You see weird connections, because you restarted you training (or resumed) with the same name without setting the epoch (or step) to the correct resumed value. If your last datapoint is at step=10 you should continue saving data at step=11 not step=0. Otherwise the last value at step=1o will be conntect to a new value at step=0 which causes the observed connection. On first training with clean log files, this will not happen. Either choose a new name, or resume with proper step or epoch.
smoothing
It's not a bug, it's a feature! Often training progress fluctuates a lot, making it hard to observe a general trend. Smoothing the time series allows you to quickly understand where the training is going.
Look at this GAN Generator training. On the first image, without smoothing, its hard to tell what is happening.
weird connections
You see weird connections, because you restarted you training (or resumed) with the same name without setting the epoch (or step) to the correct resumed value. If your last datapoint is at
step=10you should continue saving data atstep=11notstep=0. Otherwise the last value atstep=1owill be conntect to a new value atstep=0which causes the observed connection. On first training with clean log files, this will not happen. Either choose a new name, or resume with propersteporepoch.smoothing
It's not a bug, it's a feature! Often training progress fluctuates a lot, making it hard to observe a general trend. Smoothing the time series allows you to quickly understand where the training is going.
Look at this GAN Generator training. On the first image, without smoothing, its hard to tell what is happening.
Activating smoothing allows easier interpretation.