Comments (1)
This is how i understood it.
comment this line and run the training epochs. Once you have trained models or checkpoints, replace the commented checkpoint_name with recently trained checkpoint and run training again.
Only this time, the accuracy and validation accuracy will start from where the last training epoch ended.
"It improves the precision of trained model"
from text-emotion-classification.
Related Issues (18)
- Additional Data Processing if using other GLoVE
- Meaning of emotion labels HOT 2
- ValueError: None values not supported. HOT 3
- Converting sparse IndexedSlices to a dense Tensor of unknown shape.
- Requirements.txt file
- no module named _pywrap_tensorflow
- Where is your dataset with the 5 classes ? HOT 1
- when checking target: expected dense_6 to have shape (4,) but got array with shape (5,) HOT 1
- model doesn't learn
- Published or Referable source for wordlists HOT 2
- Version
- Version Issues
- Wrong dataset
- Please add requirements.txt file.
- please add requirements file
- No paper? HOT 3
- Not end train cycle HOT 4
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from text-emotion-classification.