Keras EarlyStopping patience parameter

There are three consecutively worse runs by loss, let's look at the numbers:

val_loss: 0.5921 < current best
val_loss: 0.5731 < current best
val_loss: 0.5956 < patience 1
val_loss: 0.5753 < patience 2
val_loss: 0.5977 < patience >2, stopping the training

You already discovered the min delta parameter, but I think it is too small to trigger here (you're off by 10x).

Epoch 1      val_loss: 0.6811 <- current best
Epoch 2      val_loss: 0.6941 <-patience 1
Epoch 3      val_loss: 0.6532 <- current best # current best gets updated
Epoch 4      val_loss: 0.6546 <- patience 1
Epoch 5      val_loss: 0.6534 <-patience 2

Training will stop at epoch 5

Try this example in google colab for more intuitive understanding:https://colab.research.google.com/github/minsuk-heo/tf2/blob/master/jupyter_notebooks/06.DropOut_EarlyStopping.ipynb