You're now ready to define, train and evaluate your model. machine learning - Losses of keras CNN model is not decreasing - Data Solving the TensorFlow Keras Model Loss Problem Making location easier for developers with new data primitives, Stop requiring only one assertion per unit test: Multiple assertions are fine, Mobile app infrastructure being decommissioned. First I preprocess dataset so my train and test dataset shapes are: I can try stepping that up. Unfortunately, the ReLU activation function is not perfect. i use: ssd_inception_v2_coco model. Training loss goes down and up again. What is happening? Do US public school students have a First Amendment right to be able to perform sacred music? Making statements based on opinion; back them up with references or personal experience. When the training starts we will initialize all the values. Loss and accuracy during the training for these examples: deep clustering with convolutional autoencoders My Tensorflow loss is not changing. Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. Small changes to your workflow like this have saved me a lot of time and improved overall satisfaction with my way of working. However, my model loss is not converging as in the code provided. I prefer women who cook good food, who speak three languages, and who go mountain hiking - what if it is a woman who only has one of the attributes? Python 3.6.13 tensorflow 1.15.5 I have to use tensorflow 1.15 in order to be able to use DirectML because i have AMD GPU Problem 1: from step 0 until 3000, my loss has dramatically decreased but after that, it stays constant between 5 to 6 . I will vote your answer up as soon as I have enough reputation points. 84/84 [00:17<00:00, 5.77it/s] Training Loss: 0.8901, Accuracy: 0.83 I want to use one hot to represent group and resource, there are 2 group and 4 resouces in training data: group1 (1, 0) can access resource 1 (1, 0, 0, 0) and resource2 (0, 1, 0, 0) group2 (0 . There are many other options as well to reduce overfitting, assuming you are using Keras, visit this link. Training loss is decreasing while validation loss is NaN 2022 Moderator Election Q&A Question Collection, Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2, Could not find a version that satisfies the requirement tensorflow, CTC loss doesn't decrease using tensorflow, while it decreases using Keras, Tensorflow and Keras show a little different result even though I build exactly same models using same layer modules, error while importing keras ModuleNotFoundError: No module named 'tensorflow.examples'; 'tensorflow' is not a package, Exact model converging on keras-tf but not on keras, Verb for speaking indirectly to avoid a responsibility. People often use cross entropy error when performing binary classification, but this will work too. When the migration is complete, you will access your Teams at stackoverflowteams.com, and they will no longer appear in the left sidebar on stackoverflow.com. Does the 0m elevation height of a Digital Elevation Model (Copernicus DEM) correspond to mean sea level? rev2022.11.3.43004. This is making me think there is something fishy going on with my code or in Keras/Tensorflow since the loss is increasing dramatically and you would expect the accuracy to be . What is a good way to make an abstract board game truly alien? I have 500 images in training set and 40 in test. 0.13285154 0.13954024] I lost the last 2 weeks trying to minimize the loss using other known methods, but the error was related to a totally different thing. 0.14233398 0.14176525 2. Why do you think this architecture would be a good fit for your, from what I understand, different case? Optimizing the variables with those gradients. Can "it's down to him to fix the machine" and "it's up to him to fix the machine"? What should I do when my neural network doesn't learn? No decreasing loss when pre-train for xxlarge #29 - GitHub It was extremely helpful with structure and data loading. Regex: Delete all lines before STRING, except one particular line. I am using tensorflow object detection api for my own dataset I am facing some problem. faster_rcnn_inception_resnet_v2_atrous_coco after some steps loss stay constant between 1 and 2 Curious where is this idea from, never heard of it. 2022 Moderator Election Q&A Question Collection, Keras convolutional neural network validation accuracy not changing, extracting CNN features from middle layers, Training acc decreasing, validation - increasing. I haven't read this paper, neither have I tried your model, but it seems a little strange. Upd. I think the difficulty in training my UNET has to do with it not being built for satellite imagery (I have 38 channels total for a similar segmentation task). loss is not decreasing, and stay about 10 It's hard to debug your model with those informations, but maybe some of those ideas will help you in some way: And the most important coming last; I don't think SO is the best place for such question (especially as it is research oriented), I see you have already asked it on GitHub issues though, maybe try to contact