TensorBoard | TensorFlow
https://www.tensorflow.org/tensorboardTensorBoard provides the visualization and tooling needed for machine learning experimentation: Tracking and visualizing metrics such as loss and accuracy. Visualizing the model graph (ops and layers) Viewing histograms of weights, biases, or other tensors as they change over time. Projecting embeddings to a lower dimensional space.
TensorBoard | TensorFlow
www.tensorflow.org › tensorboardTensorBoard provides the visualization and tooling needed for machine learning experimentation: Tracking and visualizing metrics such as loss and accuracy. Visualizing the model graph (ops and layers) Viewing histograms of weights, biases, or other tensors as they change over time. Projecting embeddings to a lower dimensional space.
torch.utils.tensorboard — PyTorch 1.10.1 documentation
pytorch.org › docs › stablePlotting a precision-recall curve lets you understand your model’s performance under different threshold settings. With this function, you provide the ground truth labeling (T/F) and prediction confidence (usually the output of your model) for each target. The TensorBoard UI will let you choose the threshold interactively. Parameters