".1 hyper-parameters we do a hyper-parameter search for the training on both original dataset and augmented dataset and find the following setting: a batch size of 4 and learning rate of 5e-6 is the best one for both. we run at most 20 epochs for each experiment and do validation for every epoch, with an early stop step of 3. for each experiment, we run for three times with different random seeds and report the average value, along with the standard deviation. we run experiments with nvidia rtx a4000 gpu for totally 1440 hours. c.2 metric joint goal accuracy evaluates the performance of predicting dialog states. it counts one for each turn if the model successfully generate all slot values, otherwise count zero", how long was the model trained Do not say the word "turn" in the response
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