在机器学习中,epoch 数量是指整个训练集通过模型的次数。一个epoch意味着训练数据集中的每个样本都有机会更新内部模型参数。 epoch由一个或多个batch组成。 选择合适的 epoch 数. 变化趋势分析: train loss 不断下降,test loss不断下降,说明网络仍在学习;(最好的) train loss 不断下降,test loss趋于不变,说明网络过拟合; train loss 趋于不变,test loss不断下降,说. 最后的结果还是可以的,train和val的acc都是保持上升的,但前面val的acc在波动,可能是在训练集上 过拟合 了。 可以尝试加些正则项(比如l1、l2)或者使用dropout;另外设置 早停机.
“I'd already begun my preparation for the Dark Knight” Val Kilmer Was
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