Submitted by liberollo t3_104sw4a in deeplearning

Is there a way to easily do that?
I would be able to automatically log every experiment I do, like I change a layer/optimizer or whatever, train the model, and I get logged the accuracies, model details ecc. how do you do that?

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ekbravo t1_j370wqd wrote

Check out weights and biases website WandB.com That’s exactly what it does.

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Just_CurioussSss t1_j37t9e5 wrote

Have you tried using tools such as TensorBoard, which is a visualization tool for TensorFlow that can be used to track the performance of your Keras models?
To use TensorBoard with Keras, you will need to install TensorFlow and modify your Keras code to write log files that TensorBoard can read. This can be done by using the TensorBoard callback provided by Keras, which writes log files to a specified directory that TensorBoard can use to visualize the results of your training runs.
Here is an example of how you might use the TensorBoard callback in your Keras code:

from tensorflow.keras.callbacks import TensorBoard
# Create a TensorBoard callback
tensorboard_callback = TensorBoard(log_dir='/path/to/logs')
# Compile and fit your Keras model
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
model.fit(x_train, y_train, epochs=10, callbacks=[tensorboard_callback])

After you have trained your model, you can start TensorBoard by running the tensorboard command in a terminal, specifying the directory where the log files are stored. TensorBoard will then start a web server that you can access in a web browser to visualize the results of your training runs.

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Clicketrie t1_j37zi1a wrote

Comet has an integration with Keras (disclosure: I work for Comet). But it does exactly what you're looking for and it's super easy.

The Comet integration with Keras automatically logs the following items:

  • Model and graph description.
  • Steps and epochs.
  • Metrics (such as loss and accuracy)
  • Hyperparameters.
  • Optimizer Parameters (such as the learning rate, beta decay rate, and more)
  • Number of trainable parameters.
  • Histograms for weights and biases.
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mmeeh t1_j3avzl1 wrote

Check out the website neptune ai. I'm not paid to say it but they are pretty awesome.

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1