How to use the fine-tuned bert pytorch model for classification (CoLa) task?
I do not see the argument --do_predict
, in /examples/run_classifier.py
.
However, --do_predict
exists in the original implementation of the Bert.
The fine-tuned model is getting saving in the BERT_OUTPUT_DIR as pytorch_model.bin
, but is there a simple way to reuse it through the command line?
Using Pytorch implementation from: https://github.com/huggingface/pytorch-pretrained-BERT
The command which I am using to execute the code is:
python run_classifier.py \
--task_name CoLA \
--do_train \
--do_eval \
--do_lower_case \
--data_dir ./split/ \
--bert_model bert-base-uncased \
--max_seq_length 128 \
--train_batch_size 32 \
--learning_rate 2e-5 \
--num_train_epochs 3.0 \