If training fails to increase F1 above 0.0 exception thrown about jack

[dirkweissenborn]

if this happens, training has already stopped. However, this can only happen after max_epochs (a parameter of the training configuration dict when using train_tensorflow.py directly) is reached. This means that after max_epochs the model has never improved over 0.0 F1. So I would guess that max_epochs is set to something very low, like 1.

[antonyscerri]

Right now its set to 10 epochs. In this case we probably have insufficient/poor data for it to do anything with. However if it breaks with such an exception it makes it hard to see whats happening. I patched the local copy to check if the final model directory existed before trying to load and then evaluate against it, and instead output a different message.

[dirkweissenborn]

Perfect. The best solution to avoid this issue is to save the initial model before training will be fixed soon. Thanks for the catch.