Updated to support Fastai v1
This callback plots training loss, validation loss, metrics, learning rate, and momentum. Every X iterations a snapshot of the model’s weights are logged and can be viewed in Tensorboard histogram and distribution tab. Every epoch, the embedding layers are saved and can be viewed in 3D with dimensionality reduction in the projector tab. Lastly, the model’s dataflow graph can be viewed in the graph tab.
pip install git+https://github.com/Pendar2/fastai-tensorboard-callback.gitLaunch the Tensorboard server with tensorboard --logdir="learn.path/logs", then navigate to localhost:6006