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Can I continue a machine learning process after shutdown?


Can we train a neural network to tell if an object is present or not in an Image?What exactly is a step in Tensorflow prebuilt architectures?Breaking captcha with a neural network - Learning deep learningWhat are differentiable modules used in deep learningHow to extract all information by using idIs there any work done on reconfigurable convolutional neural networks?How can I combine images for Matlab deep learning?Simple Object DetectionHow is Stochastic Gradient Descent done in Faster RCNN?What (and how) should I use for object detection in this case?













1












$begingroup$


I use Mask RCNN for object detection and instance segmentation.
I am new to neural networks, this is my first project.



I use jupyter notebook. Can I continue learning after shutdown?
enter image description here



I would like start learning from 6 epoch. How can I do it?
One epoch ~ 1h. I don't want to waste time, and continue this process. Is it possible?










share|improve this question











$endgroup$
















    1












    $begingroup$


    I use Mask RCNN for object detection and instance segmentation.
    I am new to neural networks, this is my first project.



    I use jupyter notebook. Can I continue learning after shutdown?
    enter image description here



    I would like start learning from 6 epoch. How can I do it?
    One epoch ~ 1h. I don't want to waste time, and continue this process. Is it possible?










    share|improve this question











    $endgroup$














      1












      1








      1





      $begingroup$


      I use Mask RCNN for object detection and instance segmentation.
      I am new to neural networks, this is my first project.



      I use jupyter notebook. Can I continue learning after shutdown?
      enter image description here



      I would like start learning from 6 epoch. How can I do it?
      One epoch ~ 1h. I don't want to waste time, and continue this process. Is it possible?










      share|improve this question











      $endgroup$




      I use Mask RCNN for object detection and instance segmentation.
      I am new to neural networks, this is my first project.



      I use jupyter notebook. Can I continue learning after shutdown?
      enter image description here



      I would like start learning from 6 epoch. How can I do it?
      One epoch ~ 1h. I don't want to waste time, and continue this process. Is it possible?







      deep-learning jupyter






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Mar 20 at 13:27









      Blenzus

      446




      446










      asked Mar 20 at 13:17









      BadumBadum

      113




      113




















          1 Answer
          1






          active

          oldest

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          1












          $begingroup$

          In order to continue the learning process, you will need to use checkpoints.



          # source: https://stackoverflow.com/questions/36356004/continue-training-from-a-specific-epoch
          weight_save_callback = ModelCheckpoint('/path/to/weights.epoch:02d-val_loss:.2f.hdf5', monitor='val_loss', verbose=0, save_best_only=False, mode='auto')
          model.fit(X_train,y_train,batch_size=batch_size,nb_epoch=nb_epoch,callbacks=[weight_save_callback])

          # load model
          model = Sequential()
          model.add(...)
          model.load('path/to/weights.hf5')

          # use model.fit to continue training.





          share|improve this answer








          New contributor




          MachineLearner is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
          Check out our Code of Conduct.






          $endgroup$












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            1 Answer
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            active

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            active

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            1












            $begingroup$

            In order to continue the learning process, you will need to use checkpoints.



            # source: https://stackoverflow.com/questions/36356004/continue-training-from-a-specific-epoch
            weight_save_callback = ModelCheckpoint('/path/to/weights.epoch:02d-val_loss:.2f.hdf5', monitor='val_loss', verbose=0, save_best_only=False, mode='auto')
            model.fit(X_train,y_train,batch_size=batch_size,nb_epoch=nb_epoch,callbacks=[weight_save_callback])

            # load model
            model = Sequential()
            model.add(...)
            model.load('path/to/weights.hf5')

            # use model.fit to continue training.





            share|improve this answer








            New contributor




            MachineLearner is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
            Check out our Code of Conduct.






            $endgroup$

















              1












              $begingroup$

              In order to continue the learning process, you will need to use checkpoints.



              # source: https://stackoverflow.com/questions/36356004/continue-training-from-a-specific-epoch
              weight_save_callback = ModelCheckpoint('/path/to/weights.epoch:02d-val_loss:.2f.hdf5', monitor='val_loss', verbose=0, save_best_only=False, mode='auto')
              model.fit(X_train,y_train,batch_size=batch_size,nb_epoch=nb_epoch,callbacks=[weight_save_callback])

              # load model
              model = Sequential()
              model.add(...)
              model.load('path/to/weights.hf5')

              # use model.fit to continue training.





              share|improve this answer








              New contributor




              MachineLearner is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
              Check out our Code of Conduct.






              $endgroup$















                1












                1








                1





                $begingroup$

                In order to continue the learning process, you will need to use checkpoints.



                # source: https://stackoverflow.com/questions/36356004/continue-training-from-a-specific-epoch
                weight_save_callback = ModelCheckpoint('/path/to/weights.epoch:02d-val_loss:.2f.hdf5', monitor='val_loss', verbose=0, save_best_only=False, mode='auto')
                model.fit(X_train,y_train,batch_size=batch_size,nb_epoch=nb_epoch,callbacks=[weight_save_callback])

                # load model
                model = Sequential()
                model.add(...)
                model.load('path/to/weights.hf5')

                # use model.fit to continue training.





                share|improve this answer








                New contributor




                MachineLearner is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.






                $endgroup$



                In order to continue the learning process, you will need to use checkpoints.



                # source: https://stackoverflow.com/questions/36356004/continue-training-from-a-specific-epoch
                weight_save_callback = ModelCheckpoint('/path/to/weights.epoch:02d-val_loss:.2f.hdf5', monitor='val_loss', verbose=0, save_best_only=False, mode='auto')
                model.fit(X_train,y_train,batch_size=batch_size,nb_epoch=nb_epoch,callbacks=[weight_save_callback])

                # load model
                model = Sequential()
                model.add(...)
                model.load('path/to/weights.hf5')

                # use model.fit to continue training.






                share|improve this answer








                New contributor




                MachineLearner is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.









                share|improve this answer



                share|improve this answer






                New contributor




                MachineLearner is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.









                answered Mar 20 at 13:23









                MachineLearnerMachineLearner

                32410




                32410




                New contributor




                MachineLearner is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.





                New contributor





                MachineLearner is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.






                MachineLearner is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.



























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