![python - Sparse Categorical Crossentropy Loss Seems Scaled Really High, Despite Very Successful Model - Stack Overflow python - Sparse Categorical Crossentropy Loss Seems Scaled Really High, Despite Very Successful Model - Stack Overflow](https://i.stack.imgur.com/d1ytN.png)
python - Sparse Categorical Crossentropy Loss Seems Scaled Really High, Despite Very Successful Model - Stack Overflow
![Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names](https://gombru.github.io/assets/cross_entropy_loss/softmax_CE_pipeline.png)
Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names
![Using loss=Sparse categorical cross entropy returned an issue - General Discussion - TensorFlow Forum Using loss=Sparse categorical cross entropy returned an issue - General Discussion - TensorFlow Forum](https://discuss.tensorflow.org/uploads/default/original/2X/a/ac60a34a35e5901235ba0d830d6a7ea6866dea2a.png)
Using loss=Sparse categorical cross entropy returned an issue - General Discussion - TensorFlow Forum
![Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names](https://gombru.github.io/assets/cross_entropy_loss/intro.png)
Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names
![Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names](https://gombru.github.io/assets/cross_entropy_loss/multiclass_multilabel.png)
Understanding Categorical Cross-Entropy Loss, Binary Cross-Entropy Loss, Softmax Loss, Logistic Loss, Focal Loss and all those confusing names
Santiago on X: "Instead of using Sparse Categorical Cross Entropy, use Categorical Cross Entropy. https://t.co/rdudIBNkkc" / X
![python - Sparse Categorical Crossentropy Loss Seems Scaled Really High, Despite Very Successful Model - Stack Overflow python - Sparse Categorical Crossentropy Loss Seems Scaled Really High, Despite Very Successful Model - Stack Overflow](https://i.stack.imgur.com/xuCiv.png)
python - Sparse Categorical Crossentropy Loss Seems Scaled Really High, Despite Very Successful Model - Stack Overflow
![Sparse Categorical Cross-Entropy | Explanation and Practical Tips | Deep learning Tutorial - YouTube Sparse Categorical Cross-Entropy | Explanation and Practical Tips | Deep learning Tutorial - YouTube](https://i.ytimg.com/vi/SIoo6NTH88U/sddefault.jpg)
Sparse Categorical Cross-Entropy | Explanation and Practical Tips | Deep learning Tutorial - YouTube
![Santiago on X: "The loss is categorical cross-entropy. In English: we want to predict a single class for each image. By adding "accuracy" to the metrics, the training process will record the Santiago on X: "The loss is categorical cross-entropy. In English: we want to predict a single class for each image. By adding "accuracy" to the metrics, the training process will record the](https://pbs.twimg.com/media/Eu9csOhXYAAhR5b.jpg:large)
Santiago on X: "The loss is categorical cross-entropy. In English: we want to predict a single class for each image. By adding "accuracy" to the metrics, the training process will record the
![objective functions - Why does TensorFlow docs discourage using softmax as activation for the last layer? - Artificial Intelligence Stack Exchange objective functions - Why does TensorFlow docs discourage using softmax as activation for the last layer? - Artificial Intelligence Stack Exchange](https://i.stack.imgur.com/uGw1c.jpg)