You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: As TIMIT is a relatively small dataset, proper regularization is crucial. We usedthe adaptive weight noise as a main regularizer [22]. We firsttrained our models with a column norm constraint [23] with themaximum norm 1until the lowest development negative log-likelihood is achieved.333Applying the weight noise from the beginning of training caused severeunderfitting.During this time, \epsilon and \rho are set to 10^{-8} and 0.95,respectively. At this point, we began using the adaptive weight noise, andscaled down the model complexity cost L_{C} by a factor of 10, while disablingthe column norm constraints. Oncethe new lowest development log-likelihood was reached, we fine-tuned the modelwith a smaller \epsilon=10^{-10}, until we didnot observe the improvement in the development phoneme error rate (PER) for 100Kweight updates. Batch size 1 was used throughout thetraining.

Question: Did authors perform a hyperparameter search before deciding the values of batch size, epsilon and L_C during training?
While the paper shows what value the author set for those hyperparameters, there is no evidential information about the hyperparameter search in this paper.