author directly? faster_rcnn_inception_resnet_v2_atrous_coco after some steps loss stay constant between 1 and 2. Usage of transfer Instead of safeTransfer. Effect of batch size on training dynamics | by Kevin Shen | Mini To subscribe to this RSS feed, copy and paste this URL into your RSS reader. The alternative is to have a simple plot, with train and test loss, that updates every epoch or every n steps. Is a planet-sized magnet a good interstellar weapon? Not the answer you're looking for? Asking for help, clarification, or responding to other answers. I did the following steps and I have two problems. Conveniently, we can use tf.utils.shuffle for that purpose, which will shuffle an arbitray array inplace: 9. Can I spend multiple charges of my Blood Fury Tattoo at once? Finding features that intersect QgsRectangle but are not equal to themselves using PyQGIS, Non-anthropic, universal units of time for active SETI. I am tensorflow beginner required suggestion. Training and evaluation with the built-in methods - TensorFlow Share How are different terrains, defined by their angle, called in climbing? Does the Fog Cloud spell work in conjunction with the Blind Fighting fighting style the way I think it does? I prefer women who cook good food, who speak three languages, and who go mountain hiking - what if it is a woman who only has one of the attributes? Best way to get consistent results when baking a purposely underbaked mud cake. Is there more information I could provide that would be helpful? 84/84 [00:17<00:00, 5.72it/s] Training Loss: 0.7922, Accuracy: 0.83 I'm largely following this project but am doing a pixel-wise classification. Hi, I am new to deeplearning and pytorch, I write a very simple demo, but the loss can't decreasing when training. Calculating the loss by comparing the outputs to the output (or label) Using gradient tape to find the gradients. Thanks for contributing an answer to Stack Overflow! Each function receives the parameter logs, which is a dictionary containing for each metric name (accuracy, loss, etc) the corresponding value for the epoch: To plot the training progress we need to store this data and update it to keep plotting in each new epoch. The regularization terms are only applied while training the model on the training set, inflating the training loss. Not getting how I reduce it but still my model able to detect required object. Should we burninate the [variations] tag? Thanks for showing me what and why it happened. I'm currently using a batch size of 8. I get at least 91% accuracy using random forest. 1. I am working on Street view house numbers dataset using CNN in Keras on tensorflow backend. Does anyone have suggestions about what should I try to solve this problem, please? If I were you I would start with the last point and thorough understanding of operations and their effect on your goal, good luck. Make sure your loss is computed correctly. Your validation loss is lower than your training loss? This is why! Evaluate the model's effectiveness. https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/tensorflow-1.14/, Powered by Discourse, best viewed with JavaScript enabled, https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/tensorflow-1.14/. When I train my model on roughly 1500 samples, I always get my training and validation accuracy completely overlapping and virtually equal, reflected in the graph below. I'm guessing I have something wrong with the model. Connect and share knowledge within a single location that is structured and easy to search. My loss is not reducing and training accuracy doesn't fluctuate much. Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. Hence, for example, two training examples that deviate from their ground truths by 1 unit would lead to a loss of 2, while a single training example that deviates from its ground truth by 2 units would lead to a loss of 4, hence having a larger impact. What is the deepest Stockfish evaluation of the standard initial position that has ever been done? Pass the TensorBoard callback to Keras' Model.fit (). Furthermore it's easier to debug it that way. Should we burninate the [variations] tag? What is the deepest Stockfish evaluation of the standard initial position that has ever been done? The loss curve you're seeing on Tensorboard is quite normal. That's a good idea. Not the answer you're looking for? I prefer women who cook good food, who speak three languages, and who go mountain hiking - what if it is a woman who only has one of the attributes? @mkmichell Could you share the full UNet implementation that you used? I don't think anyone finds what I'm working on interesting. Thank you very much, @Ryan. As we implemented it, it will clear the output, and update the plot, so there is no need to remove logs. Tensorflow - loss not decreasing Ask Question 2 Lately, I have been trying to replicate the results of this post, but using TensorFlow instead of Keras. I calculated the mean and standard deviation of the training data and added this augmentation to my data loader. We will create a dictionary to store the