keras
seqeval
| keras | seqeval | |
|---|---|---|
| 3 | 1 | |
| 54,926 | 1,046 | |
| - | 0.7% | |
| 9.9 | 0.0 | |
| about 2 years ago | 15 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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keras
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Keras - Difference between categorical_accuracy and sparse_categorical_accuracy
The source code can be found here:
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keras error on predict
Here
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How to get reproducible results in keras
I get different results (test accuracy) every time I run the imdb_lstm.py example from Keras framework (https://github.com/fchollet/keras/blob/master/examples/imdb_lstm.py)The code contains np.random.seed(1337) in the top, before any keras imports. It should prevent it from generating different numbers for every run. What am I missing?
seqeval
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Beginner questions about NER model evaluation.
. The standard way to evaluate NER (or any other sequence labelling problem) is to use the conlleval script (https://www.clips.uantwerpen.be/conll2000/chunking/output.html) or through the seqeval package in python (https://github.com/chakki-works/seqeval) . Either way, you need a list of predicted labels and a list of gold labels (see the code example in the link, it should be trivial to converse your output to the same data format).
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