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无法理解我用于多类分类的 CNN model 是否过拟合?

[英]Could not understand if my CNN model for multiclass classification is overfitted or not?

Good training, testing and validation accuracies but strange historical accuracies behavior for model: Here is the summary of my model: model 的训练、测试和验证准确度很好,但历史准确度行为奇怪:这是我的 model 的总结:

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I performed the execution and prediction tasks and I've got the next confusion matrix:我执行了执行和预测任务,得到了下一个混淆矩阵:

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while the Accuracy behavior was the next:而准确性行为是下一个:

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I can not understand if this is overfitting or underfitting or a normal behavior?我不明白这是过拟合还是欠拟合还是正常行为?

Adding the loss plot to clarify more in the next添加损失 plot 以在下一个中澄清更多

数字

Thank you in advance for any useful information and help !提前感谢您提供任何有用的信息和帮助!

Does not look like over fitting.看起来不像过度拟合。 Your training accuracy is increasing and so is the AVERAGE test accuracy.您的训练准确度正在提高,AVERAGE 测试准确度也在提高。 Over fitting is when the test loss improves, then plateaus and then starts to increase.过度拟合是指测试损失有所改善,然后达到稳定水平,然后开始增加。 It is best to look at loss metrics to monitor this.最好查看损失指标来监控这一点。 It is typical that once the training accuracy gets high the test loss will oscillate to a small degree.通常,一旦训练准确度变高,测试损失就会在很小的程度上波动。 You can test for over fitting by varying the drop out rate and see the effect on test loss.您可以通过改变丢弃率来测试过度拟合,并查看对测试损失的影响。

As you already mentioned your training is doing well.正如你已经提到的,你的训练做得很好。

First of all I recommend you to check a prediction by yourself with test-data.首先,我建议您使用测试数据自行检查预测。 The Validation-loss will converge until a specific value. Validation-loss 会收敛到一个特定的值。 It may looks a little bit variance but you need as reference the y-Axis.它可能看起来有点差异,但您需要 y 轴作为参考。 The ups and downs of the last epochs are between 91% and 94% which is not really much in reference to 100% (maybe change the y-Axis).最后一个时期的起伏在 91% 到 94% 之间,相对于 100% 来说并不算多(可能会改变 y 轴)。

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