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:param max_iters: The number of training iterations to run.
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:param max_iters: The number of training iterations to run.
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iteration here refers to the number of times we call self.optimizer.step().
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iteration here refers to the number of times we call
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used to calculate n_epochs.
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self.optimizer.step(). used to calculate n_epochs.
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:param eval_iters: The number of iterations used to estimate the loss.
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:param eval_iters: The number of iterations used to estimate the loss.
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:param init_model: A dictionary containing the initial model/optimizer
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:param init_model: A dictionary containing the initial model/optimizer
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state_dict and model_meta_data saved by self.save() method.
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state_dict and model_meta_data saved by self.save() method.
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