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Why doesn't the Artificial Neural Network stop training at the point where it achieves the best performance indicated by the lowest MSE on the performance plot?

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Why doesn't the Artificial Neural Network stop training at the point where it achieves the best performance indicated by the lowest Mean Squared Error (performance) on the performance plot?

Answers (1)

Ganesh
Ganesh on 22 Dec 2023
Edited: Ganesh on 24 Dec 2023
Hi @Sunita,
The ANN cannot stop at the lowest point, because at the time of training there is no lowest point. Ideally, the lowest loss that a model can achieve is 0. However, during training, the model has no idea of whether the loss will increase or decrease further down the line.
A model training works in the following way:
  1. The model starts off with initial weights.
  2. The model makes a prediction and assesses the loss attained for a data point.
  3. The model corrects the weight according to the loss attained.
  4. The model makes a prediction using the corrected weight and assesses the loss for next data point.
  5. The process continues until all data points are exhausted.
  6. The performance plot shows the loss attained at each step.
The model thus, has no way of knowing it’s performance on data it has not seen.
It is to be noted that the lowest mean squared error does not mean that the model is performing the best at that point. It means that the model performs well for the data it has already seen. Allowing it to train over more data would ensure that the model makes accurate predictions for unseen data.
Hope this answer helps!
  3 Comments
Sunita
Sunita on 23 Dec 2023
Thank you for your response. My question pertains to the following data obtained during model training:
  1. The model stopped at epoch 22 with an MSE of 0.0242
  2. The best performance was observed at epoch 16 with an MSE of 0.031
  3. However, the final MSE between actual and predicted values is 0.0308
Shouldn't the third data align with the best performance (second) value ?
Matt J
Matt J on 25 Dec 2023
Edited: Matt J on 25 Dec 2023
The best performance was observed at epoch 16 with an MSE of 0.031
An MSE of 0.031 is worse than an MSE of 0.0242. MSE is something you want to minimize.
Shouldn't the third data align with the best performance (second) value ?
No, see here:

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