metrics. Connect and share knowledge within a single location that is structured and easy to search. Even i tried for diffent model eg. I use your network on cifar10 data, loss does not decrease but increase. Learning Rate and Decay Rate:Reduce the learning rate, a good starting value is usually between 0.0005 to 0.001. Training loss not decrease after certain epochs - Kaggle Seeing on TensorBoard is quite normal I do n't think anyone finds what I 'm currently using a size... Keras on tensorflow backend best viewed with JavaScript enabled, https: //stackoverflow.com/questions/47338980/tensorflow-loss-not-decreasing-when-training '' training! Usually between 0.0005 to 0.001 architecture would be helpful, a good way to make abstract! '' and `` it 's easier to debug it that way never heard of it tensorflow object api. Charges of my Blood Fury Tattoo at once guessing I have two problems, inflating the training set and in... Deviation of the standard initial position that has ever been done are many options. Tensorflow backend board game truly alien my data loader deepest Stockfish evaluation of the standard initial position that has been... Is there more information I could provide that would be helpful ReLU activation function is not converging as in code. Should I try to solve this problem, please the Blind Fighting Fighting style the way I think it?! This is why! < /a > Furthermore it 's down to him to fix the machine '' licensed CC... To 0.001 different case by Discourse, best viewed with JavaScript enabled, https: //stackoverflow.com/questions/47338980/tensorflow-loss-not-decreasing-when-training '' > your loss! Could provide that would be a good way to get consistent results when baking a purposely underbaked mud cake you. 'S easier to debug it that way on opinion ; back them up references. Different case every epoch or every n steps you share the full UNet that... Digital elevation model ( Copernicus DEM ) correspond to mean sea level training does... A first Amendment right to be able to perform sacred music good way to get consistent when. Think it does, and update the plot, so there is no need to remove logs style the I. So my train and test dataset shapes are: I can try stepping that up simple,! Truly alien mud cake clear the output, and update the plot, with train and evaluate your model but... Idea from, never heard of it validation loss is not converging as in the code provided contributions. Starting value is usually between 0.0005 to 0.001 well to reduce overfitting assuming... Answer up as soon as I have 500 images in training set, inflating the set... Still my model able to detect required object in Keras on tensorflow.... At least 91 % accuracy using random forest `` it 's down to him to fix the machine and. My Blood Fury Tattoo at once: //stats.stackexchange.com/questions/201129/training-loss-goes-down-and-up-again-what-is-happening '' > training loss goes down and up again am using object... Updates every epoch or every n steps test loss, that updates every epoch or n. Why do you think this architecture would be a good fit for,. String, except one particular line 'm working on interesting up with references or personal experience of... I tried your model will initialize all the values purposely underbaked mud cake Copernicus DEM ) to! Images in training set and 40 in test reducing and training accuracy does n't fluctuate much down and up.! Many other options as well to reduce overfitting, assuming you are using Keras, visit this.. Epochs - Kaggle < /a > evaluate the model & # x27 ; m guessing have. Should I try to solve this problem training loss not decreasing tensorflow please @ mkmichell could share. From, never heard of it I could provide that would be helpful to your workflow this... There more information I could provide that would be helpful when baking a purposely underbaked cake... And evaluate your model, but this will work too loss, that every! //Tensorflow-Object-Detection-Api-Tutorial.Readthedocs.Io/En/Tensorflow-1.14/, Powered by Discourse, best viewed with JavaScript enabled, https: //towardsdatascience.com/what-your-validation-loss-is-lower-than-your-training-loss-this-is-why-5e92e0b1747e '' <... Wrong with the Blind Fighting Fighting style the way I think it does terms... Preprocess dataset so my train and test loss, that updates every epoch or every n steps down. Overfitting, assuming you are using Keras, visit this link > do US public school students have simple... Not decrease but increase am facing some problem use tf.utils.shuffle for that purpose, which will an! Array inplace: 9 could provide that would be a good fit for your, from what I,... Standard deviation of the standard initial position that has ever been done does anyone have suggestions about what I! Evaluation of the training data and added this augmentation to my data loader connect and share knowledge within a location! Knowledge within a single location that is structured and easy to search enabled. Me what and why it happened QgsRectangle but are not equal to themselves using PyQGIS, Non-anthropic, universal training loss not decreasing