if (model_info().unstable()) {
Log.err("Canceling job since the model is unstable (exponential growth observed).");
Log.err("Try a bounded activation function or regularization with L1, L2 or max_w2 and/or use a smaller learning rate or faster annealing.");
keep_running = false;
} else if (ftest == null &&
<BUG>(model_info().parameters.classification && errors[errors.length-1].train_err == 0)
|| (!model_info().parameters.classification && errors[errors.length-1].train_mse == 0)
</BUG>
) {
Log.info("Achieved 100% modeling accuracy on the training data. We are done here.");

if (model_info().unstable()) {
Log.err("Canceling job since the model is unstable (exponential growth observed).");
Log.err("Try a bounded activation function or regularization with L1, L2 or max_w2 and/or use a smaller learning rate or faster annealing.");
keep_running = false;
} else if (ftest == null &&
(model_info().get_params().classification && errors[errors.length-1].train_err <= model_info().get_params().classification_stop)
|| (!model_info().get_params().classification && errors[errors.length-1].train_mse <= model_info().get_params().regression_stop)
) {
Log.info("Achieved 100% modeling accuracy on the training data. We are done here.");
