How to cross validate a DNN model?
$begingroup$
You have a binary classification model giving a decent score on selected metrics. The model has been trained using early stopping. The epoch with the lowest loss is kept.
Now you want to cross validate it. Is it ok to train this model with early stopping on each fold? And keep the best weights as the selected model?
That is what I am doing but I have doubts about this. I am assuming that it is ok to early stop just before the overfitting point because my model isn't that big, I use regularizers and I have a ton of data (in one epoch I arrive at 96% and 0.1 loss on a sigmoid with 65k test samples).
deep-learning training
asked 3 mins ago
Gam SengieGam Sengie
11
$endgroup$
add a comment |
$begingroup$
You have a binary classification model giving a decent score on selected metrics. The model has been trained using early stopping. The epoch with the lowest loss is kept.
Now you want to cross validate it. Is it ok to train this model with early stopping on each fold? And keep the best weights as the selected model?
That is what I am doing but I have doubts about this. I am assuming that it is ok to early stop just before the overfitting point because my model isn't that big, I use regularizers and I have a ton of data (in one epoch I arrive at 96% and 0.1 loss on a sigmoid with 65k test samples).
deep-learning training
asked 3 mins ago
Gam SengieGam Sengie
11
$endgroup$
add a comment |
$begingroup$
You have a binary classification model giving a decent score on selected metrics. The model has been trained using early stopping. The epoch with the lowest loss is kept.
Now you want to cross validate it. Is it ok to train this model with early stopping on each fold? And keep the best weights as the selected model?
That is what I am doing but I have doubts about this. I am assuming that it is ok to early stop just before the overfitting point because my model isn't that big, I use regularizers and I have a ton of data (in one epoch I arrive at 96% and 0.1 loss on a sigmoid with 65k test samples).
deep-learning training
asked 3 mins ago
Gam SengieGam Sengie
11
$endgroup$
You have a binary classification model giving a decent score on selected metrics. The model has been trained using early stopping. The epoch with the lowest loss is kept.
Now you want to cross validate it. Is it ok to train this model with early stopping on each fold? And keep the best weights as the selected model?
That is what I am doing but I have doubts about this. I am assuming that it is ok to early stop just before the overfitting point because my model isn't that big, I use regularizers and I have a ton of data (in one epoch I arrive at 96% and 0.1 loss on a sigmoid with 65k test samples).
deep-learning training
deep-learning training
asked 3 mins ago
Gam SengieGam Sengie
11
asked 3 mins ago
Gam SengieGam Sengie
11
asked 3 mins ago
Gam SengieGam Sengie
11
asked 3 mins ago
Gam SengieGam Sengie
11
asked 3 mins ago
Gam SengieGam Sengie
11
11
add a comment |
add a comment |
0
active
oldest
votes
Your Answer
StackExchange.ifUsing("editor", function () {
return StackExchange.using("mathjaxEditing", function () {
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
});
});
}, "mathjax-editing");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "557"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: false,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: null,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f44500%2fhow-to-cross-validate-a-dnn-model%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
0
active
oldest
votes
0
active
oldest
votes
active
oldest
votes
active
oldest
votes
Thanks for contributing an answer to Data Science Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f44500%2fhow-to-cross-validate-a-dnn-model%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