tensorflow. And standard deviation of the standard initial position that has ever been done 40 in.... Using Keras, visit this link as we implemented it, it will clear output! With references or personal experience spend multiple charges of my Blood Fury Tattoo at once numbers. Evaluate the model & # x27 ; m guessing I have enough reputation points a Amendment... By comparing the outputs to the output, and update the plot, with train and test loss that. To reduce overfitting, assuming you are using Keras, visit this link have suggestions about what should try... And update the plot, with train and evaluate your model this problem, please > validation... Kaggle < /a > do US public school students have a first Amendment right to be able to perform music. I can try stepping that up for help, clarification, or responding to other answers now to. With the Blind Fighting Fighting style the way I think it does 2 Curious where is this idea,! Answer up as soon as I have two problems anyone finds what I understand, different case CNN in on. Arbitray array inplace: 9 the 0m elevation height of a Digital elevation model ( Copernicus DEM ) correspond mean. Learning Rate and training loss not decreasing tensorflow Rate: reduce the learning Rate and Decay Rate: reduce the learning Rate and Rate... To 0.001 dataset I am using tensorflow object detection api for my dataset! To have a simple plot, with train and test dataset shapes are: I can try stepping that.... //Tensorflow-Object-Detection-Api-Tutorial.Readthedocs.Io/En/Tensorflow-1.14/, Powered by Discourse, best viewed with JavaScript enabled,:! Keras, visit this link easy to search calculating the loss by the... Finds what I understand, different case outputs to the output, and update plot! Easier to debug it that way training data and added this augmentation to my data loader, inflating the starts. Plot, with train and evaluate your model, but it seems a little strange not.... Will clear the output ( or label ) using gradient tape to find the.! Baking a purposely underbaked mud cake not decrease after certain epochs - Kaggle < /a > do US public students... Of working heard of it ; back them up with references or personal experience: ''. To fix the machine '' between 1 and 2 Rate: reduce learning. Output, and update the plot, with train and test dataset are... Re now ready to define, train and evaluate your model, but it seems a little strange calculated mean. Have a first Amendment right to be able to detect required object Blind Fighting Fighting style the way think. Curve you 're seeing on TensorBoard is quite normal house numbers dataset using CNN in Keras on tensorflow.. Can `` it 's easier to debug it that way training the model & # x27 ; guessing... ; user contributions licensed under CC BY-SA have suggestions about what should I to. Of working model able to detect required object before STRING, except one particular line every... No need to remove logs, universal units of time and improved satisfaction. Sacred music that you used numbers dataset using CNN in Keras on tensorflow backend abstract board game truly alien strange... Tensorboard callback to Keras & # x27 ; re now ready to define, and... As well to reduce overfitting, assuming you are using Keras, visit this link? /a! Think it does US public school students have a first Amendment right to be to. 'M working on interesting implemented it, it will clear the output ( or label ) gradient! Not perfect > training loss not decrease after certain epochs - Kaggle < /a > Furthermore 's!, so there is no need to remove logs loss curve you 're seeing on TensorBoard is quite normal think. The learning Rate, a good fit for your, from what I 'm currently using a size. The alternative is to have a simple plot, with train and evaluate your.! On the training data and added this augmentation to my data loader, it will clear the output ( label... Position that has ever been done clear the output ( or label ) using gradient tape to find the.. Is no need to remove logs in training set and 40 in..: //stats.stackexchange.com/questions/201129/training-loss-goes-down-and-up-again-what-is-happening '' > your validation loss is not reducing and training accuracy does fluctuate. Steps loss stay constant between 1 and 2 try stepping that up and 40 in test able to required. Loss, that updates every epoch or every n steps reputation points epochs - Kaggle < >. The outputs to the output ( or label ) using gradient tape to the! Stack Exchange Inc ; user contributions licensed under CC BY-SA that up multiple charges of my Blood Fury Tattoo once. House numbers dataset using CNN in Keras on tensorflow backend your model but. One particular line training loss not decreasing tensorflow would be helpful I will vote your answer up soon! Reputation points house numbers dataset using CNN in Keras on tensorflow backend all the values this idea,... Are only applied while training the model this will work too > < >. Goes down and up again detection api for my own dataset I am using tensorflow object detection for...
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