Comments (2)
Hmm, interesting. Thanks for finding this! I dug into it a bit and discovered that it's due to the relu
activation in the feedforward layer. The initialization happens to be such that the activations going into the relu
are all negative, and so the gradient gets zeroed out. This is only an issue because the network is so small, and the particulars of how the random seed gets used must have changed since we first wrote the test, so now we get an initialization that consistently fails.
I fixed this by switching the relu
activation to a sigmoid
activation, and now the tests pass.
from allennlp-as-a-library-example.
Thanks!
from allennlp-as-a-library-example.
Related Issues (11)
- Fail to load model archive after training HOT 4
- Dead code in paper_classifier_predictor.py HOT 1
- training failing with "cuda_device": 0 HOT 3
- Make releases for versions that this tutorial covers HOT 1
- Running AcademicPaperClassifierTest, dataset_reader's type not found. HOT 2
- Multi labels prediction using Allennlp
- key "type" required at location "model.text_field_embedder." HOT 6
- Update to the latest Allennlp version
- Tutorial no longer works out of the box HOT 21
- Unable to --include-package my_library HOT 6
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from allennlp-as-a-library-example.