Comments (1)
There is something like "better do like that" :) and you have two ways:
- (but that will reset progress thru training file)
- just break training right after every 1k of steps (when checkpoint is saved)
- change settings in setup/settings.py
- uncomment 'override_loaded_hparams' as well, but only for next training reset
- reset training
- break training process just after next 5k of steps - eval is done every 5k of steps and hparams file inside model folder as well (you wan to keep track of progress thru training set)
- change settings in model/hparams
- restart training
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Related Issues (20)
- Chatbot only produces 1 answer despite beam width being 20 HOT 4
- Can't run train.py HOT 7
- Train.py says it's finished training after 1 second. HOT 2
- ERROR: cannot import name 'nmt' from 'nmt' HOT 2
- FileNotFoundError: [Errno 2] No such file or directory: 'data//corpus_size'
- nmt: [ deleted ] while training
- Trained Model ? HOT 1
- does this work with tensorflow 2.0?
- is it supposed to just be stopped on this
- 2021-05-06 22:03:17.947802: I tensorflow/core/kernels/shuffle_dataset_op.cc:121] Shuffle buffer filled.
- decoding to output F:\Nebula0.0.5\nmt-chatbot\model\output_dev.
- from nmt import nmt : error
- TypeError: 'encoding' is an invalid keyword argument for this function HOT 1
- Inference returning the same empty answer to everything i type HOT 1
- bot producing only one translation per input
- Cannot Downgrade Tensorflow 1.x on Google Colab
- how do i make it train more epoch like 10000
- cannot import name 'nmt' from 'nmt'
- Issue with tensorflow api and pip installation candidate missing before 2.x
- cannot import name 'lookup_ops' from 'tensorflow.python.ops'
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