What rating indicates that a model is in a 'Good' performance range?

A model's performance rating falling between 70 and 90 percent is widely regarded as being in a 'Good' performance range. This range indicates that the model demonstrates a satisfactory level of accuracy, balancing the potential for errors while still maintaining a degree of reliability. Ratings below 70 percent typically suggest that the model may not be adequate for practical applications, displaying a higher likelihood of inaccuracies. Conversely, a rating above 90 percent can indicate exceptional performance, yet it might also hint at overfitting, where the model is too tailored to the training dataset and could struggle with new, unseen data. Therefore, the range of 70 to 90 percent optimally reflects a balanced trade-off between model effectiveness and generalization, making it the ideal benchmark for categorizing a model as performing well.