Comments (2)
guillaumegenthial
commented on May 10, 2024
Hi @amundle-cs
That would be theoretically possible. 2 options:
- you run the evalutation out of the graph (for F1 score and accuracy) and give it back as a placeholder that you can then send to tensorboard.
- you use the latest version of the CRF (https://github.com/tensorflow/tensorflow/blob/r1.4/tensorflow/contrib/crf/python/ops/crf.py) that runs in graph so that you can compute the accuracy directly in the graph. For the F1 score, I think you would have to go for option 1 anyway.
Note that adding these metrics to tensorboard will slow down learning and should be done just for the development phase, to check that your model is learning!
Hope that helps.
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guillaumegenthial
commented on May 10, 2024
Maybe having a look at https://www.tensorflow.org/versions/r1.0/api_docs/python/tf/metrics/mean might help.
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