Comments (4)
It seems that your model didn't converge, the training loss is too large, you can try other optimizers like adam.
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Have you changed the blank label index ?
You'd better check the prediction.
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I didn't change, the blank label index is 0. Do I need to change? I checked the prediction, is all 0.
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This is my phone map, I used character based map. The first should be the blank, index is 0.
{'': 0, 'T': 1, 'U': 2, 'S': 3, 'N': 4, 'F': 5, 'A': 6, 'C': 7, 'H': 8, 'D': 9, 'R': 10, 'W': 11, 'V': 12, 'J': 13, 'L': 14, 'Y': 15, ' ': 16, 'M': 17, 'G': 18, 'I': 19, 'O': 20, 'K': 21, 'E': 22, 'B': 23, '': 24}
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Related Issues (20)
- mxnet.base.MXNetError: [11:42:46] src/operator/contrib/./rnnt_loss-inl.h:218: Check failed: dshape[0] == lshape[0] (474 vs. 1) The batch size for the labels and data arrays must be the same. HOT 16
- Put the testing process to gpu HOT 6
- Why adding a while loop when decoding on the gpu? HOT 10
- The performance gets worse when I use a bigger model HOT 11
- Phoneme Mapping HOT 2
- RNNTLoss issue with model 2013 HOT 2
- MXNet with Version 1.1.0 doesn't contain the install files (/docs/install), Version 1.4.x doesn't work (Shape Error) HOT 1
- Why should we use log_softmax when training?
- Loss is decrease but SER is increase
- A question about vocab_size
- mxnet.base.MXNetError: [16:48:44] ../src/operator/./rnn-inl.h:507: RNN on GPU is only available for cuDNN at the moment. HOT 1
- A Question About Padding
- What is the license for the code/model in this repository?
- DataLoader.py return these errors... HOT 1
- Model 2012 reproduce HOT 2
- A problem about getting 123 dim feature
- question in greedy decoder HOT 2
- Dataset and run.sh HOT 12
- src/operator/rnn.cc:254:30: error: ‘kCuDNNDropoutDesc’ is not a member of ‘mxnet::ResourceRequest’ HOT 2
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