Comments (6)
run python prepro.py
before running python train.py
. Please read the instructions carefully.
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I ran python prepro.py
already and it took over 10 hours to complete but I didn't see the file. If it comes after running the script, I'll try again and see if that helps.
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What's your spacy version? if you follow all instructions and install spacy==1.9 the prepro script should only take 1~2 minutes.
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@hitvoice
It seems like the annotate function from SpaCy will eat up lots of memory (>10GB)
during the data preparation process. If the machine doesn't have enough RAM, the process will turn out to be extremely slow. I guess it is what @YuanTW was experiencing.
Not sure if it is a memory leakage problem for SpaCy.
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@tim5go I didn't pay attention to the memory usage before. I'll check that.
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@tim5go I ran the script again and indeed, the memory keeps increasing to about 10G. I didn't figure out the exact reason and I'll add a warning to ReadMe. Thanks for reporting this!
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Related Issues (20)
- no model file HOT 2
- Adding Evidence as Database (like wikipedia ) HOT 5
- Only decode on a test set HOT 3
- How long to run the model for the default params HOT 2
- Is there a way to know the score of the prediction to analyse whether it is right or wrong? HOT 1
- planning to implement Attend It Again paper. HOT 2
- Using DrQA on an Chinese dataset HOT 3
- using DrQA for Squad 2.0 and other datasets HOT 1
- train stop HOT 3
- Finetune against a custom dataset HOT 1
- AssertionError: Torch not compiled with CUDA enabled HOT 2
- Regarding train.py HOT 2
- msgpack.exceptions.UnpackValueError: Unpack failed: error = 0 HOT 1
- Trying to understand the index_answer funtion HOT 6
- Getting low F1 and EM scores HOT 1
- Different function of evaluating metrics
- Gradient flow of the failing model
- training stopped at epoch 1 HOT 9
- Cant do "bash" HOT 7
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