Questions tagged [early-stopping]

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Tensorflow / Keras - Using both ModelCheckpoint: save_best_only and EarlyStopping: restore_best_weights

ModelCheckpoint save_best_only: if save_best_only=True, it only saves when the model is considered the "best" and the latest best model according to the quantity monitored will not be ...
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3 votes
1 answer
218 views

What is the purpose of EarlyStopping returning last epoch's weights by default?

I recently realized that keras callback for early stopping returns the last epoch's weights by default. If you want to do otherwise you can use the argument ...
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0 answers
88 views

How to use early_stopping_rounds in the Final Model? (CatBoost example with Optuna)

Imagine we have a model in the sklearn pipeline: ...
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0 answers
48 views

Early stopping on validation loss or macro-F1?

I am working on an extremely imbalanced dataset to build a classification model. The number of classes is 53 classes. I use early stopping on the validation loss to prevent the model from overfitting. ...
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1 vote
2 answers
45 views

Strategy to choose maximum value from an unknown array of n numbers

Suppose you have an array of n normally distributed numbers whose values are initially unknown(and the probability parameters are unknown too). You must choose one number and you want it to have ...
0 votes
1 answer
96 views

Is it ok if I use early callbacks with restore best weights?

Does anyone know, if it is ok if I use early callbacks with restore best weights? The metric measured by the early callback is validation loss. I was afraid that if I restore the best weights of the ...
1 vote
0 answers
18 views

Is Callback / early stopping and validation set is not mandatory

I just noticed that in mostly github repositry of research papers they didnt implemented early stopping criteria and they didnt use validation set but whats the reason behind this?
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1 vote
1 answer
193 views

Keras: How to restore initial weights when using EarlyStopping

Using Keras, I setup EarlyStoping like this: EarlyStopping(monitor='val_loss', min_delta=0, patience=100, verbose=0, mode='min', restore_best_weights=True) When I ...
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0 votes
1 answer
259 views

Early stopping based on average val_loss of last ten epoches and with some n partiences

I am training a DNN with CNN in Keras. Though, I can write an EarlyStopping criteria based on val_loss but due to minor oscillations in the val_loss, I want to monitor the average validation loss over ...
2 votes
0 answers
48 views

When to stop the final model training?

Let's say I'm participating in a Kaggle image recognition competition. Firstly, I create a train/validation split and find the good hyperparameters for my model. Here the stopping criterion is when ...
0 votes
1 answer
165 views

Early stopping with class weights / sample weights

I'm performing a classification of imbalanced multiclass data using a Neural Network in the TensorFlow framework. Therefore, I'm applying class weights. I would like to apply early stopping to reduce ...
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3 votes
1 answer
2k views

Keras EarlyStopping callback: Why would I ever set restore_best_weights=False?

The point of EarlyStopping is to stop training at a point where validation loss (or some other metric) does not improve. If I have set ...
0 votes
0 answers
186 views

Can we used both cross validation/nested cross validation technique and early stopping with patient at the same time?

Can we use both cross validation/nested cross validation technique and early stopping with patient at the same time? Using early stopping for each (training, validation) fold and get best result of ...
1 vote
1 answer
112 views

NGBoost and overfit - which model is used?

While training an NGBoost model I got: ...
-1 votes
1 answer
66 views

Can the use of EarlyStopping() offset overfitting problems caused by validation_split?

Keras gives users the option, while fitting a model, to split the data into train/test samples using the parameter "validation_split. Example: ...
1 vote
1 answer
107 views

EarlyStopping based on the loss

When training my CNN model, based on the random initialization of weights, i get the prediction results. In other words, with the same training and test data i get different results every time when i ...
1 vote
1 answer
76 views

Daily new data for my neural network, and I want transfer(?) learning

I made my neural network, it is pre-trained for 180 days of data. ...
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17 votes
3 answers
6k views

What is the proper way to use early stopping with cross-validation?

I am not sure what is the proper way to use early stopping with cross-validation for a gradient boosting algorithm. For a simple train/valid split, we can use the valid dataset as the evaluation ...
7 votes
1 answer
6k views

Keras Early Stopping: Monitor 'loss' or 'val_loss'?

I often use "early stopping" when I train neural nets, e.g. in Keras: ...
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