NER predict only mode

[UrszulaCzerwinska]

I would like to use NER model I fine-tune with

python run_ner.py \
    --do_train=true \
    --do_eval=true \
...

to make prediction on sentences without labels (without evaluation of course)

But

python run_ner.py \
    --do_train=false \
    --do_eval=false \
    --do_predict=true \
...

gives me error:

raise ValueError("At least one of `do_train` or `do_eval` must be True.")
ValueError: At least one of `do_train` or `do_eval` must be True.

How can I make predictions without having evaluation?

[jhyuklee]

Hi @UrszulaCzerwinska ,
you can just comment the line below:

biobert/run_ner.py

Lines 477 to 478 in 7a3c96e

	if not FLAGS.do_train and not FLAGS.do_eval:
	raise ValueError("At least one of `do_train` or `do_eval` must be True.")

but this could cause other issues if do_eval and do_predict have unintended dependencies.
Thanks.

[wonjininfo]

Hi,
I am writing this comment since the issue #50 mentioned this issue.

One simple way to bypass " At least one of do_train or do_eval must be True. " error is to set
(1) --do_train=true
(2) --num_train_epochs=0.1 (or less than pre-trained ckpt)
(3) --output_dir=(as your pre-trained model)
(4) (optional) --init_checkpoint=(as your pretrained model)
and this will skip training steps.

For example,

python run_ner.py \
    --vocab_file=$BIOBERT_DIR/vocab.txt \
    --bert_config_file=$BIOBERT_DIR/bert_config.json \
    --init_checkpoint=$BIOBERT_DIR/biobert_model.ckpt \
    --data_dir=$NER_DIR/ \
    --do_train=true \
    --do_predict=true \
    --num_train_epochs=0.1 \
    --output_dir=/tmp/bioner/(pre-trained dir) 

How it works

Our code (and also BERT) checks whether the model in the output folder is already trained.
Therefore setting --num_train_epochs less than the epochs, which the pre-trained model in the output folder went through, will make the code skip training and just perform prediction.
(You will see a message INFO:tensorflow:Skipping training since max_steps has already saved. from the middle of the console output.)

I will check with other colleagues about the line,
Please use our "bypass method" until then.
Thanks!
Wonjin